Distributed reinforcement learning algorithm for energy harvesting sensor networks

Hanan Al-Tous, Imad Barhumi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Citations (Scopus)

Abstract

In this paper, a distributed reinforcement-learning (RL) algorithm is proposed for power control and data scheduling in energy-harvesting (EH) multi-hop wireless-sensor-networks (WSNs). The WSN consists of M EH sensor nodes aiming to transmit their data to a sink node with minimum delay. Each sensor node has a battery of limited capacity to save the harvested energy and a buffer of limited size to store both the sensed and relayed data from neighboring nodes. A state-action-reward-state-action (SARSA) based distributed algorithm is proposed. The proposed distributed-SARSA (D-SARSA) algorithm adaptively changes the transmitted data and power control at each sensor node according to the state information such that the data of all sensor nodes are received at the sink node with minimum delay. Simulation results demonstrate the merits of the proposed algorithm.

Original languageEnglish
Title of host publication2019 IEEE International Black Sea Conference on Communications and Networking, BlackSeaCom 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728132341
DOIs
Publication statusPublished - Jun 2019
Event7th IEEE International Black Sea Conference on Communications and Networking, BlackSeaCom 2019 - Sochi, Russian Federation
Duration: Jun 3 2019Jun 6 2019

Publication series

Name2019 IEEE International Black Sea Conference on Communications and Networking, BlackSeaCom 2019

Conference

Conference7th IEEE International Black Sea Conference on Communications and Networking, BlackSeaCom 2019
Country/TerritoryRussian Federation
CitySochi
Period6/3/196/6/19

Keywords

  • SARSA
  • Wireless sensor network
  • energy harvesting
  • reinforcement learning

ASJC Scopus subject areas

  • Hardware and Architecture
  • Signal Processing
  • Information Systems and Management
  • Computer Networks and Communications
  • Safety, Risk, Reliability and Quality

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