Modeling Complexity of Enterprise Routing Design

Xin Sun Sanjay G. Rao Geoffrey G. Xie School of Computing and School of Electrical and Department of Computer Information Sciences Computer Engineering Science Florida International University Purdue University Naval Postgraduate School xinsun@cs.fiu.edu [email protected] [email protected]

ABSTRACT to choose from [23]. Often, multiple designs exist to meet the same operational objectives, and some are significantly Enterprise networks often have complex routing designs given easier to implement and manage than others for a target net- the need to meet a wide set of resiliency, security and rout- work. For example in some cases, route redistribution may ing policies. In this paper, we take the position that minimiz- be a simpler alternative to BGP for connecting multiple rout- ing design complexity must be an explicit objective of rout- ing domains [16]. Lacking an analytical model to guide the ing design. We take a first step to this end by presenting a operators, the current routing design process is mostly ad systematic approach for modeling and reasoning about com- hoc, prone to creating designs more complex than necessary. plexity in enterprise routing design. We make three contri- butions. First, we present a framework for precisely defining In this paper, we seek to quantitatively model the com- objectives of routing design, and for reasoning about how a plexity associated with a routing design, with a view to de- combination of routing design primitives (e.g. routing in- veloping alternate routing designs that are less complex but stances, static routes, and route filters etc.) will meet the ob- meet the same set of operational objectives. Quantitative jectives. Second, we show that it is feasible to quantitatively complexity models could enable systematic abstraction-driven measure the complexity of a routing design by modeling in- top-down design approaches [23], and inform the develop- dividual routing design primitives, and leveraging configura- ment of clean slate network architectures [9, 13], which tion complexity metrics [5]. Our approach helps understand seeks to simplify the current IP network control and man- how individual design choices made by operators impact agement planes. configuration complexity, and can enable quantifying design The earliest and most notable work on quantifying com- complexity in the absence of configuration files. Third, we plexity of network management was presented by Benson et validate our model and demonstrate its utility through a lon- al. [5]. This work introduceda family of complexitymetrics gitudinal analysis of the evolution of the routing design of that could be derived from router configuration files such as a large campus network over the last three years. We show dependencies in the defintion of routing configuration com- how our models can enable comparison of the complexity of ponents. The work also showed that networks with higher multiple routing designs that meet the same objective, guide scores on these metrics are harder for operators to manage, operators in making design choices that can lower complex- change or reason correctly about. ity, and enable what-if analysis to assess the potential impact While [5] is an important first step, it takes a bottom-up of a configuration change on routing design complexity. approach in that it derives complexity metrics from router configuration files. This approach does not shed direct light 1 Introduction on the intricate top-downchoices faced by the operatorswhile Recent studies [16,20] show that routing designs of many designing a network. Conceivably, an operator could enu- enterprise networks are much more complicated than the merate all possible designs, translate each into configura- simple models presented in text books and router vendor tions, and finally quantify the design complexity from the documents. Part of the complexity is inherent, given the configurations. However, such a brute-force approach may wide range of operationalobjectives that these networks must only work for small networks where the design space is rel- support, to include security (e.g., implementinga subnet level atively small. Additionally, this approach still requires a reachability matrix), resiliency (e.g., tolerating up to two model to determine which designs actually are correct, i.e., component failures), safety (e.g., free of forwarding loops), meeting the design objectives. performance, and manageability. There is also evidence, In this paper, we present a top-down approach to char- however, to suggest that some of the network design com- acterizing the complexity of enterprise routing design given plexity may have resulted from a semantic gap between the only key high-level design parameters, and in the absence high level design objectives and the diverse set of routing of actual configuration files. Our model takes as input ab- protocols and low level router primitives for the operators stractions of high-level design objectives such as network

1 topology, reachability matrix (which pairs of subnets can physical topology has been constructed, including three sub- communicate), and design parameters such as the routing in- nets (Sales, Support and Data Center) in the main building stances [20] (see Section 2 for formal definition), and choice and two additional subnets in building 2. of connection primitive (e.g., static routes, redistribution etc). Our overall modeling approach is to (i) formally abstract the 2.1 Policy groups operational objectives related to the routing design which can help reason about whether and how a combination of de- An integral part of almost every enterprise’s security policy sign primitives will meet the objectives; and (ii) decompose is to compartmentalize the flow of corporate information in routing design into its constituent primitives, and quantify its network. For the example network, there are two cate- the configuration complexity of individual design primitives gories of users: Sales and Support. Suppose the Data Center using the existing bottom-up complexity metrics [5]. subnet contains accounting servers that should be accessible A top-down approach such as ours has several advantages. only by the Sales personnel. A corresponding requirement By working with design primitives directly (independent of of routing design would be to ensure that only the Sales sub- router configuration files), the model is useful not only for nets have good routes to reach the Data Center subnet. analyzing an existing network, but also for “what if” analy- We refer to the set of subnets belonging to one user cat- sis capable of optimizing the design of a new network and egory and have similar reachability requirements as policy similarly, a network migration [24], or evaluating the poten- group. We note that policy groups are similar to policy units tial impact of a change to network design. Further, our mod- introduced in [6], though there are some differences (see els help provide a conceptual framework to understand the Sec. 9). A primary source of complexity for routing design underlying factors that contribute to configuration complex- is to support the fine grained reachability requirements of ity. For example, reachability restrictions between subnet policy groups. This is particularly challenging since busi- pairs may require route filters or static routes, which in turn ness stipulations often imply that subnets of a policy group manifest as dependencies in network configuration files. may need to be distributed across multiple buildings, multi- We demonstrate the feasibility and utility of our top-down ple enterprise branches, or even multiple continents. complexity modeling approach using longitudinal configu- The operator faces several choices in designing networks ration data of a large-scale campus network. Our evalua- to meet these reachability requirements. The operator may tions show that our model can accurately estimate configu- choose to deploy a single IGP over the entire network to ration complexity metrics given only high-level design pa- allow full reachability and then place packet filters on se- rameters. Discrepancies when present were mainly due to lected router interfaces to implement the required reacha- redundant configuration lines introduced by network opera- bility policy. This is a viable solution for small networks. tors. Our models provided important insights when applied However, for medium to large networks, a large number of to analyzing a major routing design change made by the op- filtering rules need to be configured, and on many router in- erators undertakenwith an explicitgoal to lower design com- terfaces. Doing so will likely introduce performance prob- plexity. Our model indicated that while some of the design lems because packet filters incur per packet processing. In changes were useful in lowering complexity, others in fact addition, according to a recent study [23], proper placement were counter-productive and increased complexity. Further, of packet filters in itself is a complex task, particularly when our models helped point out alternate designs that could fur- the solution must be resilient against link failures and other ther lower complexity. changes in the network topology. 2 Dimensions of Routing Design Alternatively, the operator may choose to deploy a sepa- rate routing protocol instance to connect the subnets of each According to most computer networking textbooks, routing policy group. For the example network, two independent design is nothing more than selecting and configuring a sin- OSPF instances (OSPF 10 and OSPF 20)may be used to join gle interior gateway protocol (IGP) such as OSPF on all the subnets of Sales and Support, respectively. Such a design routers and setting up one or more BGP routers to connect is not straightforward either. First, the operator must decide to the Internet. In reality, as one would quickly discover which routers to include in each routing instance, subject to from meetings and online discussion forums of the opera- additional requirements such as resiliency. Second, the oper- tional community, network operators consistently rate rout- ator must select a small number of routers as border routers ing design as one of the most challenging tasks. and configure connecting primitives [16,19] to “glue” the In this section, using a toy example, we briefly breakdown different routing protocol instances together. (The next sec- the challenges of routing design along two structural dimen- tion has a detailed description of the tradeoffs involved in sions, each made of a distinct logical building block. The this step.) Last but not the least, the operator may need to goal is to identify the general sources of its complexity by configure route filters at the border routers to implement the exposing the major design choices that operators must make. required reachability policy. For the example network, route Consider Fig. 1, which illustrates a hypothetical company filters should be configured to prevent routes to Data Center network that spans two office buildings. Assume that the subnets from leaking into Support.

2 main eBGP Z3 ISP building 2 building ISP EIGRP 10 XZ1 Z2

Y3 Sales Sales X1 X2 Y1 Y2 Sales Sales Support OSPF 10 OSPF 20 Support Support Data-Ctr Data-Ctr Support

Figure 1: Example enterprise network spanning two offices Figure 2: A design with multiple IGP instances

Si subnet i Ri router i Ii routing instance i Zi policy group i 2.2 Routing instances MC connecting primitive matrix MR reachability matrix MB border-router matrix MX route-exchange matrix In several recent papers [4,16,20], researchers have revealed MA arc matrix Ti the internal routes that Ii has the common use of multiple routing protocol instances in Wi the entire set of routes that Ii f(x) complexity of configuring a has route filter to allow a set of one enterprise network. This is not surprising as the evo- routes x lution of an enterprise’s computer network parallels that of |x| size of the set x Krr complexity of configuring one- way route redistribution its business. Networks of different routing designs are fused Ksr complexity of configuring one Kbgp complexity of configuring a at times of company mergers and acquisitions. Also, large static route BGP peering session on one border router enterprises and universities are usually made of a group of Kobj complexity of configuring ob- h(i, j) a binary function denoting autonomous business units with quasi-independent IT staff; ject tracking for one static route whether filtering is needed MP eBGP-peering matrix Kdr complexity of configuring a de- each unit often has a large degree of freedom in managing its fault route part of the enterprise network, including the choice of which routing protocol to use. Table 1: Notation table We adopt from these prior works the definition of a rout- ing protocol instance, or simply routing instance, to refer to tion and possibly route filters to allow the injection of routes a connected component of the network where all member between the two instances. Another complication is that routers run the same routing protocol, use matching proto- multiple routing instances may simultaneously offer routes col parameters, and are configured to exchange routes with to the same destination at a border router. The operator must each other. When dealing with a routing design with multi- implement the correct order of preference between the in- ple routing instances, the operator must weigh different op- stances, sometimes requiring an override of some protocols’ tions of joining the different routing instances together while default Administrative Distance (AD) [4,18] values on a per implementing the company’s security policy. border router basis. To illustrate, suppose the operator of the example network For connecting the routing instances of OSPF 20 and the of Fig. 1 has created a routing design with three routing in- backbone, the operator has adopted a different approach. stances, as shown in Fig. 2. Each office building has its own Two border routers (i.e., Y3 and Z2) are used as in the case routing instance (OSPF 10 or OSPF 20) while the EIGRP 10 of the ISP connection. However, instead of using a dynamic instance serves as the backbone of the network. protocol, the operatorhas configuredtwo sets of static routes, The operator has chosen to use BGP to connect to the In- on the two border routers respectively, to achieve reachabil- ternet. It is straightforward to configure an external BGP ity across routing instances. This design incurs considerable (eBGP) peering session and mutual route redistribution (RR) amount of manual configuration on a per destination prefix between the EIGRP and BGP instances to allow routes to be basis. For example, on Y3, static routes are required for des- exchanged between the enterprise network and its ISP. The tination prefixes not only within EIGRP 10 but also within complexity increases significantly, however, if the operator OSPF 10. Clearly, due to its static nature, the design may needs to configure route filters to reject certain incoming not bode well when the subnet prefixes frequently change or and outgoing routes. The problem would be compounded dynamic re-routing is required. However, it has one advan- for multi-homed enterprise networks because of additional tage over dynamic mechanisms like BGP or co-location of policy requirements such as the designation of primary and routing processes in one border router: the packet forward- backup or load balancing. ing paths across routing instances are much easier to predict For connecting the routing instances of OSPF 10 and the when hardcoded. In contrast, both BGP and RR can result in backbone, the operator has chosen to use a single border routing anomalies in ways that are difficult to identify from router (i.e., XZ1) that participates in both routing instances. their configurations [18]. (For brevity, we do not consider the resiliency requirement in this example.) This removes the need for BGP peering 3 Abstractions for Modeling Routing Design to advertise routes across the boundaries of the instances. This section first presents a set of formal abstractions that However, the operator must still configure route redistribu- capture the routing design primitives, and design objectives

3 and constraints. These abstractions form the foundation for Router 1 modeling design complexity. We then describe the metrics 1. interface GigabitEthernet 1/1 2. ip address 10.1.0.1 255.255.255.252 we used for quantifying the complexity of a given design 3. ! 4. router eigrp 10 instance that makes use of a specific set of design primitives 5. distribute-list prefix TO-SAT out GigabitEthernet1/1 6. ! and targets a specific network topology. Table 1 summarizes 7. ip prefix-list TO-SAT seq 5 permit 192.168.1.0/24 the notations used in this and the following sections. 8. ip prefix-list TO-SAT seq 10 premit 192.168.5.0/24 Router 2 1. interface FastEthernet1/1 3.1 Abstracting essential elements of routing design 2. ip address 192.168.1.1 255.255.255.0 3. ! S ,S , ... 4. interface FastEthernet2/1 We use 1 2 to denote the host subnets in the network. 5. ip address 192.168.5.1 255.255.255.0 Each subnet is assigned a unique IP prefix address (e.g., 6. ! “192.168.1.0/24”). We use R1, R2, ... to denote the routers in the network. Each subnet connects to a router and uses Figure 3: Configuration snippets of two routers. that router as its gateway (i.e. the router routes all the pack- ets generated by the subnet). A “route” is considered as an IP prefix address, plus additional attributes (e.g., weight) also given the connecting primitive matrix MC. Each cell M that may be used for calculation of a next-hop for the route. C(i, j) specifies the connecting primitive used by Ii and A router always has routes to all the connected subnets for Ij , to allow routes to be sent from Ii to Ij . which it is the default gateway. In addition, routes may be In this paper, we focus on the primary use of routing de- manually injected into a router via configuration of static sign: implementing reachability policies. The primary layer- routes (Sec. 5.3). Routers may exchange routes by running three mechanisms to implement reachability are the connect- one or more dynamic routing protocols. To participate in ing primitives and route filters. We do not model the se- each routing protocol, a router must run a separate routing lection logic, which is used to prefer one routing path over process. Each routing process maintains a separate Routing another, as this is typically used for traffic engineering pur- Information Base, or RIB. The RIB contains all the routes poses, rather than implementing reachability. known to the routing process, each associated with one or more next-hops. A router maintains a global RIB (also re- 3.2 Abstracting design objectives and constraints ferred to as the forwarding information base, or FIB, in the literature), and uses selection logic to select routes from its The design objectives and constraints considered in this pa- routing process RIBs, as well as routes to connected sub- per include reachability and resiliency, as well as routing nets and statically configured routes, to enter the global RIB. path policies. First, to capture the reachability requirements, M A router uses the global RIB to make forwarding decisions. it is assumed that we are given the reachability matrix R. M (Readers are referred to [20] for a moredetailed description.) Each cell R(i, j) denotes whether the subnet Si can reach the subnet S . Note that in the routing design we only con- We say that “a router R has a route to a subnet S ”, if j i j sider reachability at the subnet level. We do not consider the prefix address of S matches a route in the global RIB j host-level reachability as it is typically implemented by data of R . Furthermore, we say that “a subnet S is routable i i plane mechanisms such as packet filters. from another subnet Sj ”, if the gateway router for Sj has a route to S . Finally, since this paper concerns only the To capture the resiliency requirement, we assume that we i M M routing design and uses routing as the only mechanism to are given the border-router matrix B. Each cell B(i, j) implement reachability, we use the terms “reachable” and specifies the set of Ii’s border routers that enable Ii to adver- “routable” inter-changeably. tise routes to Ij . Note that a routing instance may use differ- ent border routers to communicate with different neighbor- Let I = {I1, I2, ...} denote the set of routing instances (Sec. 2.2), an essential routing design component that ab- ing instances. stracts route propagation in the network. As described in To capture the path policies, it is assumed that we are Sec. 2.2, routing processes in the same routing instance ex- given the route-exchange matrix MX. Each cell MX(i, j) change all their routes freely. As a result, all the routing specifies the set of routes that Ii should advertise to Ij to processes share the same set of routes. To change this behav- meet the reachability requirement. We assume that the routes ior, route filters are typically used to filter route updates be- in the matrix is in the most aggregated form. Clearly the set M tween routing processes (Sec. 4). On the other hand, routing of external routes that Ii has may be calculated as Sj X(j, i). processes in different routing instances do not exchange any Let Ti denote the set of internal routes that Ii has (i.e., routes route. To change this behavior, connecting primitives must originated by subnets inside Ii). Let Wi denote the entire set be used (e.g., static routes, route redistribution and BGP). of routes that Ii has, which may be calculated as follows: The routers where connecting primitives are implemented M are termed border routers. Wi = ([ X(j, i)) [ Ti (1) We assume that we are given the set of routing instances j I and their member routers and routing processes. We are

4 3.3 Measuring complexity S1 routing instance I1 R5 Using these abstractions, we are able to precisely define the S2 S4 R6 objectives, or the correctness criteria, of a routing design, R3 R1 R4 S3 S1 S2 S3 S4 AS2 R7 S1 Y Y Y N Y and reason about how a combination of routing primitives S2 Y Y Y N Y R2 S3 Y Y Y Y N (e.g., routing instances, static routes, route filters, etc.) will S4 N N Y Y Y to AS2 meet the objectives. We then leverage metrics developed by AS2 Y Y N Y Y previous work to measure how the choice of different rout- (a) An example network and reachability policy. The matrix has ing primitives may impact the complexity of the resulting one row (column) per subnet. Y (N) indicates the subnets can network. (cannot) reach each other. The particularmetric that we use is proposedby[5], which R5 captures the complexity in configuring a network by count- Z1 ing the number of reference links in the device configuration R6 R3 R1 R4 Z3

files. Basically a reference link is created when a network Z2 R7 R2 V object (e.g., a route filter, a subnet) is defined in one con- R VB figuration block, and is subsequently referred to in another VZ VX configuration block, in either the same configuration file or a AS2 different file. As an example, consider Fig. 3 that shows con- (b) The per-instance routing graph of routing instance I1 figuration snippets from two routers. The referential links are shown in italics. In line 5 in Router 1’s configuration, a Figure 4: Illustrating need for route filters. route filter named TO-SAT is applied to the interface Giga- bitEthernet1/1 to filter two routes in the outgoing direction. This line introduces two reference links: one to the name of 4.1 Source of intra-instance complexity filter (defined in line 7-8), and the other to the name of the The complexity within a routing instance primarily comes interface (defined in line 1). Moreover, the definition of the from the route filters installed inside the instance. By defini- route filter (lines 7-8) introduces two reference links to the tion, all routing processes of the same routing instance have two subnet prefixes, which are defined in Router 2’s config- the same routing tables. This means that all the subnets con- uration file (line 2 and 5). Clearly, the existence of refer- necting to those routing processes will have the same reach- ence links increases the configuration complexity as it intro- ability toward other subnets. If this is not desired, route fil- duces dependencies between configuration blocks either in ters must be used to implement reachability policies inside a the same configuration file or in different configuration files. routing instance. We choose to use this metric because it has been exten- As an example, consider the example network shown in sively validated in [5] through operator interviews. Our own Fig. 4a. Routers R1-R7 and subnetsS1-S4 are placed in rout- interaction with operators also suggests that the metric re- ing instance I1. Border router R2 runs eBGP with another flects operator perceived complexity reasonably well. We autonomous system AS2 and injects eBGP learned routes to note that other complexity metrics have been proposed in I1. The figure also shows the desired reachability matrix. [5] such as the number of routing instances, and the number To implement the reachability matrix, route filters must be of distinct router roles. Many of these other metrics are rel- carefully placed. For example, to prevent S1 and S2 from atively straight-forward to estimate from the design. For ex- reaching S4, while permitting S3 to reach S4, route filters ample, the number of distinct router roles could be estimated must be installed between R3 and R5, and between R3 and based on the insight that border and non-border routers play R6. Similarly, a route filter must be installed between R1 different roles. Further, we have observed in our evaluation and R4 to prevent S4 from reaching S1 and S2. In addition, settings that the reference link metric shows the most varia- another route filter must be installed between R3 and R7, to tion across designs, making it particularly useful in facilitat- prevent S3 from reaching the external routes of I2. ing comparisons. In general, the degree of diversity in terms of reachability 4 Modeling Intra-Instance Complexity among subnets of the same routing instance directly impacts the amount of filtering required, which in turn determines This section presents a framework for estimating complexity the complexity inside that instance. To capture this degree of existing within a routing instance. We first show that such diversity, we leverage the notion of policy groups discussed complexity results from the need to install route filters in- in Sec 2.1. side the routing instance, in order to implement the differ- Policy groups: Formally, let Z = {Z1,Z2, ...} denote the ent reachability requirements of different subnets. We then set of policy groups in a network. A policy group Zi ∈ present models to quantify the complexity associated with Z is a set of subnets that (i) can reach each other, and (ii) such route filters. In doing so, our models determine the are subject to the same reachability treatment toward other route filter placement and the filter rules. subnets (e.g., if a subnet sa ∈ Zi can reach another subnet

5 sb ∈ Zj , then all subnets in Zi must be able to reach sb as Determine filters needed for one policy group: Using the well). Clearly, policy groups divide the set of all subnets, per-instance routing graph, we determine the route filters and each subnet belongs to one and only one policy group. needed for implementing the reachability of a policy group The set of policy groups of a given network can be easily vi ∈ VZ toward other subnets. First, consider every policy derived from the reachability matrix MR. In the example in group vj ∈ VZ . If vj contains one or more subnets that vi Fig. 4a, S1 and S2 forms a policy group, while S3 and S4 can not reach, then a route filter must be placed on every each constitute a separate policy group. possible path between vi and vj on the per-instance routing By definition, there is no need for filtering within a pol- graph, to filter out routing updates corresponding to those icy group. Thus if a routing instance contains only a single subnets before they reach any gateway router of vi. Sim- policy group, the intra-instance complexity is zero. On the ilarly, consider every external network vk ∈ VX . If there other hand, if a routing instance contains subnets of multiple exist one or more subnets in vk that vi cannot reach, a route policy groups, route filters must be installed among them to filter must be placed on every possible path between vi and implement their different reachability constraints, and thus vk to filter routing updates corresponding to those subnets as incur complexity. well. Upper and lower bounds on the number of filters: In both 4.2 Modeling the complexity cases described above, the upper bound on the number of Intuitively, the degree of complexity of a given routing in- route filters needed for policy group vi is the total number stance Ia depends on two factors: of paths between vi and vj (vk), summed over all vj and vk • The number of route filters installed inside Ia, as each in- for which filtering is needed. The upper bound can always stallation of a filter creates a reference link to the name of be achieved by placing the filters on the on gateway routers that filter (e.g., line 5 of router 1 in Fig 3). of vi. The lower bound is the number of links in the small- • The complexity associated with each filter, which is mea- est edge-cut set between vi and vj (vk), summed over all sured by the number of rules in each filter, as each rule cre- vj and vk for which filtering is needed. However, the lower ates a reference link to a prefix address (e.g., lines 7-8 of bound may not always be achievable, as some links may be router 1 in Fig 3). included in the smallest edge-cut sets between multiple pairs Below we model the two factors separately. of policy groups. For example, in Fig. 4b routing updates of Z3 must be filtered before they reach Z1, as Z1 is not al- 4.2.1 Estimating number of filters lowed to reach Z3. While one smallest edge-cut set between In order to estimate the number of route filters needed to be Z1 and Z3 is the link R1 − R3, we cannot place the filter on that link, as doing so would wrongfully prevent Z from installed inside a given routing instance Ia, we first introduce 2 getting those routing updates. an undirected graph Ga(VR, VZ , VX , VB, E) , called the per- instance routing graph of Ia. We then show how we use this The lower bound can be achieved for a special type of star graph to do the estimation for different network topologies. topology, which we believe is typical in many enterprise net- Per-instance routing graph: The purposeof the per-instance works. In this type of topology, any path between a pair of routing graph is to model how policy groupsare inter-connected. policy groups, or between a policygroup and an external net- There are fourtypes of nodes in the graphfor a given routing work, always goes through the core router. This ensures that design: VR, VZ , VX and VB. VR denotes the set of routers the paths between the core tier and differentpolicy groups do that participate in this routing instance. VZ denotes the set not share any common router. Given this special topology, of policy groups that are placed inside this routing instance. it may be shown that (i) the core-tier will have the complete VX denotes networks external to this routing instance (i.e., set of routes, and (ii) it is sufficient to place the route fil- other routing instances in the same AS and external ASes as ters between the core tier and each policy group. Hence it is well), whose routes are injected into this routing instance by now feasible to place the filters on the smallest edge-cut set one or more border routers. Finally, VB denotes the set of between the core tier and each policy group. border routers of this routing instance. 4.2.2 Estimating number of rules in each filter E denotes the set of edges. First, there is an edge between two nodes vi, vj ∈ VR if the two routers are physically con- Consider using a route filter to implement a policy group nected, and the corresponding routing processes running on vi’s reachability constraint toward another policy group vj . them are adjacent, i.e., can exchange routing updates [20]. The number of rules in this filter depends on the number of Second, there is an edge between vi ∈ VZ and vj ∈ VR if routes to be blocked from vj to vi, as one route translates to one or more subnets in policy group vi connect to the rout- one filter rule (see Fig. 3 for an illustration). ing process running on vj . Finally, there is an edge between For example, as we have discussed above, a route filter vi ∈ VX and vj ∈ VB , if the border router vj injects the must be installed between Z1 and Z3 in the toy network routes of the external network vi. (Fig. 4b), to prevent the routes of S1 and S2 from being For example, the per-instance routing graph of I1 in Fig. 4a advertised to S4. The number of rules in this filter will be is shown in Fig. 4b. two, as there are two prefixes to be blocked. (Note that the

6 I1 (OSPF 10) I2 (EIGRP 20) S1 S2 S3 I1 (OSPF 10) I2 (EIGRP 20) S1 S2 S3 S1 S1 YYN S2 Y Y Y S1 S1 YYN R1 S3 S2 Y Y Y S3 N Y Y R1 S3 S2 R3 S3 N Y Y R2 S2 R4 R3 R2 Figure 5: A toy network with two routing instances. (a) The network design using route redistribution.

Router 4 number of rules may be reduced, if several prefixes can be 1. router ospf 10 2. redistribute eigrp 20 aggregatedinto a larger prefix. For simplicity we do not con- 3. ! sider such route aggregation in this work.) 4. router eigrp 20 5. redistribute ospf 10 route-map OSPF-TO-EIGRP 6. ! 5 Modeling Inter-Instance Complexity 7. route-map OSPF-TO-EIGRP permit 10 8. match ip address 1 This section presents a framework for estimating the inter- 9. ! instance complexity. We show that this complexity results 10. access-list 1 permit S2 from the use of connecting primitives. We then present mod- (b) Configuration snippet of the border router R4 els for estimating the complexity for the three typical con- Figure 6: Design using route redistribution for the network necting primitives described in Sec. 2.2: route redistribution, shown in Fig. 5. static and default routes, and BGP. 5.1 Source of inter-instance complexity Router R4 is the border router and is configured to redis- The inter-instance complexity comes from the need for con- tribute routes between I1 and I2. necting primitives to connect multiple routing instances. Con- Fig. 6b shows the relevant configuration snippet of R3 in sider the toy network shown in Fig. 5 as an example. There Cisco IOS syntax, with referential links highlighted in ital- are two routing instances: I1 running OSPF with process ID ics. Line 1 and 4 create two routing processes, one partici- 10, and I2 running EIGRP with process ID 20. I1 contains pate in each routinginstance. Line 2 and 5 redistribute routes subnets S1 and S2, and I2 contains S3. The reachability pol- from I1 to I2 and from I2 to I1 respectively. icy specifies that S1 and S2, as well as S2 and S3 can reach each other, but S1 and S3 can not. Given the network as We note that by default, route redistribution will redis- such, I1 and I2 cannot exchange any route, and thus cannot tribute all the activeroutes from one instance to the other [17]. For example, in Fig. 6a, R4 will redistribute routes of both communicate. To change this behavior and implement the reachability between S1 and S3, one or more border routers S1 and S2 to I2. This enables S3 to reach both S1 and S2, must be deployed to physically connect the two routing in- which does not conform to the reachability policy as shown. To change the default behavior, a route filter (in the form of stances, and in addition, a connecting primitive must be con- figured on each border router to enable route exchange. a route-map) must be used in conjunction with route redis- An importantfactor that impacts the degree of inter-instance tribution, as shown in line 5 in Fig. 6b. Such a filter permits complexity is the resiliency requirement (Sec. 3.1), which a subset of routes specified by the filtering rules (line 8 and specifies the number of border routers (Sec. 3.2) each rout- 10), and blocks the rest routes. ing instance should have. While having more border routers Modeling complexity: Consider route redistribution from improves the resiliency of the design, it also introduces po- Ii to Ij . Route redistribution in the other direction may be tential anomalies (e.g., routing loops) and complicates the modeled similarly and separately. As shown above, the con- configuration, as we will show in the next section. figuration may include two components: (i) configuration of In this section we focus on the basic scenario with a sin- the route redistribution itself, and (ii) configuration of the gle border router for each routing instance (i.e., minimum route filter, which is required if only a subset of Ij ’s routes resiliency). We discuss the case with multiple border routers should be redistributed. Let Krr denote the complexity of in the next section. configuring the route redistribution itself. Let the function f(x) denote the complexity of configuring and installing a 5.2 Route redistribution route filter with x rules (i.e., the filter allows x routes). We The first connecting primitive we consider is route redistri- note that f(x) includes (i) the complexity of configuring the bution, which dynamically sends routes from one routing in- filtering rules, which is linear to the number of rules, and stance to another. Using route redistribution to connect two (ii) the complexity of installing the filter by referring to its routing instances requires having a common border router name, which is a constant factor. In addition, we let h(i, j) that runs routing processes in both routing instances. The be the following binary function that denotes whether a filter border router then is configured to redistribute routes from is needed: (Recall that a filter is not needed if all the routes one routing instance to the other, and vice versa. (Note Ii has, i.e. Wi, can be redistributed into Ij .) that route redistribution must be separately configured for h(i, j)=0, if MX(i, j)= W ; (2) each direction.) For example, Fig. 6a illustrates the design i using route redistribution for the network shown in Fig. 5. h(i, j)=1, otherwise. (3)

7 I1 (OSPF 10) I2 (EIGRP 20) S1 S2 S3 Router 4 S1 S1 YYN 1. router ospf 10 S2 Y Y Y R1 S3 S3 N Y Y 2. redistribute bgp 64501 S2 R4 R5 R3 R2 3. ! 4. router bgp 64501 (a) The network design using either static routes or BGP. 5. neighbor R5 remote-as 64502 6. neighbor R5 distribute-list 1 out 7. redistribute ospf 10 Router 4 8. ! 1. router ospf 10 9. access-list 1 permit S2 2. redistribute static Router 5 3. ! 10. router eigrp 20 4. ip route S3 R5 11. redistribute bgp 64502 Router 5 12. ! 5. router eigrp 20 13. router bgp 64502 6. redistribute static 14. neighbor R4 remote-as 64501 7. ! 15. redistribute eigrp 20 8. ip route S2 R4 16. !

(b) Configuration snippets of the border routers using static Figure 8: Configuration snippets of the border routers using routes. BGP, for the network shown in Fig. 7a Figure 7: Design using static routes for the network shown in Fig. 5. Default routes: A default route is a special case of static routes, which injects a default gateway to the router it is The overall complexity denoted by Crr(i, j) can be calcu- configured on. A default route has a constant complexity lated as follows: (denoted as Kdr). For example, in Cisco IOS syntax the command to configure a default route is “ip route 0.0.0.0 Crr(i, j)= Krr + f(MX(i, j)) ∗ h(i, j) (4) 0.0.0.0 next-hop-IP ”. This is essentially the same command for configuring static routes, except that the destination pre- 5.3 Static routes fix takes the special form “0.0.0.0 0.0.0.0”, which will match Another way to connect the two routing instances in Fig. 5 is any IP address. Clearly the complexity of this command is to use static routes, which can be viewed as manually entered one, as it creates a single referential link to the address of the routing table entries. This design is shown in Fig. 7a. Each next-hop router. routing instance now must have its own border router (R4 5.4 BGP and R5) that participates in only that routing instance. Static routes are configuredon the borderrouters and point to desti- A third connecting primitive is BGP, which is a dynamic nation subnets in the other routing instance. One static route routing protocol that allows routes to be exchanged among is needed for every destination subnet. Further, the static routing instances. BGP typically requires each routing in- routes are redistributed into the respective routing instance stance to have its own border router. The design using BGP so that internal routers in the routing instance also have those for the same example network is shown in Fig. 7a. Again R4 routes. and R5 are the border routers for I1 and I2 respectively. In Fig. 7b shows the relevant configuration snippets of the addition to running the respective IGP routing process, R4 two border routers, with referential links highlighted in ital- and R5 each also runs a separate BGP routing process. A ics. On R4, a static route is configured and installed in line BGP peering relationship is established between R4 and R5, 4. The static route points to S3 as the destination, and speci- so that R4 can advertise S2 to R5, and R5 can advertise S3 fies R5 as the next-hop to reach the destination. Having this to R4. R4 and R5 also redistribute the learned BGP routes to static route installed, R4 now has a route to S3. Further, line their respective routing instance, so that other routers in the 2 redistributes any static route configured on the router into routing instance have those routes too. I1, so that other routers of I1 (i.e., R1 and R2) also have a Fig. 8 shows the relevant configuration snippets of R4 and route to reach S3. Similarly, a static route to S2 is configured R5. Configuring R4 involves: (i) starting a BGP routing pro- on R5 (line 8) and redistributed (line 6) to I2. cess (line 4); (ii) redistributing routes from the IGP into the Modeling complexity: Consider using static routes to allow BGP process (line 7); (iii) establishing a BGP peering ses- Ij to reach a set of subnets MX(i, j) in Ii. Let |MX(i, j)| sion with the neighboring border router (R5), and exchang- denote the size of MX(i, j). Since one static route is needed ing routes with it (line 5); (iv) installing an optional route for each route in MX(i, j), there will be |MX(i, j)| static filter to restrict the routes to be advertised (line 6); and (v) routes to configure. Let Ksr denote the complexity of con- redistributing the learned BGP routes into IGP (line 2). Sim- figuring a single static route. The total complexity denoted ilar configuration is done on R5 too. We wish to note two by Csr(i, j) can be calculated as follows: things here. First, the BGP process does not have any route by default, and hence routes must be explicitly redistributed M Csr(i, j)= | X(i, j)|∗ Ksr (5) from the IGP to the BGP, i.e., the step (ii) above. Second,

8 the complexity of each of these connecting primitives. I1 (RIP) R4 I2 (OSPF) S1 R1 S3 6.1 Ensuring safety with route redistribution S2 R3 R2 R5 Consider a design scenario where route redistribution is con- Figure 9: Both border routers R4 and R5 are performing figured on multiple border routers to redistribute routes from mutual route redistribution between I1 and I2. Assume full Ii to Ij . The complexity of this design depends on what con- reachability among all subnets. necting primitive is used to send routes in the reverse direc- tion (i.e., from Ij to Ii), as we discuss below. BGP advertises all its routes to neighbors by default. If this On the one hand, if no connecting primitive or a differ- is not desired, a route filter must be used to restrict routes to ent connecting primitive than route redistribution is used in be advertised, i.e. the step (iv) above. the reverse direction, the complexity Crr is simply the single Modeling complexity: Consider that Ii advertises a set of border-router complexity (Sec. 5.2) multiplied by the num- routes to Ij using BGP. The complexity of configuring BGP ber of border routers, i.e., on Ii’s border router consists of three components: (i) the complexity of configuring the BGP session itself, includ- Crr(i, j) = (Krr + f(Mx(i, j)) ∗ h(i, j)) ∗ |MB(i, j)| ing configuring the BGP process and the peering relation- (7) ship with a neighbor; (ii) the complexity of configuring two- way route redistribution between the IGP and the BGP pro- Recall that MB(i, j) denotes the set of border routers that cesses; and (iii) the complexity of configuring a route filter, Ii uses to reach Ij , which is an input to our framework MB if it is needed (i.e., only a subset of Ii’s routes can be adver- (Sec. 3.2). | (i, j)| denotes the size of this set, i.e., the number of border routers. tised). Let Kbgp denote the complexity of configuring the BGP protocol itself. Let f(x) and h(i, j) be the same func- On the other hand, if route redistribution is also used in tions as defined in Sec. 5.2. The total complexity denoted by the reverse direction, then a potential anomaly called route feedback may occur. Route feedback happens when a route Cbgp(i, j) can be calculated as follows: is first redistributed from Ii to Ij by one border router, but M Cbgp(i, j)= Kbgp +2 ∗ Krr + f( X(i, j)) ∗ h(i, j) then is redistributed back from Ij to Ii by another border (6) router. For example, in the network in Fig. 9, S1 may be first redistributed from I1 (RIP) to I2 (OSPF) by router R4. So 6 Complexity With Multiple Border Routers router R5 learns the route from both RIP and OSPF. If R5 prefers the OSPF-learned route, it will redistribute the route We now consider designs where a routing instance uses mul- back to RIP. Route feedback can lead to several problems tiple border routers to connect to another routing instance. such as routing loops and route oscillations [17]. Clearly An example of such a design is shown in Fig. 9, where both route feedback can happen only when mutual route redistri- R4 and R5 are configured to perform two-way route redis- bution is conducted by multiple border routers between two tribution between I1 and I2. The main benefit of using mul- routing instances. tiple border routers is increased resiliency, i.e., even if one border router in Fig. 9 fails, I1 and I2 can still communicate As a common conservative solution to this issue, a route through the other one. On the other hand, using multiple filter is used in conjunction with route redistribution to pre- border routers can cause anomalies such as routing loops. vent any route from re-entering a routing instance where it To prevent the anomalies, additional configuration will be originally came. In the above example, a route filter should required, which may introduce more referential links and in- be installed on R4 and R5 to allow only the route S3 to enter crease complexity. I1, and preventroutesof S1 and S2 from re-enteringI1. Note that such a filter may be already in place to implementreach- In this section, we model the additional complexity re- ability as described in Sec. 5.2 (i.e., to only allow a subset sulting from both the safety and resiliency requirements with of routes of I to be sent to I , and block all other routes). multiple border routers: j i In such case, there is no additional complexity introduced. • Safety: the routing must function correctly when all the Only in the case where the filter is not needed otherwise (i.e. border routers are alive and running, e.g., no routing loop MX(j, i)= W ), a route filter needs to be configuredfor the will occur; j sole purpose of preventing route feedback. To summarize, in • Resiliency: when one or more border router and/or link is the mutual route redistribution case, the total inter-instance down, the routing must be able to adapt and re-route traffic complexity of using route redistribution to send routes from though live routers and/or links. I to I is: We examined all three connecting primitives and found i j that (i) for route redistribution, additional mechanisms are Crr(i, j) = (Krr + f(Mx(i, j))) ∗ |MB(i, j)| (8) required to ensure safety; (ii) for static routes, additional mechanisms are required to ensure resiliency; and (iii) for The complexity on the reverse direction can be similarly BGP, no additional mechanism is needed. Below we model modeled.

9 I1 (OSPF 10) I2 (EIGRP 20) I1 (OSPF 10) I2 (EIGRP 20) S1 S1 R1 R4 R6 S3 R1 R4 R6 S3 S2 R3 S2 R3 R2 R5 R7 R2 R5 R7

Figure 10: Static routes are configured on all border routers Figure 11: BGP is configured on all border routers R4 - R7. R4 - R7. Assuming full reachability among all subnets. Assuming full reachability among all subnets.

6.2 Ensuring resiliency with static routes to each static route), multiplied by the total number of arcs Consider a design scenario where a routing instance Ii uses from Ii to Ij (denoted by |MA(i, j)|). static routes to reach a set of destination subnets in I , as j 6.3 The casewith BGP is the case for routing instances I1 and I2 in the example network in Fig. 10. On each border router of Ii (e.g., R4 Consider a design scenario where BGP is used to enable two in Fig. 10), and for each destination subnet in Ij (e.g., S3), routing instances Ii and Ij to exchange routes. An example multiple static routes may be defined, each using a different of such design is shown in Fig. 11. Each border router runs border router of Ij as the next-hop. For example, two static eBGP peering sessions with one or more border routers of routes may be configured on R4 to reach S3, one using R6 the other routing instance, and runs iBGP peering sessions as the next-hop, and the other using R7. We assume that with each border router of the same routing instance. For we are also given as input an arc matrix MA, where each example, R4 in Fig. 11 runs eBGP peering sessions with R6 cell MA(i, j) specifies the set of arcs from the set of border and R7, and an iBGP peering session with R5. routers in Ii to the set of border routers in Ij . An “arc” We assume thatwe arealso givenas inputan eBGP-peering M is said to exist from one border router Ra ∈ B(i, j) to matrix MP, where each cell MP(i, j) specifies the set of MB another border router Rb ∈ (j, i), if there exists a static eBGP peering sessions between border routers of Ii and Ij . route on Ra that uses RB as the next hop. For the example network shown in Fig. 11, MP(1, 2) is 4. One limitation with static routes is that they may not be In addition, we assume that each border router runs an iBGP able to automatically detect the failure of the next-hop router session with every other border router in the same routingin- or the link in between, and will continueto try to route traffic stance, which is required for iBGP to work correctly. Hence to the bad path, even when other valid paths exist. This will each border router of Ii runs (|MB(i, j)|−1) iBGP sessions. result in packets being dropped. For example, In Fig. 10, The complexity of configuring Ii’s border routers consists when there is no failure, R4 will load balance the two static of three parts: (i) the complexity of configuring the eBGP routes and use both R6 and R7 to route traffic to I2. R5 will sessions with border routers of Ij , which includes configur- do the same thing. However, if R6 fails, R4 and R5 will ing route filters if needed to restrict routes to be advertised; not be able to detect the failure or cancel the corresponding (ii) the complexity of configuring the iBGP sessions among static route that uses R6 as the next-hop. Instead, they will border routers of Ii; and (iii) the complexity of configuring continue to try to route half of the traffic to R6, resulting in the route redistribution between the BGP process and the those packets being dropped. IGP process. Hence the total complexity may be calculated A common solution to this problem is using object track- as follows: ing [10] along with each static route. In doing so, each static M M route involves referring to an object tracking module. At a Cbgp(i, j) = (Kbgp + f( X(i, j)) ∗ h(i, j)) ∗ | P(i, j)|+ high level, object tracking will periodically ping the desti- K ∗ |MB(i, j)|∗ (|MB(i, j)|− 1)+ nation subnet of the static route, using the same next-hop bgp router as specified in the static route. When a failure occurs 2 ∗ Krr ∗ |MB(i, j)| (10) and the destination is no longer reachable via the particular next-hop, the static route will be removed from the RIB at 7 Evaluation that point. In this section, we evaluate our framework using configu- Let Kobj denote the complexity of installing object track- ration files of a campus network of a large U.S. university ing to one static route. The total complexity of using static with tens of thousands of users. Our data-set includes mul- routes to enable Ij to reach Ii can be modeled as follows, tiple snapshots of the configuration files of all switches and assuming each arc contains static routes to reach all subnets routers from 2009 to 2011. It also includes multiple snap- M in X(i, j): shots of the complete layer-two topology data, each col- M M lected using Cisco CDP at the same time each configura- Csr(i, j)= | A(i, j)| ∗ | x(i, j)|∗ (Ksr + Kobj) (9) tion snapshot was collected. The network has more than That is, the total complexity is the single arc complexity 100 routers and more than 1000 switches, all of which are (which includes both the complexity of configuringthe set of Cisco devices. It also has tens of thousands of user hosts, static routes, and the complexity of installing object tracking and around 700 subnets, most of which are /24.

10 Krr Ksr Kdr Kbgp Kobj f(x) EIGRP OSPF GRID INT 1 2 1 2 1 |x| +2 EIGRP - all H-1-1 D-1, H-1-1 OSPF all - - - Table 2: Realizing framework parameters GRID all - - - DATA RSRCH GRID INT INT all - - - X DATA - H-1 × Table 4: Each cell (row, column) shows the set of routes X X X RSRCH - that routing instance row should advertise to routing instance GRID × H-1-1 - × column. “All” means that row should advertise all its routes INT D-1 H-1-1 × - (both internal and external ones) to column. Table 3: Each cell (row, column) shows whether the policy EIGRP OSPF GRID INT group column can be reached by the policy group row. X/× EIGRP 7 1 6 30 means full/no reachability. D-1, H-1 and H-1-1 each denotes OSPF 1 0 - - a subset of the subnets in DATA and RSRCH, which can be GRID 1 0 - - reached by the corresponding row. H-1-1 is in turn a subset INT 2 - - - of H-1. Table 5: Estimated complexity for the original design. Each 7.1 Framework validation non-diagonal cell (row, column) shows the inter-instance We first evaluate the accuracy of our framework in estimat- complexity of advertising routes from row to column. The ing complexity. In doing so, we run the framework on one cells on the diagonal show the intra-instance complexity. “-” of the configuration snapshots, and compare the predicted indicates that the two instances are not directly connected. complexity numbers with the actual numbers obtained from measuring the configuration files directly. groups: DATA and RSRCH. R1 also directly connects to the other borders R2, R3 and R4. Note that there is no direct 7.1.1 Inferring model parameters and framework in- link between the two policy groups, or between either policy puts group and R2/R3/R4. We only need to calculating the model parameters for the From the reachabilitymatrix (Table3), it is easy to see that Cisco IOS platform, as this platform is exclusively used by intra-instance filtering is needed between the core router R1 the campus network. Obtaining these parameters is straight- and the DATA policy group as only a subset of routes from forward, as we just need to run the heuristics proposed in [5] R1 can be sent to DATA, and in particular, the routes learned on corresponding configuration blocks that relate to each pa- from GRID cannot be exposed to DATA. Using the model rameter, and count the number of reference links introduced. presented in Sec. 4, the route filter placement is determined The results are shown in Table 2. and shown in Fig. 12b. Route filtering is not needed between To infer the inputs as described in Sec. 3.2, we used a the core router R1 and RSRCH, because RSRCH can reach methodology that combines reverse-engineering the config- every other policy group. The predicted complexity is shown uration files and discussions with operators. We were able by the diagonal cells in Table 5. to identify the inputs as follows. Table 3 shows the policy Comparing with the actual configuration: We measured groups and the reachability policies among them. Fig. 12a the actual configuration complexity in the configurationfiles. shows the topology and what policy groups each routing in- The result in shown in the diagonal cells in Table 6. As pre- stance contains. In particular the campus network has two dicted, only the EIGRP routing instance incurs intra-instance routing instances denoted as EIGRP and OSPF. There are route filters, and the filter placement is exactly as predicted. also two policy groups in the network denoted as DATA and Furthermore, the measured complexity numbers also match RSRCH. In addition, two external AS-es (denoted as GRID the estimated value well. and INT) peer with this campus network. Each external AS 7.1.3 Estimating inter-instance complexity can be viewed both as a single policy group and as a sin- gle routing instance. Finally, the MX matrix, i.e., the set of Using the models presented in Sec. 5, we estimate the inter- routes exchanged between every pair of routing instances, is instance complexity, and show results in Table 5. shown in Table 4. Comparing with the actual configuration: We compare the predicted inter-instance complexity with the complex- 7.1.2 Estimating intra-instance complexity ity measured in the configuration files. The differences are First, according to our framework, only the EIGRP instance shown in Table 6. We see that the majority of the predicted will incur intra-instance route filters as it is the only instance numbers match well with the actual configuration. There is that contains multiple policy groups. a mismatch in the case of filtering routes between GRID and Second, the EIGRP instance employsthe typical star topol- EIGRP. The measured value is greater than the prediction, ogy (Sec. 4.2.1), as shown in Fig. 12b. The border router R1 which makes sense as the prediction is the minimum neces- also serves as the core router and connects the two policy sary complexity. The actual configuration may incur higher

11 INT ( INT ) INT ( INT ) R3 R4 R6 R7 R6 R7

BGP BGP BGP BGP DATA RSRCH R3 R4 R2 R3 R4 GRID BGP R5 R2 (GRID ) EIGRP ( DATA, RSRCH ) EIGRP ( DATA ) R1 R1 redistribution EIGRP static routes static routes R1 default route default route OSPF ( RSRCH ) BGP R2 R9 GRID R5 (GRID ) OSPF ( RSRCH ) (a) Instance-level topology of the original de- (b) Detailed topology of EIGRP in the (c) Instance-level topology of the new design. sign. original design. Figure 12: The original and new routing designs.

EIGRP OSPF GRID INT compare the new routing design with the original one. We EIGRP ǫ =0 ǫ =0 ǫ = −6 ǫ =0 first use our framework to analyze the change in complexity OSPF ǫ =0 ǫ =0 - - due to the redesign. We then consider whether alternative GRID ǫ = −3 ǫ =0 - - designs could have met the same resiliency objectives but INT ǫ =0 - - - with lower complexity. Table 6: Difference between complexity estimated using our 7.2.1 Impact of redesign on complexity models and the actual complexity measured from the config- Fig. 12c illustrates the new instance-level graph after the uration files for the original design. network redesign was completed. The primary purpose of the redesign was to increase resiliency. In particular, the EIGRP OSPF GRID INT number of border routers connecting the OSPF instance to EIGRP δ = −7 δ =7 δ = −6 δ =0 EIGRP was increased to two. In addition, two other changes OSPF δ = 29 δ =0 δ =6 - were made: (i) the connecting primitive between EIGRP and GRID δ = −1 δ =1 - - OSPF was changed from route redistribution to static routes INT δ =0 - - - (configured on the EIGRP side) and default routes (config- Table 7: Increase in the intra- and inter-instance complexity ured on the OSPF side); and (ii) the subnets of the policy after the redesign. group RSRCH that were in the EIGRP instance were moved to OSPF. As a result, in the new design, EIGRP only contains complexity, for example, due to redundant configurations or subnets of the policy group DATA, while OSPF contains all suboptimal configurations. subnets of the policy group RSRCH. Finally, we note that the In particular, the outgoing routes from EIGRP to GRID policy groups and the reachability matrix were unchanged are subject to filtering as only a subset of EIGRP routes can after the redesign. be sent to GRID. We note that the filtering may be config- Table 7 presents the change in complexity estimated by ured either at the redistribution point (i.e. permitting only our framework. Overall, the total complexity in the new de- the subset of routes to enter BGP), or within the BGP ses- sign increased. This is in part due to the fact that the re- sion (i.e. permitting only the subset of routes to be adver- silience of the new design also increased, i.e., it used two tised to GRID). However, in the actual configuration, the border routers for the OSPF routing instance, compared to exact same filtering is implemented at both places. This is one in the old design. We note that the new designeliminated redundant configuration, and results in unnecessary increase the intra-instance complexity in the EIGRP routing instance, in the complexity. Further, GRID can advertise all its routes as now EIGRP only contained a single policy group. On the to EIGRP, so there is no route filter needed. However, in other hand, the inter-instance complexity between EIGRP the actual configuration, an unnecessary filter is configured, and OSPF increased in the new design, caused by the need which simply allows all routes to pass. As a result, three to implement the different reachability requirements for the extra reference links were created. two policy groups RSRCH and DATA. Overall, these results confirm that our framework can ac- 7.2.2 Could alternative designs lower complexity? curately estimate the complexity of a given routing design. In the previous section, we noted that while the primary goal 7.2 Case study of a routing design change of the redesign was to improve resiliency, operators made The campus network experienced a major design change re- two additional changes that were not strictly necessary to cently. The change was primarily motivated by the need to achieve this goal: (i) changing the connecting primitive be- increase the resiliency of the original design. Thus as the tween OSPF and EIGRP from redistribution to static/default second part of the evaluation, we apply our framework to routes; and (ii) moving all subnets of the RSRCH policy

12 static route redistribution BGP EIGRP ( DATA , RSRCH ) EIGRP ( DATA ) default route 38 20 25

R1 static route static route redistribution 38 20 25 redistribution R1 R2 redistribution BGP 43 25 26 default routeR2 R9 default route OSPF ( RSRCH ) OSPF ( RSRCH ) Table 8: Complexity associated with different choices of Hypothetical design 1 (HD-1) Hypothetical design 2 (HD-2) connecting primitive between EIGRP and OSPF. Each cell (row, column) shows the complexity of the design that uses Figure 13: The two hypothetical designs. the row(column) to send routes from EIGRP (OSPF) to OSPF (EIGRP). intra-instance complexity inter-instance complexity between EIGRP and OSPF 250 % total complexity used to connect OSPF and EIGRP.We foundthat using route 200 % redistribution (i.e.HD-2) lowers the complexity compared to

150 % using static routes (i.e., the actual new design). This indi-

of old design cates that by changing the connecting primitive from redis- 100 % tribution to static/default routes during the redesign process, 50 %

Complexity relative to the total complexity the operators introduced unnecessary design complexity.

0 % Given these insights, we next want to find out whether new HD-1 HD-2 mutual route redistribution is the best connecting primitive Figure 14: Comparison of complexity of different designs. to use to connect EIGRP and OSPF, and if alternative prim- itives could further lower complexity. For this purpose, we group to OSPF. We hypothesized these changes may have enumerate all possible connecting primitives, and apply our been made to lower complexity. To isolate the impact of framework to estimate the complexity associated with each each of these changes, we considered two hypothetical de- alternative design choice. The results are shown in Table 8. signs termed HD-1 and HD-2, as shown in Fig. 13. Both de- Note that it is not feasible to use static routes (default routes) signs use two border routers for OSPF, to achieve the same to send routes from EIGRP (OSPF) to OSPF (EIGRP), so resiliency requirement as the new design. HD-1 uses static the corresponding column and row as omitted. The table and default routes to connect EIGRP and OSPF, and rep- shows that mutual route redistribution indeed achieves the resents a design where only the first of the two additional minimum complexity. A similar complexity could have also changes above were made. HD-2 involves a rearrangement been obtained through a design that uses a combination of of policy groups and represents a design where only the sec- default routes and route redistribution. We also see that dif- ond of the two additional changes above were made. Route ferent choices of connecting primitive may lead to signifi- redistribution is used to connect the instances. cant difference in resulting complexity. We apply our framework to estimate the complexity for In summary, these results show that (i) the design change both hypothetical designs. The results are shown in Fig 14. of movingsubnets of the policy group RSRCH from EIGRP For ease of comparison, we normalized all bars to the to- to OSPF greatly reduced both intra- and inter-instance com- tal complexity of the original campus design. We see that plexity; and (ii) the change of connecting primitive actually while HD-1 is a worse alternative design as its total complex- made the network more complex and thus should have been ity (third bar) increases compared to the actual new design, avoided; and (iii) different design choices may result in sig- HD-2 is a better alternative as its total complexity decreases nificantly different complexity. Overall, this case study high- compared to the actual new design. lights the power of our framework in systematically compar- We next seek to better understand why HD-1 has higher ing multiple design alternatives and in guiding operators to- complexity than the actual new design. The main differ- wards approaches that lower complexity while meeting the ence between the two designs is whether the policy group same design objectives. RSRCH is placed entirely in the OSPF routing instance 7.3 Operator Interview (new design), or split across both OSPF and EIGRP (HD- 1). We observe that by placing RSRCH entirely in OSPF, We discussed the above results with the operators of the the address space of OSPF is more unified, which allows campus network, and they were able to confirm many of our better aggregation of its routes. This results in a reductionof observations. In particular, they confirmed that moving the the size of MX(EIGRP,OSPF ) from 9 to 3, which trans- RSRCH subnets from EIGRP to OSPF significantly reduced lates to fewer static routes needed, and thus results in less the management complexity. In fact, the motivation of that inter-instance complexity (second bar in Fig. 14). In addi- change was to make the RSRCH network more unified and tion, HD-1 incurs significant intra-EIGRP complexity (first simplify the network design. In addition, the operators also bar), while the actual new design eliminates that complexity. acknowledged that our hypothetical design 2 (Fig. 13) that Next, we compare the actual new design and HD-2. The uses route redistribution instead of static routes could indeed main difference between the two is the connecting primitive be a less complex design. The primary reason they decided

13 to use static routes in the new design was because this partic- the first step has been accomplished. In future, it should ular operator team consisted of people with varyingexpertise be beneficial to consider multiple design stages and steps and skill levels (including senior operators, part-time student in one framework and explore ways to improve routing de- workers, and new hires), all of whom could potentially alter sign further through joint optimization of all pertinent design configuration files. While configuring static routes did not choices. require extensive prior knowledge, configuring route redis- Complexity-aware top-down design: The complexity mod- tribution required greater knowledge and expertise, partic- els presented in this paper pave the way for complexity- ularly given the potential for routing loops. The operators aware top-down routing design. Such top-down design takes indicated however that they would prefer route redistribu- as input the high-level design objectives and constraints, and tion if only a small number of senior operators managed the seeks to minimize design complexity while meeting other network. Overall, these results confirm that our framework design requirements. In doing so, our complexity models provides useful guidance to operators. An open question for can beused to guidethesearch of thedesign spaceto system- future work is whether current complexity metrics must be atically determine (i) how policy groups should be grouped refined to take operator skill levels into account. into routing instances; (ii) optimum placement of route fil- ters; and (iii) what primitives should be used to connect each 8 Discussion and open issues pair of routing instances. We defer the development of such Incorporating other design objectives and constraints: In a top-down design framework to future work. putting together a routing design, operators must reconcilea Emerging architectures and configuration languages: In variety of objectives and constraints such as performance, recent years, researchers have started investigating new net- complexity, hardware constraints etc. This paper focuses on work architectures based on logically centralized controllers the design complexity, given that it is very important, is dif- (e.g., software defined networking [2]), and declarative con- ficult to quantify, and has received limited attention from the figuration languages (e.g., Frenetic [11]). These approaches community. In future, it would be interesting to also factor in have the potential to simplify network management by shift- other important requirements. For example, hardware con- ing complexity away from the configuration of individual straint may restrict the number of route filters that a router devices to programmingof the centralized controllers. While can support. Such restriction may in turn impact both intra- these approacheshave much potential, hard problems remain and inter-instance route filter placements. We believe our such as the need to update network devices in a consistent framework can be easily enhanced to systematically deter- fashion [22], and building appropriate coordination mecha- mine the best filter placements, so that the hardware con- nisms across multiple controllers. Further exploration of the straint is honored, while the total design complexity is min- opportunities and challenges of utilizing these new architec- imized. In addition, it may be interesting to consider other tures to simplify network design complexity is an important design objectives such as performance (e.g., measured as av- area of future work. erage hop counts between any two subnets), and costs (re- stricting the number and hardware capacity of devices that 9 Related Work can be used). While some of these objectives and constraints In recent years, there has been much interest in both in- may not be critical in a typical over-provisioned enterprise dustry [1], and academia [5] in developing formal metrics environment, they are nevertheless worthwhile to consider. to capture network configuration complexity. We have dis- Joint optimization of multiple design tasks: This work cussed in detail how our work differs from [5] in Sec. 1. builds upon a “divide and conquer” network design strat- Similarly, our work also differs from other research [7,15] egy that is commonly practiced by the operational commu- that measures the configuration complexity in longitudinal nity [23]. In particular, such a design processconsists of four configuration data-sets in a bottom-up fashion. There is a distinct stages: (i) wiring and physical topology design; (ii) considerable amount of prior work on modeling individual VLAN design and IP address allocation; (iii) routing design; routing protocols, particularly BGP [3,8, 12,14], and also and (iv) deployment of services such as VoIP and IPsec. We OSPF [21], to ensure correct, safe, and efficient behaviors further break down the task of routing design into two se- from these protocols. There is also recent progress on safe quential steps: (1) creating routing instances and determin- migration of IGP protocols [24] and on modeling the inter- ing the set of routes to be exchanged between each pair of action between multiple routing algorithms deployed in the these instances, and then (2) configuring policy groups and same network [4]. In contrast, our work analyzes how spe- the necessary glue logic. Step (1) is relatively straightfor- cific routing protocols and primitives should be combined to ward, typically influenced by factors such as the proximity meet a given set of design objectives, and the focus is on of routers (e.g., in the same building, city, etc.), administra- minimizing the complexity of the resulting design. Our no- tive boundaries (e.g., different network segments are man- tion of policy groups is similar to policy units introduced in aged by different operators), and equipment considerations [6], but has some differences in that (i) we require subnets (e.g., EIGRP is available only on Cisco routers). Therefore, within the same policy group to be full reachable to each this work focuses on the second step while assuming that other; and (ii) we restrict our definition to reachability re-

14 strictions on the routing plane since our focus is on routing 12 References design, (i.e., we do not consider data-plane mechanisms like packet filters, firewalls, etc.). Algorithms to extract policy units from low-level configuation files were introduced in [1] IRTF Network Complexity Research Group. [6]. In contrast, our focus is on estimating the number of http://irtf.org/ncrg. route filters and filter rules, and consequently the resulting [2] Open Networking Foundation. configuration complexity, when multiple policy groups are http://www.opennetworking.org. present in a routing instance. [3] C. Alaettinoglu, C. Villamizar, E. Gerich, D. Kessensand, D. Meyer, T. Bates, D. Karrenberg, 10 Conclusion and Future Work and M. Terpstra. Routing Policy Specification Language (RPSL). Internet Engineering Task Force, In this paper, we present a top-down approach to character- 1999. RFC 2622. izing the complexity of enterprise routing design given only [4] M. A. Alim and T. G. Griffin. On the interaction of key high-level design parameters, and in the absence of ac- multiple routing algorithms. In Proc. ACM CoNEXT, tual configuration files. Our overall modeling approach is to 2011. (i) formally abstract the routing specific operational objec- [5] T. Benson, A. Akella, and D. Maltz. Unraveling the tives which can help reason about whether and how a com- complexity of network management. In Proc. of bination of design primitives will meet the objectives; and USENIX NSDI, 2009. (ii) decompose routing design into its constituent primitives, [6] T. Benson, A. Akella, and D. A. Maltz. Mining and quantify the configuration complexity of individual de- policies from enterprise network configuration. In sign primitives using bottom-up complexity metrics [5]. We Proceedings of the 9th ACM SIGCOMM conference have validated and demonstrated the utility of our approach on Internet measurement conference, pages 136–142, using longitudinal configuration data of a large-scale cam- 2009. pus network. Estimates produced by our model accurately [7] T. Benson, A. Akella, and A. Shaikh. Demystifying match empirically measured configuration complexity met- configuration challenges and trade-offs in rics. Discrepancies when present were mainly due to redun- network-based isp services. In Proc. of ACM dant configuration lines introduced by network operators. SIGCOMM, 2011. Our models enable what-if analysis to help evaluate if al- [8] H. Boehm, A. Feldmann, O. Maennel, C. Reiser, and ternate routing design choices could lower complexity while R. Volk. Network-wide inter-domain routing policies: achieving the same objectives. Analysis of a major routing Design and realization. Apr. 2005. Draft. design change made by the operators indicates that while [9] M. Casado, M. J. Freedman, J. Pettit, J. Luo, some of their design changes were useful in lowering com- N. McKeown, and S. Shenker. Ethane: Take control of plexity, others in fact were counter-productive and increased the enterprise. In Proc. ACM SIGCOMM, 2007. complexity. Further, our models helped point out alternate [10] Cisco Systems Inc. Reliable static routing backup designs that could further lower complexity. using object tracking. http://www.cisco.com/ Overall, we have taken an important first step towards en- en/US/docs/ios/12_3/12_3x/12_3xe/ abling systematic top-down routing design with minimizing feature/guide/dbackupx.html. design complexity being an explicit objective. Future work [11] N. Foster, R. Harrison, M. J. Freedman, C. Monsanto, includes modeling a wider range of routing design objec- J. Rexford, A. Story, and D. Walker. Frenetic: a tives and primitives (such as selection logic), developing al- network programming language. In Proceedings of the gorithms for automatically producing complexity-optimized 16th ACM SIGPLAN international conference on routing designs in a top-down fashion, and using similar Functional programming, pages 279–291, 2011. models to capturing complexity of other enteprise design [12] J. Gottlieb, A. Greenberg, J. Rexford, and J. Wang. tasks. Automated provisioning of BGP customers. In IEEE 11 Acknowledgments Network Magazine, Dec. 2003. [13] A. Greenberg, G. Hjalmtysson, D. A. Maltz, This material is based upon work supported by the National A. Myers, J. Rexford, G. Xie, H. Yan, J. Zhan, and Science Foundation (NSF) Career Award No. 0953622, NSF H. Zhang. A clean slate 4D approach to network Grant CNS-0721574, and Cisco. Any opinions, findings, control and management. ACM Computer and conclusions or recommendations expressed in this ma- Communication Review, October 2005. terial are those of the author(s) and do not necessarily re- [14] T. G. Griffin and J. L. Sobrinho. Metarouting. In Proc. flect the views of NSF or Cisco. We thank Brad Devine for ACM SIGCOMM, 2005. his insights on Purdue’s network design. We thank Michael [15] H. Kim, T. Benson, A. Akella, and N. Feamster. The Behringer, Alexander Clemm, Ralph Droms and our shep- evolution of network configuration: A tale of two herd Vyas Sekar for feedback that greatly helped improve campuses. In Proc. of ACM IMC, 2011. the presentation of this paper. [16] F. Le, G. G. Xie, D. Pei, J. Wang, and H. Zhang.

15 Shedding light on the glue logic of the Internet routing architecture. In Proc. ACM SIGCOMM, 2008. [17] F. Le, G. G. Xie, and H. Zhang. Understanding route redistribution. In Proc. International Conference on Network Protocols, 2007. [18] F. Le, G. G. Xie, and H. Zhang. Instability free routing: Beyond one protocol instance. In Proc. ACM CoNEXT, 2008. [19] F. Le, G. G. Xie, and H. Zhang. Theory and new primitives for safely connecting routing instances. In Proc. ACM SIGCOMM, 2010. [20] D. Maltz, G. Xie, J. Zhan, H. Zhang, G. Hjalmtysson, and A. Greenberg. Routing design in operational networks: A look from the inside. In Proc. ACM SIGCOMM, 2004. [21] R. Rastogi, Y. Breitbart, M. Garofalakis, and A. Kumar. Optimal configuration of ospf aggregates. IEEE/ACM Transaction on Networking, 2003. [22] M. Reitblatt, N. Foster, J. Rexford, C. Schlesinger, and D. Walker. Abstractions for network update. In Proceedings of the ACM SIGCOMM, 2012. [23] E. Sung, X. Sun, S. Rao, G. G. Xie, and D. Maltz. Towards systematic design of enterprise networks. IEEE/ACM Trans. Networking, 19(3):695–708, June 2011. [24] L. Vanbever, S. Vissicchio, C. Pelsser, P. Francois, and O. Bonaventure. Seamless network-wide IGP migrations. In Proc. ACM SIGCOMM, 2011.

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