FLeet: When time-bounded communication meets high energy-efficiency

Chayan Sarkar*, R. Venkatesha Prasad, Koen Langendoen

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

7 Citations (Scopus)
160 Downloads (Pure)

Abstract

With the advent of low-cost, embedded sensor-actuator devices, the applications of cyber-physical systems have spread multi-fold in domains like infrastructure, manufacturing, automation, etc. Wireless sensor-actuator networks (WSANs) act as the backbone for applications in these domains. Typical WSAN deployments focus on energy-efficiency (in-turn lifetime) as replacing batteries is labor intensive and expensive. However, many CPS applications require highly-reliable data delivery with strict time bounds. Unfortunately, the classical approach of scheduling/prioritizing flows for bounded time communication is hard to implement with energy-constrained embedded devices. In this work, we present FLEET, a communication primitive that guarantees timely data delivery with 1) low latency by scheduling a maximum number of end-to-end flows within a short time span; 2) highly energy-efficient networking; and 3) reliable data delivery. Using a smart parallelization technique, FLEET achieves simultaneous transmissions while guaranteeing data delivery. This reduces the average duty-cycle of the nodes and makes it more energy-efficient than many state-of-the-art protocols. By combining multiple routing strategies, FLEET not only simplifies the schedulability problem but also accommodates more flows within a time span reducing delay considerably. Overall, with respect to the state of the art, FLEET offers a delay and duty cycling reduction by 2.2 and 2.8 times, respectively.

Original languageEnglish
Article number8731988
Pages (from-to)77555-77568
Number of pages14
JournalIEEE Access
Volume7
DOIs
Publication statusPublished - 2019

Keywords

  • Capture effect
  • Clustering
  • Constructive interference
  • Cyber-physical systems
  • Energy-efficient
  • Internet of Things
  • Low-latency
  • Wireless sensor networks
  • OA-Fund TU Delft

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