QoS-aware distributed adaptive cooperative routing in wireless sensor networks

Md Abdur Razzaque, Mohammad Helal Uddin Ahmed, Choong Seon Hong, Sungwon Lee

Research output: Contribution to journalArticlepeer-review

46 Citations (Scopus)

Abstract

In this paper, we investigate a cooperative routing problem in time-varying Wireless Sensor Networks (WSNs) targeting the achievement of quality-of-service guarantees in delay and reliability domains. We develop a distributed adaptive cooperative routing protocol, called DACR, that exploits cooperative communication on top of delay- and energy-aware end-to-end routes and optimizes the trade-off between the reliability and delay through Lexicographic Optimization at each hop. We employ a lightweight reinforcement learning method to update the routing nodes with knowledge of expected performances that could be provided by the candidate relay nodes, helping to determine the optimal relay with the least overhead. The decision of selecting a transmission mode (i.e., direct or relayed transmission) at each hop is taken adaptively so that the reliability is maximized. The performances of our DACR have been evaluated through ns-2 simulations for a wide range of link failure rates and data traffic generation rates and the results show that the DACR outperforms a number of state-of-the-art protocols.

Original languageEnglish
Pages (from-to)28-42
Number of pages15
JournalAd Hoc Networks
Volume19
DOIs
Publication statusPublished - Aug 2014

Bibliographical note

Funding Information:
We would like to pay our highest level of gratitude and sincere thanks to the anonymous reviewers for their expert opinions and useful feedbacks, which helped a lot to enrich the quality of the paper. This research was supported by Next-Generation Information Computing Development Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science, ICT & Future Planning (2010-0020728). Dr. C.S. Hong is the corresponding auhor.

Keywords

  • Cooperative routing
  • Energy efficiency
  • Lexicographic optimization
  • Quality-of-service
  • Reinforcement learning
  • Wireless sensor networks

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