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Distributed Graph Routing and Scheduling for Industrial Wireless Sensor-Actuator Networks Junyang Shi, Student Member, IEEE,Mosha , Member, IEEE, and Zhicheng Yang

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Distributed Graph Routing and Scheduling for Industrial Wireless Sensor-Actuator Networks Junyang Shi, Student Member, IEEE,Mosha , Member, IEEE, and Zhicheng Yang This article has been accepted for inclusion in a future issue of this journal. Content is final as presented, with the exception of pagination. IEEE/ACM TRANSACTIONS ON NETWORKING 1 Distributed Graph Routing and Scheduling for Industrial Wireless Sensor-Actuator Networks Junyang Shi, Student Member, IEEE,MoSha , Member, IEEE, and Zhicheng Yang Abstract— Wireless sensor-actuator networks (WSANs) tech- 2025 (according to McKinsey’s report on future disruptive nology is appealing for use in the industrial Internet of technologies) [3]. Things (IoT) applications because it does not require wired Industrial networks, the underlying support of Industrial infrastructure. Battery-powered wireless modules easily and inex- pensively retrofit existing sensors and actuators in the industrial IoT (IIoT), typically connect hundreds or thousands of sensors facilities without running cabling for communication and power. and actuators in industrial facilities, such as steel mills, oil The IEEE 802.15.4-based WSANs operate at low-power and can refineries, chemical plants, and infrastructures implement- be manufactured inexpensively, which makes them ideal where ing complex monitoring and control processes. Although battery lifetime and costs are important. Almost, a decade of real- the typical process applications have low data rates, they world deployments of WirelessHART standard has demonstrated pose unique challenges because of their critical demands the feasibility of using its core techniques including reliable graph routing and time slotted channel hopping (TSCH) to achieve for reliable and real-time communication in harsh industrial reliable low-power wireless communication in the industrial environments. Failing to achieve such performance can lead facilities. Today, we are facing the fourth Industrial Revolution as to production inefficiency, safety threats, and financial loss. proclaimed by political statements related to the Industry 4.0 Ini- These requirements have been traditionally met by specifically tiative of the German Government. There exists an emerging chosen wired solutions, e.g., Highway Addressable Remote demand for deploying a large number of field devices in an indus- Transducer (HART) [4], where cables connect sensors and trial facility and connecting them through the WSAN. However, a major limitation of current WSAN standards is their limited forward sensor readings to a control room where a controller scalability due to their centralized routing and scheduling that sends commands to actuators. However, wired networks are enhance the predictability and visibility of network operations often costly to deploy and maintain in industrial environments at the cost of scalability. This paper decentralizes the network and difficult to reconfigure to accommodate new production management in WirelessHART and presents the first Distributed process requirements. G S raph routing and autonomous cheduling (DiGS) solution that Wireless sensor-actuator networks (WSANs) technology is allows the field devices to compute their own graph routes and transmission schedules. The experimental results from two appealing for use in industrial process applications because it physical testbeds and a simulation study shows our approaches does not require wired infrastructure. Battery-powered wire- can significantly improve the network reliability, latency, and less modules easily and inexpensively retrofit existing sensors energy efficiency under dynamics. and actuators in industrial facilities without running cabling Index Terms— Wireless sensor-actuator networks, Industrial for communication and power. IEEE 802.15.4-based WSANs Internet of Things, graph routing, transmission scheduling. operate at low-power and can be manufactured inexpensively, which makes them ideal where battery lifetime and costs are important. Almost a decade of real-world deployments of I. INTRODUCTION WirelessHART standard [5] has demonstrated the feasibility of HE Internet of Things (IoT) refers to a broad vision using its core techniques including reliable graph routing and Twhereby things such as everyday objects, places, and Time Slotted Channel Hopping (TSCH) to achieve reliable environments are interconnected with one another via the low-power wireless communication in industrial facilities. Internet [1]. Until recently, most of the IoT infrastructure and Under graph routing, a packet is scheduled to reach its desti- applications development work by businesses have focused nation through multiple redundant paths to enhanced end-to- on smart homes and wearables. However, it is “production end reliability. TSCH requires that all devices in the network and manufacturing” cyber-physical system (CPS), underlying are time synchronized and hop channels to exploit frequency the 4th generation of industrial revolution (or Industry 4.0), diversity. that presents one of the largest economic impact potential Today we are facing the 4th Industrial Revolution as of IoT [2] – up to $47 trillion in added value globally by proclaimed by political statements related to the Industry 4.0 Initiative of the German Government [6]. There exists Manuscript received September 21, 2018; revised April 5, 2019 and an emerging demand for deploying a large number of field June 11, 2019; accepted June 24, 2019; approved by IEEE/ACM TRANSAC- devices in an industrial facility, e.g., hundreds of devices over TIONS ON NETWORKING Editor G. Paschos. This work was supported by the NSF under Grant CRII-1657275 (NeTS). (Corresponding author: Mo Sha.) an oil field, and connecting them through a WSAN. However, J. Shi and M. Sha are with the Department of Computer Science, State a major limitation of current WSAN standards such as Wire- University of New York at Binghamton, Binghamton, NY 13902 USA lessHART is their limited scalability due to their centralized (e-mail: [email protected]; [email protected]). routing and scheduling that enhance the predictability and Z. Yang is with the Department of Computer Science, University of California, Davis, CA 95616 USA (e-mail: [email protected]). visibility of network operations at the cost of scalability. For Digital Object Identifier 10.1109/TNET.2019.2925816 instance, when encountering network dynamics (e.g., node 1063-6692 © 2019 IEEE. Personal use is permitted, but republication/redistribution requires IEEE permission. See http://www.ieee.org/publications_standards/publications/rights/index.html for more information. This article has been accepted for inclusion in a future issue of this journal. Content is final as presented, with the exception of pagination. 2 IEEE/ACM TRANSACTIONS ON NETWORKING or link failure, topology change), the centralized Network designated sinks in a wireless sensor networkt [7]. CTP has Manager (a software module) in a WirelessHART network been used in research, teaching, and in commercial products. has to regenerate the routes and transmission schedule and Experiences with CTP have also informed the design of then distribute them to all devices, introducing long delay and RPL [8]. However, both CTP and RPL are tree-based routing large overhead. protocols and cannot generate graph routes which are specified Recently, there has been an increasing interest in developing in WirelessHART to achieve high reliability. Thus, they are new distributed scheduling approaches, which run on top not suitable for those mission-critical industrial applications, of the distributed routing protocols developed for wireless where packet lost must become an exception. In contrast, sensor networks (WSNs), such as the Collection Tree Protocol multipath routing protocols (e.g., [11]–[15]) are proposed to (CTP) [7] and the IPv6 Routing Protocol for Low-Power and enhance reliability by providing a few either node-disjoint or Lossy Networks (RPL) [8], to replace the centralized routing link-disjoint paths between source and destination. There also and scheduling in industrial WSANs. For instance, the IETF exist RPL based multipath routing protocols (e.g, [16]–[20]), created the 6TiSCH working group to standardize how to which are designed to balance the traffic load and energy use an IPv6-enabled upper stack on top of IEEE 802.15.4e consumption among nodes in the network. Comparing to these TSCH networks [9]. Duquennoy et al. developed the Orchestra protocols, the graph routing specified in WirelessHART is that allows nodes in the RPL networks to compute their designed to achieve high reliability by providing a high degree own schedules [10]. Unfortunately, the stringent reliability and of routing redundancy to the TSCH networks. Its real-world real-time requirements of industrial applications distinguish deployments during the last decade have demonstrated the traditional WSNs from industrial WSANs, that packet lost feasibility of achieving reliable low-power wireless communi- must become an exception and redundant routes between a cation in industrial facilities. Han et al. [21] and Wu et al. [22] source and a destination are essential to meet with guaranteed developed two algorithms to generate graph routes in a cen- service. Our study shows that the networks relying on the tree- tralized fashion, while Modekurthy et al. proposed to use the based routing suffer long repair time and insufficient reliability Bellman-Ford algorithm to generate the graph routes [23] in a when encountering external interference and node failure. distributed fashion. Comparing to these efforts, we developed This paper aims to address the abovementioned scalability the first RPL-based
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