Designing security-aware incentives for computation offloading via device-to-device communication

Jie Xu, Lixing Chen, Kun Liu, Cong Shen

Research output: Contribution to journalArticlepeer-review

26 Scopus citations


Computation offloading via device-to-device (D2D) communication, or D2D offloading, can enhance mobile computing performance by exploiting spare computing resources of nearby user devices. The success of D2D offloading relies on user participation in collaborative service provisioning, which incurs extra costs to users providing the service, thus mandating an incentive mechanism that can compensate for these costs. Although incentive mechanism design has been intensively studied in the literature, this paper considers a much more challenging yet less investigated problem in which selfish users are also facing interdependent security risks, such as infectious proximity-based attacks. Security cost is significantly different in nature from conventional service provisioning costs such as energy consumption because security risks often depend on the collective behavior of all users. To this end, we build a novel mathematical framework by leveraging the combined power of game theory and epidemic theory to investigate the interplay between user incentives and interdependent security risks in D2D offloading, thereby enabling the design of security-aware incentive mechanisms. Our analysis discovers an interesting 'less is more' phenomenon: although giving users more incentives promotes more participation, it may harm the network operator's utility. This is because too much participation may foster persistent security risks, and as a result, the effective participation level does not improve.

Original languageEnglish (US)
Article number8412253
Pages (from-to)6053-6066
Number of pages14
JournalIEEE Transactions on Wireless Communications
Issue number9
StatePublished - Sep 2018


  • Device-to-device
  • computation offloading
  • epidemic models
  • game theory
  • incentives
  • security

ASJC Scopus subject areas

  • Computer Science Applications
  • Electrical and Electronic Engineering
  • Applied Mathematics


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