Miguel Gutiérrez Gaitán
Thomas Watteyne
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Abstract
This article presents a novel centrality-driven gateway designation framework for the improved real-time performance of low-power wireless sensor networks (WSNs) at system design time. We target time-synchronized channel hopping (TSCH) WSNs with centralized network management and multiple gateways with the objective of enhancing traffic schedulability by design. To this aim, we propose a novel network centrality metric termed minimal-overlap centrality that characterizes the overall number of path overlaps between all the active flows in the network when a given node is selected as gateway. The metric is used as a gateway designation criterion to elect as a gateway the node leading to the minimal number of overlaps. The method is then extended to multiple gateways with the aid of the unsupervised learning method of spectral clustering. Concretely, after a given number of clusters are identified, we use the new metric at each cluster to designate as cluster gateway the node with the least overall number of overlaps. Extensive simulations with random topologies under centralized earliest-deadline-first (EDF) scheduling and shortest-path routing suggest our approach is dominant over traditional centrality metrics from social network analysis, namely, eigenvector, closeness, betweenness, and degree. Notably, our approach reduces by up to 40% the worst-case end-to-end deadline misses achieved by classical centrality-driven gateway designation methods.
- [1] . 2015. Decentralized traffic aware scheduling in 6TiSCH networks: Design and experimental evaluation. IEEE Internet of Things Journal 2, 6 (2015), 455–470.Google Scholar
Cross Ref
- [2] . 2022. Modernizing marinas in the mediterranean sea using smarty: Methodologies and lessons learned. In 2022 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops). IEEE, 472–477.Google ScholarCross Ref
- [3] . 2021. Demonstrating RA-TDMAs+ for robust communication in WiFi mesh networks. In 42nd IEEE Real-Time Systems Symposium (RTSS), Demo Session.Google Scholar
- [4] . 2009. Gateway selection in backbone wireless mesh networks. In 2009 IEEE Wireless Communications and Networking Conference. IEEE, 1–6.Google ScholarCross Ref
- [5] . 2010. Improved multiprocessor global schedulability analysis. Real-Time Systems 46, 1 (2010), 3–24.Google ScholarDigital Library
- [6] . 2005. Measuring the performance of schedulability tests. Real-Time Systems 30, 1-2 (2005), 129–154.Google ScholarDigital Library
- [7] . 2013. Cache “less for more” in information-centric networks (extended version). Computer Communications 36, 7 (2013), 758–770.Google ScholarDigital Library
- [8] . 2018. Multiple sink placement with latency and reliability guarantee in lossy wireless sensor networks. In IEEE Global Communications Conference (GLOBECOM). IEEE, 1–7.Google ScholarDigital Library
- [9] . 2016. QoS-aware cross-layer configuration for industrial wireless sensor networks. IEEE Trans. Indust. Informat. 12, 5 (2016), 1679–1691.Google ScholarCross Ref
- [10] . 2014. 6TiSCH: Deterministic IP-enabled industrial internet (of things). IEEE Communications Magazine 52, 12 (2014), 36–41.Google ScholarCross Ref
- [11] . 2020. TSCH networks for health IoT: Design, evaluation, and trials in the wild. ACM Transactions on Internet of Things 1, 2 (2020), 1–27.Google ScholarDigital Library
- [12] . 2010. Techniques for the synthesis of multiprocessor tasksets. In 1st International Workshop on Analysis Tools and Methodologies for Embedded and Real-time Systems (WATERS 2010). 6–11.Google Scholar
- [13] . 2021. Impact of network centrality on the gateway designation of real-time TSCH networks. In 17th IEEE International Conference on Factory Communication Systems (WFCS). IEEE.Google ScholarCross Ref
- [14] . 2021. EDF scheduling and minimal-overlap shortest-path routing for real-time TSCH networks. In Workshop on Next Generation Real-Time Embedded Systems (NG-RES), Vol. 87. Virtual, 2–1.Google Scholar
- [15] . 2022. Multi-gateway designation for real-time TSCH networks using spectral clustering and centrality. IEEE Embedded Systems Letters (2022).Google Scholar
- [16] . 2019. Multiprocessor scheduling meets the industrial wireless: A brief review. U. Porto Journal of Engineering 5, 1 (2019), 59–76.Google ScholarCross Ref
- [17] . 2020. Work-in-progress: Assessing supply/demand-bound based schedulability tests for wireless sensor-actuator networks. In IEEE International Conference on Factory Communication Systems (WFCS). IEEE, 1–4.Google ScholarCross Ref
- [18] . 2018. FF-DBF-WIN: On the forced-forward demand-bound function analysis for wireless industrial networks. In Work-in-Progress Session of the 30th Euromicro Conference on Real-Time System (ECRTS). 13–15.Google Scholar
- [19] . 2020. MASTER: Long-term stable routing and scheduling in low-power wireless networks. In 2020 16th International Conference on Distributed Computing in Sensor Systems (DCOSS). IEEE, 86–94.Google ScholarCross Ref
- [20] . 2020. Industrial internet of things: Recent advances, enabling technologies and open challenges. Computers & Electrical Engineering 81 (2020), 106522.Google ScholarDigital Library
- [21] . 2021. Time optimal concurrent data collection trees for IoT applications. In 2021 IEEE International Systems Conference (SysCon). IEEE, 1–7.Google ScholarCross Ref
- [22] . 2021. Data aggregation point placement for smart meters in the smart grid. IEEE Trans. on Smart Grid 13, 1 (2021), 541–554.Google ScholarCross Ref
- [23] . 2011. Time and space efficient spectral clustering via column sampling. In CVPR 2011. IEEE, 2297–2304.Google ScholarDigital Library
- [24] . 2012. A novel gateway selection method to maximize the system throughput of wireless mesh network deployed in disaster areas. In 2012 IEEE 23rd International Symposium on Personal, Indoor and Mobile Radio Communications-(PIMRC). IEEE, 771–776.Google Scholar
- [25] . 2015. Real-time wireless sensor-actuator networks for industrial cyber-physical systems. Proc. IEEE 104, 5 (2015), 1013–1024.Google ScholarCross Ref
- [26] . 2016. On the computation of centrality metrics for network security in mesh networks. In 2016 IEEE Global Communications Conference (GLOBECOM). IEEE, 1–6.Google ScholarDigital Library
- [27] . 2015. Betweenness centrality in delay tolerant networks: A survey. Ad Hoc Networks 33 (2015), 284–305.Google ScholarDigital Library
- [28] . 2010. MUSTER: Adaptive energy-aware multisink routing in wireless sensor networks. IEEE Trans. Mobile Computing 10, 12 (2010), 1694–1709.Google ScholarDigital Library
- [29] . 2001. On spectral clustering: Analysis and an algorithm. Advances in Neural Information Processing Systems 14 (2001).Google Scholar
- [30] . 2010. Centrality-based routing for wireless sensor networks. In 2010 IFIP Wireless Days. IEEE, 1–5.Google Scholar
- [31] . 2019. Clustering algorithms: A comparative approach. PLOS ONE 14, 1 (
01 2019), 1–34.DOI: Google ScholarCross Ref - [32] . 2010. Real-time scheduling for WirelessHART networks. In 2010 31st IEEE Real-Time Systems Symposium. IEEE, 150–159.Google ScholarDigital Library
- [33] . 2018. Industrial Internet of Things: Challenges, opportunities, and directions. IEEE Trans. on Industrial Informatics 14, 11 (2018), 4724–4734.Google ScholarCross Ref
- [34] . 2022. Energy-efficient coverage and connectivity of wireless sensor network in the framework of hybrid sensor and vehicular network. International Journal of Computers and Applications 44, 5 (2022), 444–454.Google ScholarCross Ref
- [35] . 2022. Nodes placement in wireless mesh networks using optimization approaches: A survey. Neural Computing and Applications (2022), 1–37.Google Scholar
- [36] . 2018. Topology management and TSCH scheduling for low-latency convergecast in in-vehicle WSNs. IEEE Transactions on Industrial Informatics 15, 2 (2018), 1082–1093.Google ScholarCross Ref
- [37] . 2018. TDMH-MAC: Real-time and multi-hop in the same wireless MAC. In 2018 IEEE Real-Time Systems Symposium (RTSS). IEEE, 277–287.Google ScholarCross Ref
- [38] . 2018. An analytical model for deploying mobile sinks in industrial Internet of Things. In IEEE Wireless Communications and Networking Conference Workshops. IEEE, 155–160.Google ScholarCross Ref
- [39] . 2008. How correlated are network centrality measures? Connections 28, 1 (2008), 16.Google Scholar
- [40] . 2015. A centrality-based topology control protocol for wireless mesh networks. Ad Hoc Networks 24 (2015), 34–54.Google ScholarDigital Library
- [41] . 2020. Evaluation of LoRaWAN for sensor data collection in an IIoT–based additive manufacturing project. In 2020 IEEE International Instrumentation and Measurement Technology Conference (I2MTC). IEEE, 1–6.Google ScholarDigital Library
- [42] . 2020. The internet of things in the oil and gas industry: a systematic review. IEEE Internet of Things Journal 7, 9 (2020), 8654–8673.Google ScholarCross Ref
- [43] . 2021. APaS: An adaptive partition-based scheduling framework for 6TiSCH networks. In 2021 IEEE 27th Real-Time and Embedded Technology and Applications Symposium (RTAS). IEEE, 320–332.Google ScholarCross Ref
- [44] . 2015. Industrial IEEE802. 15.4 e networks: Performance and trade-offs. In 2015 IEEE International Conference on Communications (ICC). IEEE, 604–609.Google ScholarCross Ref
- [45] . 2018. Real-time wireless routing for industrial internet of things. In 2018 IEEE/ACM 3rd International Conference on Internet-of-Things Design and Implementation (IoTDI). IEEE, 261–266.Google ScholarCross Ref
- [46] . 2016. Resource analysis for wireless industrial networks. In International Conference on Mobile Ad-Hoc and Sensor Networks (MSN). IEEE, 424–428.Google ScholarCross Ref
- [47] . 2010. Gateway designation for timely communications in instant mesh networks. In 2010 8th IEEE International Conference on Pervasive Computing and Communications Workshops (PERCOM Workshops). IEEE, 564–569.Google ScholarCross Ref
- [48] . 2018. Enabling robust and reliable transmission in Internet of Things with multiple gateways. Computer Networks 146 (2018), 183–199.Google ScholarCross Ref
- [49] . 2015. A comprehensive survey of clustering algorithms. Annals of Data Science 2, 2 (2015), 165–193.Google ScholarCross Ref
Index Terms
- Minimal-Overlap Centrality for Multi-Gateway Designation in Real-Time TSCH Networks
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