Multi-objective Reinforcement Learning for Energy Harvesting Wireless Sensor Nodes

Shaswot Shresthamali, Masaaki Kondo, Hiroshi Nakamura

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

Abstract

Modern Energy Harvesting Wireless Sensor Nodes (EHWSNs) need to intelligently allocate their limited and unreliable energy budget among multiple tasks to ensure long-term uninterrupted operation. Traditional solutions are ill-equipped to deal with multiple objectives and execute a posteriori tradeoffs. We propose a general Multi-objective Reinforcement Learning (MORL) framework for Energy Neutral Operation (ENO) of EHWSNs. Our proposed framework consists of a novel Multi-objective Markov Decision Process (MOMDP) formulation and two novel MORL algorithms. Using our framework, EHWSNs can learn policies to maximize multiple task-objectives and perform dynamic runtime tradeoffs. The high computation and learning costs, usually associated with powerful MORL algorithms, can be avoided by using our comparatively less resource-intensive MORL algorithms. We evaluate our framework on a general single-task and dual-task EHWSN system model through simulations and show that our MORL algorithms can successfully tradeoff between multiple objectives at runtime.

Original languageEnglish
Title of host publicationProceedings - 2021 IEEE 14th International Symposium on Embedded Multicore/Many-Core Systems-on-Chip, MCSoC 2021
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages98-105
Number of pages8
ISBN (Electronic)9781665438605
DOIs
Publication statusPublished - 2021
Event14th IEEE International Symposium on Embedded Multicore/Many-Core Systems-on-Chip, MCSoC 2021 - Singapore, Singapore
Duration: 2021 Dec 202021 Dec 23

Publication series

NameProceedings - 2021 IEEE 14th International Symposium on Embedded Multicore/Many-Core Systems-on-Chip, MCSoC 2021

Conference

Conference14th IEEE International Symposium on Embedded Multicore/Many-Core Systems-on-Chip, MCSoC 2021
Country/TerritorySingapore
CitySingapore
Period21/12/2021/12/23

Keywords

  • DDPG
  • Energy Harvesting Wireless Sensor Nodes
  • Multi objective Reinforcement Learning
  • Reinforcement Learning

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Science Applications
  • Hardware and Architecture
  • Electrical and Electronic Engineering

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