Energy-Efficient Transmission with Data Sharing in Participatory Sensing Systems

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review

14 Scopus Citations
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Author(s)

  • Weiwei Wu
  • Kai Liu
  • Feng Shan
  • Junzhou Luo

Related Research Unit(s)

Detail(s)

Original languageEnglish
Article number7676345
Pages (from-to)4048-4062
Journal / PublicationIEEE Journal on Selected Areas in Communications
Volume34
Issue number12
Online published25 Oct 2016
Publication statusPublished - Dec 2016

Abstract

In a participatory sensing system, data sensed from smartphone users are shared with the general public who requests data through submitting tasks. When multiple tasks request the data from a mobile user, the mobile user can make a transmission schedule to achieve the balance between the amount of data transmitted and energy consumption. Intuitively, reducing the amount of data transmitted by making use of data sharing between the tasks can save the energy consumption. However, due to the convexity of rate-power function for rate-Adaptive transmitting devices, a schedule purely minimizing the amount of data transmitted may not always be the optimal one minimizing the energy consumption. Thus, there exists a tradeoff between the amount of data transmitted and energy consumption. This paper formulates the problem as a bi-objective optimization problem to simultaneously minimize the amount of data transmitted and the energy consumption. Two task models are studied, first-in-first-out (FIFO) task model and arbitrary deadline (AD) task model, respectively. We first provide optimal algorithms for the off-line case. We then study the online case where requests arrive dynamically without prior information. For FIFO tasks, we develop an online algorithm that is O(ln L)-competitive with respect to both the amount of data transmitted and energy consumption, where L is the longest length of the time duration of the tasks. For AD tasks, we devise an online algorithm that is O(ln2 L)-competitive with respect to both the amount of data transmitted and energy consumption. Our simulation results validate the efficiency of our online algorithms.

Research Area(s)

  • competitive analysis, data sharing, energy efficiency, participatory sensing, Rate scheduling

Citation Format(s)