An Optimal Offloading Partitioning Algorithm in Mobile Cloud Computing

  • Huaming WuEmail author
  • William Knottenbelt
  • Katinka Wolter
  • Yi Sun
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9826)


Application partitioning splits the executions into local and remote parts. Through optimal partitioning, the device can obtain the most benefit from computation offloading. Due to unstable resources at the wireless network (bandwidth fluctuation, network latency, etc.) and at the service nodes (different speed of the mobile device and cloud server, memory, etc.), static partitioning solutions in previous work with fixed bandwidth and speed assumptions are unsuitable for mobile offloading systems. In this paper, we study how to effectively and dynamically partition a given application into local and remote parts, while keeping the total cost as small as possible. We propose a novel min-cost offloading partitioning (MCOP) algorithm that aims at finding the optimal partitioning plan (determine which portions of the application to run on mobile devices and which portions on cloud servers) under different cost models and mobile environments. The simulation results show that the proposed algorithm provides a stable method with low time complexity which can significantly reduce execution time and energy consumption by optimally distributing tasks between mobile devices and cloud servers, and in the meantime, it can well adapt to environmental changes, such as network perturbation.


Mobile cloud computing Communication networks Offloading Cost graph Application partitioning 


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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Huaming Wu
    • 1
    Email author
  • William Knottenbelt
    • 2
  • Katinka Wolter
    • 3
  • Yi Sun
    • 3
  1. 1.Center for Applied MathematicsTianjin UniversityTianjinChina
  2. 2.Department of ComputingImperial College LondonLondonUK
  3. 3.Institut für InformatikFreie Universität BerlinBerlinGermany

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