Sourcesonoff Tool

Total Page:16

File Type:pdf, Size:1020Kb

Sourcesonoff Tool How to generate realistic network traffic? Antoine VARET and Nicolas LARRIEU COMPSAC – Vasteras – July the 23rd, 2014 French Civil Aviation University (ENAC) TELECOM Laboratory COMPSAC'14 - N. Larrieu - 1 22 24/07/2014 Why do we need realistic traffic? • To evaluate performances of new network entities – By face them to generated traffic with characteristics as close as possible as the Internet traffic • Lack of adequate tools to generate data flows with “realistic behaviors” at the network or transport level COMPSAC'14 - N. Larrieu - 22-24/07/2014 2 Outline 1. State of the art of traffic generation tools 2. Principles of the SourcesOnOff tool 3. Validation of realism level for traffic generated by our tool COMPSAC'14 - N. Larrieu - 22-24/07/2014 3 Outline 1. State of the art of traffic generation tools 2. Principles of the SourcesOnOff tool 3. Validation of realism level for traffic generated by our tool COMPSAC'14 - N. Larrieu - 22-24/07/2014 4 Different tools for different purposes • Available traffic generators – Network simulators: NS-2 [5], OpNet [6] or OmNet++ [7] On Off sources built-in but inside the simulator – Traffic replay tools: Tcpreplay [8], Harpoon [9] Need first to acquire the traffic trace to replay Mostly packel-level tools, not flow-level tools Retransmit the sniffed packets in the same order, and separated with the same delays as these measured during the capture – Network throughput estimation tools: iperf [10], BWPing [11], Ttcp [12], NetPerf [13], NetPerfMeter [14], Ostinato [15] Interesting throughput statistics Single flow or multiple synchornized flows generation Development of our traffic generator, the SourcesOnOff tool! COMPSAC'14 - N. Larrieu - 22-24/07/2014 5 How to characterize an “Internet-like” traffic profile? • Internet cannot be solely characterized with a small set of parameters (e.g. some mathematical distributions and additional factors) • Not currently one unique mathematical modeling able to embrace the different characteristics and the complexity of the Internet traffic [1] • “Internet” can cover very different profiles, but some common properties can be highlighted: – High variability – Self-similarity COMPSAC'14 - N. Larrieu - 22-24/07/2014 6 Internet traffic characteristics • High variability is characterized by an infinite mathematical variance and means that sudden discontinuous changes can always occur – Some mathematical distributions like Pareto and Weibull are heavy-tailed (i.e. the tail of the distribution is not exponentially bounded) and thus can be used to generate sets of values with high variances and also high- variability [2, 3] • Self-similarity is defined by a long-range dependence characteristic, which means there are bursts of traffic any time over a wide range of time scales. – W. Willinger found in [4] a relation between self-similarity and high variability for Ethernet Local Area Network (LAN) throughputs – The author showed that using ON/OFF sources with heavy-tailed distributions causes the traffic streams to be highly variable and, consequently, the aggregation of these streams to be also self-similar and highly variable COMPSAC'14 - N. Larrieu - 22-24/07/2014 7 ON-OFF sources principles (1) COMPSAC'14 - N. Larrieu - 22-24/07/2014 8 ON-OFF sources principles (2) • Sources parameters (based on random distribution) – Doff distribution: departure time of any source is computed with the departure time (second) of the preceding source plus a random duration. The first source starts at the beginning of the process. – Don distribution: duration times of any source. We generate random values, not for time duration in seconds but for quantity of transmission in bytes (because of TCP congestion control mechanism) • Statistical sources generations – Don and Doff distributions follow statistical processes with heavy-tail characteristic (i.e. Weibull or Pareto laws) – Don and Doff distributions are statistical independent COMPSAC'14 - N. Larrieu - 22-24/07/2014 9 Outline 1. State of the art of traffic generation tools 2. Principles of the SourcesOnOff tool 3. Validation of realism level for traffic generated by our tool COMPSAC'14 - N. Larrieu - 22-24/07/2014 10.
Recommended publications
  • ICS 351: Today's Plan
    ICS 351: Today's plan SNMP Performance Peer-to-Peer Networking Simple Network Management Protocol ● SNMP uses the network to report status information and alerts about remote systems ● SNMP messages are carried over UDP ● values can be loaded on demand (pull model), but when needed and configured appropriately, alerts are sent independently by the systems being managed (push) 2 SNMP Management Information Base ● SNMP needs a machine-independent way to indicate which item of information is being requested or sent ● logically, the entire universe of information that can be accessed is built into a large tree: the Management Information Base or MIB ● the tree is extensible so individuals and organization can add their own subtrees -- private MIBs ● the tree is universal and known to all 3 navigating the MIB ● the path through the tree is sufficient to indicate one specific item (corresponding to a variable in a programming language) ● the path through the tree can be indicated by a sequence of numbers, the number of left siblings of the path being taken ● for example, 0.2.7.5.14.1.7.0 is such an Object Identifier (OID) ● OIDs are useful for enumerating arrays of objects, e.g., network interfaces, routing table entries 4 SNMP programs ● a network management station is used by the system administrator to monitor multiple systems ● a management agent must run on every managed device, get the required information, and provide it on request 5 SNMP basic operation ● the network management station may send GET requests to get one or more objects from specifc agents ● the network management station may also send SET requests to modify one or more objects on specifc agents ● agents will send TRAP or INFORM alerts to network management stations that they have been configured to alert ● because it uses UDP, SNMP (like DNS) cannot 6 assume that its operations will be successful.
    [Show full text]
  • Realistic Network Traffic Profile Generation: Theory and Practice
    Realistic Network Traffic Profile Generation : Theory and Practice Antoine Varet, Nicolas Larrieu To cite this version: Antoine Varet, Nicolas Larrieu. Realistic Network Traffic Profile Generation : Theory and Practice. Computer and Information Science, Canadian Center of Science and Education, 2014, 7 (2), pp 1-16. 10.5539/cis.v7n2p1. hal-00955420 HAL Id: hal-00955420 https://hal-enac.archives-ouvertes.fr/hal-00955420 Submitted on 4 Mar 2014 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. Realistic network traffic profile generation: theory and practice Antoine Varet1 & Nicolas Larrieu1 1 ENAC Telecom/Resco Laboratory, Toulouse, France Correspondence: Nicolas Larrieu, ENAC, E-mail: [email protected] Abstract Network engineers and designers need additional tools to generate network traffic in order to test and evaluate application performances or network provisioning for instance. In such a context, traffic characteristics are the very important part of the work. Indeed, it is quite easy to generate traffic but it is more difficult to produce traffic which can exhibit real characteristics such as the ones you can observe in the Internet. With the lack of adequate tools to generate data flows with “realistic behaviors” at the network or transport level, we needed to develop our tool entitled “SourcesOnOff”.
    [Show full text]
  • Vysoke´Ucˇenítechnicke´V Brneˇ
    VYSOKE´ UCˇ ENI´ TECHNICKE´ V BRNEˇ BRNO UNIVERSITY OF TECHNOLOGY FAKULTA INFORMACˇ NI´CH TECHNOLOGII´ U´ STAV INFORMACˇ NI´CH SYSTE´ MU˚ FACULTY OF INFORMATION TECHNOLOGY DEPARTMENT OF INFORMATION SYSTEMS NA´ STROJE PRO TESTOVA´ NI´ PROPUSTNOSTI SI´TEˇ BAKALA´ Rˇ SKA´ PRA´ CE BACHELOR’S THESIS AUTOR PRA´ CE PAVOL LOFFAY AUTHOR BRNO 2013 VYSOKE´ UCˇ ENI´ TECHNICKE´ V BRNEˇ BRNO UNIVERSITY OF TECHNOLOGY FAKULTA INFORMACˇ NI´CH TECHNOLOGII´ U´ STAV INFORMACˇ NI´CH SYSTE´ MU˚ FACULTY OF INFORMATION TECHNOLOGY DEPARTMENT OF INFORMATION SYSTEMS NA´ STROJE PRO TESTOVA´ NI´ PROPUSTNOSTI SI´TEˇ COMPARISON OF OPEN-SOURCE SOFTWARE TOOLS FOR NETWORK DIAGNOSTICS BAKALA´ Rˇ SKA´ PRA´ CE BACHELOR’S THESIS AUTOR PRA´ CE PAVOL LOFFAY AUTHOR VEDOUCI´ PRA´ CE Ing. PETR MATOUSˇ EK, Ph.D. SUPERVISOR BRNO 2013 Abstrakt Cílem této práce je vytvoøit re¹er¹i existujících open source nástrojù, které jsou zaměřeny na diagnostiku síťového provozu pomocí měření propustnosti a dalších základních para- metrù. Práce se věnuje vytvoření metodiky pro testování a vzájemné porovnání nástrojù. Výsledkem práce je doporučení pro běžného uživatele spočívající v doporučení správného nástroje pro měření příslušného parametru síťového provozu. Abstract The aim of this work is to make a research of existing open source tools, which are concerned with the diagnosis of the network transmission in the form of measuring of throughput and other basic parameters. The work is devoted to the construction of methodics for testing and comparing devices between themselves. The result of the
    [Show full text]
  • Available End-To-End Throughput Measurement
    Transactions. Georgian Technical University. AUTOMATED CONTROL SYSTEMS - No 2(13), 2012 AVAILABLE END-TO-END THROUGHPUT MEASUREMENT TOOLS Aivazov Vitali, Samkharadze Roman Georgian Technical University Summary Various types of applications working in the network are sensitive to the amount of data transferred in a period of time, which directly influences their performance and end user satisfaction. In order to ensure that the network is capable of providing sufficient resources, end-to-end achievable throughput should be measured between two end nodes. A variety of tools have been developed for providing throughput measurement and most widely used out of them are evaluated in this work. General throughput measurement mechanisms are assessed, which is followed by evaluation of each of these tools, their advantages and limitations. A comparative analysis is performed in terms of accuracy, intrusiveness and response time of active probing tools. An overall conclusion is made for the applicability of these tools. Keywords: throughput. Bandwidth. Active probing. TTCP. NetPerf. Iperf. Bwping. Pathchar. Pipechar Pathload. PathChirp. 1. Introduction Throughput is defined as an average rate of successful data delivery between end nodes in IP networks. This data may be delivered over a physical or logical link, or pass through a certain network node. The throughput is usually measured in bits per second, and sometimes in data packets per second or data packets per time slot. Acquiring an accurate measurement of this metric can be decisive for achieving application performance and end user satisfaction. The available bandwidth is also a key concept in congestion avoidance algorithms and intelligent routing systems. The available bandwidth measurement mechanisms can be divided into two main groups - passive and active measurement.
    [Show full text]
  • ICS 351: Today's Plan
    ICS 351: Today's plan Performance Peer-to-Peer Networking Latency ● latency is measured in seconds: – one-way (useful, but hard to measure) – round-trip (also useful, and easy to measure) ● usually measured by sending the smallest possible transmission unit ● latency matters when there are lots of round-trips – web transfers (less so with HTTP/2) – remote login ● latency matters when things must happen in real time – telephony, gaming, trading, remote control, telemedicine Throughput ● throughuput is measured in bits/second or Bytes/second – network equipment generally rated in bits/second – network downloads generally list Bytes/second – in this class and in much (but not all) of the world: ● b/s stands for bits/second ● B/s stands for Bytes/second ● throughput matters when lots of data must be sent ● ttcp, netperf, and iperf measure and report throughput Considerations ● at each level in the network, it is usually cheaper to provide less performance than more – in other words, it is more profitable to serve more people given the same infrastructure ● HTTP headers consume multiple hundred bytes, as opposed to about 40-60 bytes for TCP/IP headers ● but until HTTP/2, nobody was concerned enough to try to compress them – so the inefficiency must be negligible compared to the available throughput A more advance performance test ● send two successive pings as fast as possible ● at the slowest link in the path, the second will be delayed in proportion to the size of the first ● this allows us to estimate the speed of the bottleneck link ● bwping performs this test Peer-to-peer Networking ● in this class, it has been clear that a PC can perform as a router, and vice-versa ● why not use our PCs as routers? ● for many purposes this is adequate Content-Addressable Networking ● if we can change from IP addresses, there is less need for hierarchical control – content-addressable networks! – “Give me X” ● to increase the incentive, every node that has content and makes it available might get priority for obtaining other content – P2P networking, e.g.
    [Show full text]
  • Tester 10 Gigabit Ethernet Sítí
    České vysoké učení technické v Praze Fakulta elektrotechnická Katedra Řídící techniky Diplomová práce Tester 10 Gigabit Ethernet sítí Bc. Jáchym Šimák Vedoucí práce: Ing. Jan Kubr Studijní program: Otevřená informatika, strukturovaný, Navazující magisterský Obor: Počítačové inženýrství 2. ledna 2012 Poděkování Mé poděkování patří především rodině, za jejich podporu nejen během psaní diplomové práce, školiteli Ing. Janu Kubrovi, Ing. Alexandru Mouchouvi za trpělivost při mém lamentování nad funkčností laboratorních zařízení, Bc. Morisovi Bangourovi, za pomoc při sestavováním testovací sítě a Bc. Peterovi Šomló za korektury. III IV Prohlášení Prohlašuji, že jsem práci vypracoval samostatně a použil jsem podkladů uvedených v přiloženém seznamu. Souhlasím s užitím tohoto školního díla ve smyslu §60 Zákona č.121/2000 Sb., o právu autorském, o právech souvisejících s právem autorským a o změně některých zákonů (autorský zákon). V Praze dne 2. 1. 2012 ............................................................... V VI Abstrakt Diplomová práce se zabývá analýzou OpenSource nástrojů pro testování parametrů komplexních sítí, ale i jednotlivých zařízení. Rozebírá parametry, pro něž je třeba navrhnout metodiku měření a proměnné tyto parametry ovlivňující. Specifikuji hlavní typy aplikací a jejich požadavky na přenosový řetězec. Testuji OpenSource programy k testování sítí, včetně popisu nutných optimalizací k dosažení nejvyšších výkonů. Abstract This thesis deals with the assessment of OpenSource tools for testing complex networks and networking
    [Show full text]
  • Realistic Network Traffic Profile Generation: Theory and Practice
    Computer and Information Science; Vol. 7, No. 2; 2014 ISSN 1913-8989 E-ISSN 1913-8997 Published by Canadian Center of Science and Education Realistic Network Traffic Profile Generation: Theory and Practice Antoine Varet1 & Nicolas Larrieu1 1 ENAC Telecom/Resco Laboratory, Toulouse, France Correspondence: Nicolas Larrieu, ENAC Telecom/Resco Laboratory, Toulouse, France. E-mail: [email protected] Received: December 17, 2013 Accepted: February 11, 2014 Online Published: February 18, 2014 doi:10.5539/cis.v7n2p1 URL: http://dx.doi.org/10.5539/cis.v7n2p1 Abstract Network engineers and designers need additional tools to generate network traffic in order to test and evaluate application performances or network provisioning for instance. In such a context, traffic characteristics are the very important part of the work. Indeed, it is quite easy to generate traffic but it is more difficult to produce traffic which can exhibit real characteristics such as the ones you can observe in the Internet. With the lack of adequate tools to generate data flows with “realistic behaviors” at the network or transport level, we needed to develop our tool entitled “SourcesOnOff”. The emphasis of this article is on presenting this tool, how we implemented it and which methodology it follows to produce traffic with realistic characteristics. To do so, we chose to consider different stochastic processes in order to model the complexity of the different original traffics we wanted to replay. In our approach, we are able to consider several statistical laws and to combine their effects to model accurately the original behavior we analyzed in the real data.
    [Show full text]