Coverage-Guaranteed and Energy-Efficient Participant Selection Strategy in Mobile Crowdsensing

Haneul Ko, Sangheon Pack, Victor C.M. Leung

Research output: Contribution to journalArticle

2 Citations (Scopus)

Abstract

In mobile crowdsensing (MCS), a participant selection strategy should be carefully designed to guarantee sufficient coverage and avoid unnecessary energy consumption. In this paper, we propose a coverage-guaranteed and energy-efficient participant selection (CG-EEPS) strategy, in which the MCS server determines participants based on the data usage profile and mobility level of mobile devices (MDs). In addition, CG-EEPS adopts a piggyback approach of sensory data for energy-efficient transmissions. To attain the optimal performance in CG-EEPS, a constraint Markov decision process (CMDP) problem is formulated and its optimal policy is obtained by a linear programming. To address the curse of dimensionality in CMDP, a greedy heuristic is proposed and evaluated. Trace-driven evaluation results demonstrate that CG-EEPS can achieve sufficient coverage rate only with 20% of participants compared to random selection schemes.

Original languageEnglish
JournalIEEE Internet of Things Journal
DOIs
Publication statusAccepted/In press - 2018 Jan 1

Keywords

  • constraint Markov decision process (CMDP).
  • coverage
  • energy
  • Energy consumption
  • Intelligent sensors
  • Markov processes
  • Mathematical model
  • Mobile crowdsensing (MCS)
  • Mobile handsets
  • piggyback
  • Servers

ASJC Scopus subject areas

  • Signal Processing
  • Information Systems
  • Hardware and Architecture
  • Computer Science Applications
  • Computer Networks and Communications

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