Adaptive computing resource allocation for mobile cloud computing

Hongbin Liang, Tianyi Xing, Lin X. Cai, Dijiang Huang, Daiyuan Peng, Yan Liu

Research output: Contribution to journalArticle

18 Citations (Scopus)

Abstract

Mobile cloud computing (MCC) enables mobile devices to outsource their computing, storage and other tasks onto the cloud to achieve more capacities and higher performance. One of the most critical research issues is how the cloud can efficiently handle the possible overwhelming requests from mobile users when the cloud resource is limited. In this paper, a novel MCC adaptive resource allocation model is proposed to achieve the optimal resource allocation in terms of the maximal overall system reward by considering both cloud and mobile devices. To achieve this goal, we model the adaptive resource allocation as a semi-Markov decision process (SMDP) to capture the dynamic arrivals and departures of resource requests. Extensive simulations are conducted to demonstrate that our proposed model can achieve higher system reward and lower service blocking probability compared to traditional approaches based on greedy resource allocation algorithm. Performance comparisons with various MCC resource allocation schemes are also provided.

Original languageEnglish (US)
Article number181426
JournalInternational Journal of Distributed Sensor Networks
Volume2013
DOIs
StatePublished - 2013

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Mobile cloud computing
Resource allocation
Mobile devices
Blocking probability

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Engineering(all)

Cite this

Adaptive computing resource allocation for mobile cloud computing. / Liang, Hongbin; Xing, Tianyi; Cai, Lin X.; Huang, Dijiang; Peng, Daiyuan; Liu, Yan.

In: International Journal of Distributed Sensor Networks, Vol. 2013, 181426, 2013.

Research output: Contribution to journalArticle

Liang, Hongbin ; Xing, Tianyi ; Cai, Lin X. ; Huang, Dijiang ; Peng, Daiyuan ; Liu, Yan. / Adaptive computing resource allocation for mobile cloud computing. In: International Journal of Distributed Sensor Networks. 2013 ; Vol. 2013.
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