Topology Management and TSCH Scheduling for Low-Latency Convergecast in In-Vehicle WSNs

被引:26
|
作者
Tavakoli, Rasool [1 ]
Nabi, Majid [1 ,2 ]
Basten, Twan [1 ]
Goossens, Kees [1 ]
机构
[1] Eindhoven Univ Technol, Dept Elect Engn, NL-5600 MB Eindhoven, Netherlands
[2] Isfahan Univ Technol, Dept Elect & Comp Engn, Esfahan 8415683111, Iran
关键词
Industrial wireless sensor networks (WSNs); intra-vehicle networks; low latency; scheduling; time-slotted channel hopping (TSCH); topology management; WIRELESS SENSOR NETWORKS; ROUTING ALGORITHM;
D O I
10.1109/TII.2018.2853986
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Wireless sensor networks (WSNs) are considered as a promising solution in intravehicle networking to reduce wiring and production costs. This application requires reliable and real-time data delivery, while the network is very dense. The time-slotted channel hopping (TSCH) mode of the IEEE 802.15.4 standard provides a reliable solution for low-power networks through guaranteed medium access and channel diversity. However, satisfying the stringent requirements of in-vehicle networks is challenging and demands for special consideration in network formation and TSCH scheduling. This paper targets convergecast in dense in-vehicle WSNs, in which all nodes can potentially directly reach the sink node. A cross-layer low-latency topology management and TSCH scheduling (LLTT) technique is proposed that provides a very high timeslot utilization for the TSCH schedule and minimizes communication latency. It first picks a topology for the network that increases the potential of parallel TSCH communications. Then, by using an optimized graph isomorphism algorithm, it extracts a proper match in the physical connectivity graph of the network for the selected topology. This network topology is used by a lightweight TSCH schedule generator to provide low data delivery latency. Two techniques, namely grouped retransmission and periodic aggregation, are exploited to increase the performance of the TSCH communications. The experimental results show that LLTT reduces the end-to-end communication latency compared to other approaches, while keeping the communications reliable by using dedicated links and grouped retransmissions.
引用
收藏
页码:1082 / 1093
页数:12
相关论文
共 50 条
  • [31] Decentralized Low-Latency Task Scheduling for Ad-Hoc Computing
    Edinger, Janick
    Breitbach, Martin
    Gabrisch, Niklas
    Schafer, Dominik
    Becker, Christian
    Rizk, Amr
    2021 IEEE 35TH INTERNATIONAL PARALLEL AND DISTRIBUTED PROCESSING SYMPOSIUM (IPDPS), 2021, : 776 - 785
  • [32] Slice Management in SDN PON Supporting Low-Latency Services
    Centofanti, Carlo
    Marotta, Andrea
    Cassioli, Dajana
    Graziosi, Fabio
    Sambo, Nicola
    Valcarenghi, Luca
    Bernard, Chris
    Roberts, Hal
    2022 EUROPEAN CONFERENCE ON OPTICAL COMMUNICATION (ECOC), 2022,
  • [33] Lever: Towards Low-Latency Batched Stream Processing by Pre-Scheduling
    Chen, Fei
    Wu, Song
    Jin, Hai
    Yao, Yin
    Liu, Zhiyi
    Gu, Lin
    Zhou, Yongluan
    PROCEEDINGS OF THE 2017 SYMPOSIUM ON CLOUD COMPUTING (SOCC '17), 2017, : 643 - 643
  • [34] Priority-based grant-aware scheduling for low-latency switching
    Song, Jongtae
    Han, Kyeong-Eun
    Kim, Dae-Ub
    Park, Chansung
    Kim, Kwangjoon
    PHOTONIC NETWORK COMMUNICATIONS, 2018, 36 (02) : 175 - 186
  • [35] Priority-based grant-aware scheduling for low-latency switching
    Jongtae Song
    Kyeong-Eun Han
    Dae-Ub Kim
    Chansung Park
    Kwangjoon Kim
    Photonic Network Communications, 2018, 36 : 175 - 186
  • [36] Edge Learning for Low-Latency Video Analytics: Query Scheduling and Resource Allocation
    Lin, Jie
    Yang, Peng
    Wu, Wen
    Zhang, Ning
    Han, Tao
    Yu, Li
    2021 IEEE 18TH INTERNATIONAL CONFERENCE ON MOBILE AD HOC AND SMART SYSTEMS (MASS 2021), 2021, : 252 - 259
  • [37] FEDERATED-LEARNING-BASED CLIENT SCHEDULING FOR LOW-LATENCY WIRELESS COMMUNICATIONS
    Xia, Wenchao
    Wen, Wanli
    Wong, Kai-Kit
    Quek, Tony Q. S.
    Zhang, Jun
    Zhu, Hongbo
    IEEE WIRELESS COMMUNICATIONS, 2021, 28 (02) : 32 - 38
  • [38] Scalable Architecture and Low-Latency Scheduling Schemes for Next Generation Photonic Datacenters
    Kiaei, Mohammad
    Mehrvar, Hamid
    Bernier, Eric
    2016 IEEE INTERNATIONAL CONFERENCE ON COMMUNICATIONS (ICC), 2016,
  • [39] Scheduling of Low-Latency Medical Services in Healthcare Cloud with Deep Reinforcement Learning
    Du, Hongfei
    Liu, Ming
    Liu, Nianbo
    Li, Deying
    Li, Wenzhong
    Xu, Lifeng
    TSINGHUA SCIENCE AND TECHNOLOGY, 2025, 30 (01): : 100 - 111
  • [40] Joint Routing and Scheduling for Low-Latency Packet Forwarding in Fronthaul Bridged Network
    Nakayama, Yu
    Hisano, Daisuke
    Kubo, Takahiro
    Fukada, Youichi
    Terada, Jun
    Otaka, Akihiro
    23RD OPTO-ELECTRONICS AND COMMUNICATIONS CONFERENCE (OECC2018), 2018,