Green Communications and Networking. First International Conference, GreeNets 2011, Colmar, France, October 5-7, 2011, Revised Selected Papers

Research Article

Bandwidth Aware Application Partitioning for Computation Offloading on Mobile Devices

Download
356 downloads
  • @INPROCEEDINGS{10.1007/978-3-642-33368-2_6,
        author={Feifei Wu and Jianwei Niu and Yuhang Gao},
        title={Bandwidth Aware Application Partitioning for Computation Offloading on Mobile Devices},
        proceedings={Green Communications and Networking. First International Conference, GreeNets 2011, Colmar, France, October 5-7, 2011, Revised Selected Papers},
        proceedings_a={GREENETS},
        year={2012},
        month={11},
        keywords={Computation offloading Graph Partitioning Energy Saving Mobile Devices Confidence Probability},
        doi={10.1007/978-3-642-33368-2_6}
    }
    
  • Feifei Wu
    Jianwei Niu
    Yuhang Gao
    Year: 2012
    Bandwidth Aware Application Partitioning for Computation Offloading on Mobile Devices
    GREENETS
    Springer
    DOI: 10.1007/978-3-642-33368-2_6
Feifei Wu1,*, Jianwei Niu1,*, Yuhang Gao1,*
  • 1: Beihang University
*Contact email: wufeifei@buaa.edu.cn, niujianwei@buaa.edu.cn, gaoyuhang@buaa.edu.cn

Abstract

Computation offloading is a promising method for reducing power consumption of mobile devices by offloading computation to remote servers. For computation offloading, application partitioning is a key component. However, making a good application partitioning is challenging, as it needs to carefully consider the tradeoffs between the communication cost and computational benifits. Most of previous work makes application partitioning by using a static bandwidth to measure the communication cost and thus cannot adapt to scenarios with dynamic bandwidth. To address this problem, in this paper, we propose a Bandwidth Aware Application Partitioning Scheme (BAAP). BAAP models the bandwidth as a random variable and formulate the application partition as a 0-1 Integer Programming with Probability (IPP) problem. Then BAAP adopts Branch and Bound algorithm to solve the problem. Experimental results show that BAAP can greatly reduce energy consumption while satisfying the cost and time constraints with guaranteed confidence probabilities regardless of different network bandwidth.