Cuckoo: flexible compute-intensive task offloading in mobile cloud computing

Zhigang Zhou, Hongli Zhang, Lin Ye, Xiaojiang Du

Research output: Contribution to journalArticlepeer-review

10 Scopus citations

Abstract

Mobile cloud computing (MCC) is an emerging technology to facilitate complex application execution on mobile devices. Mobile users are motivated to implement various tasks using their mobile devices for great flexibility and portability. However, such advantages are challenged by the limited battery life of mobile devices. This paper presents Cuckoo, a scheme of flexible compute-intensive task offloading in MCC for energy saving. Cuckoo seeks to balance the key design goals: maximize energy saving (technical feasibility) and minimize the impact on user experience with limited cost for offloading (realistic feasibility). Specifically, using a combination of static analysis and dynamic profiling, compute-intensive tasks are fine-grained marked from mobile application codes offline. According to the network transmission technologies supported in mobile devices and the runtime network conditions, adopting “task-bundled” strategy online offloads these tasks to MCC. In the task-hosted stage, we propose a skyline-based online resource scheduling strategy to satisfy the realistic feasibility of MCC. In addition, we adopt resource reservation to reduce the extra energy consumption caused by the task multi-offloading phenomenon. Further, we evaluate the performance of Cuckoo using real-life data sets on our MCC testbed. Our extensive experiments demonstrate that Cuckoo is able to balance energy consumption and execution performance.

Original languageEnglish
Pages (from-to)3256-3268
Number of pages13
JournalWireless Communications and Mobile Computing
Volume16
Issue number18
DOIs
StatePublished - 25 Dec 2016

Keywords

  • energy consumption evaluation
  • energy saving
  • mobile cloud computing
  • resource reservation
  • task offloading

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