Protecting Location Privacy for Task Allocation in Ad Hoc Mobile Cloud Computing

Yanmin Gong*, Chi Zhang, Yuguang Fang, Jinyuan Sun

*Corresponding author for this work

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

71 Citations (Scopus)

Abstract

Mobile cloud computing (MCC) is an emerging cloud-computing paradigm that integrates cloud computing and mobile computing to enable many useful mobile applications. However, the large-scale deployment of MCC is hindered by the concerns on possible privacy leakage. In this paper, we investigate the privacy issues in the ad hoc MCC, and propose a framework that can protect the location privacy when allocating tasks to mobile devices. Our mechanism is based on differential privacy and geocast, and allows mobile devices to contribute their resources to the ad hoc mobile cloud without leaking their location information. We develop analytical models and task allocation strategies that balance privacy, utility, and system overhead in an ad hoc mobile cloud. We also conduct extensive experiments based on real-world data sets, and the results show that our framework can protect location privacy for mobile devices while providing effective services with low system overhead.
Original languageEnglish
Pages (from-to)110-121
JournalIEEE Transactions on Emerging Topics in Computing
Volume6
Issue number1
DOIs
Publication statusPublished - 1 Jan 2018
Externally publishedYes

Bibliographical note

Publication details (e.g. title, author(s), publication statuses and dates) are captured on an “AS IS” and “AS AVAILABLE” basis at the time of record harvesting from the data source. Suggestions for further amendments or supplementary information can be sent to [email protected].

Research Keywords

  • location privacy
  • Mobile cloud computing
  • reputation
  • task allocation

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