Utility Based Data Computing Scheme to Provide Sensing Service in Internet of Things

Yilong Hui, Zhou Su, Song Guo

Research output: Journal article publicationJournal articleAcademic researchpeer-review

40 Citations (Scopus)

Abstract

Recently, the internet-of-things (IoT) has emerged as a new paradigm with an ever-increasing number of things to be connected to the internet. Different from the conventional paradigms, in the IoT the data computing scheme is needed to efficiently collect and offer data to provide sensing service. However, the existing data computing schemes are unfriendly which lack the integrated and incentive consideration to reduce the cost of data collection and encourage more participants for cooperation. Therefore, in this paper we propose a utility-based data computing scheme which allows vehicles to collect mobile data in the urban area, in order to provide sensing service in the IoT. First, we present an integrated architecture by introducing roadside buffers where each buffer can have a sink node to collect sensor data from vehicles. Next, by considering both the time cost and power cost during the data collection, we make the analysis of utilities in data computing process. Then, with a bargaining game to model the interaction among participants, a utility based data computing scheme is proposed with incentives where the optimal price can be determined for sensing service. Finally, extensive simulation experiments prove that the proposed scheme can efficiently improve the sensing service in IoT with a low cost.

Original languageEnglish
Article number7864378
Pages (from-to)337-348
Number of pages12
JournalIEEE Transactions on Emerging Topics in Computing
Volume7
Issue number2
DOIs
Publication statusPublished - 1 Jan 2019

Keywords

  • bargaining game
  • data computing
  • Internet-of-things
  • sensor data

ASJC Scopus subject areas

  • Computer Science (miscellaneous)
  • Information Systems
  • Human-Computer Interaction
  • Computer Science Applications

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