Collaborative Task Execution in Mobile Cloud Computing Under a Stochastic Wireless Channel

This paper investigates collaborative task execution between a mobile device and a cloud clone for mobile applications under a stochastic wireless channel. A mobile application is modeled as a sequence of tasks that can be executed on the mobile device or on the cloud clone. We aim to minimize the e...

Full description

Saved in:
Bibliographic Details
Published in:IEEE transactions on wireless communications 2015-01, Vol.14 (1), p.81-93
Main Authors: Weiwen Zhang, Yonggang Wen, Wu, Dapeng Oliver
Format: Article
Language:English
Subjects:
Algorithms
Applications programs
Channels
Cloning
Collaboration
Energy consumption
Enumeration
Heuristic
Mathematical models
Mobile communication
Mobile computing
Mobile handsets
Optimization
Tasks
Topology
Wireless communication
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:This paper investigates collaborative task execution between a mobile device and a cloud clone for mobile applications under a stochastic wireless channel. A mobile application is modeled as a sequence of tasks that can be executed on the mobile device or on the cloud clone. We aim to minimize the energy consumption on the mobile device while meeting a time deadline, by strategically offloading tasks to the cloud. We formulate the collaborative task execution as a constrained shortest path problem. We derive a one-climb policy by characterizing the optimal solution and then propose an enumeration algorithm for the collaborative task execution in polynomial time. Further, we apply the LARAC algorithm to solving the optimization problem approximately, which has lower complexity than the enumeration algorithm. Simulation results show that the approximate solution of the LARAC algorithm is close to the optimal solution of the enumeration algorithm. In addition, we consider a probabilistic time deadline, which is transformed to hard deadline by Markov inequality. Moreover, compared to the local execution and the remote execution, the collaborative task execution can significantly save the energy consumption on the mobile device, prolonging its battery life.
ISSN:1536-1276
1558-2248
DOI:10.1109/TWC.2014.2331051