Gao, Bo (2015) Developing energy-aware workload offloading frameworks in mobile cloud computing. PhD thesis, University of Warwick.

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Abstract

Mobile cloud computing is an emerging field of research that aims to provide a platform on which intelligent and feature-rich applications are delivered to the user at any time and at anywhere. Computation offload between mobile and cloud plays a key role in this vision and ensures that the integration between mobile and cloud is both seamless and energy-efficient. In this thesis, we develop a suite of energy-aware workload offloading frameworks to accommodate the efficient execution of mobile workflows on a mobile cloud platform. We start by looking at two energy objectives of a mobile cloud platform. While the first objective aims at minimising the overall energy cost of the platform, the second objective aims at the longevity of the platform taking into account the residual battery power of each device. We construct optimisation models for both objectives and develop two efficient algorithms to approximate the optimal solution. According to simulation results, our greedy autonomous offload (GAO) algorithm is able to efficiently produce allocation schemes that are close to optimal. Next, we look at the task allocation problem from a workflow's perspective and develop energy-aware offloading strategies for time-constrained mobile workflows. We demonstrate the effect of software and hardware characteristics have over the offload-efficiency of mobile workflows with a workflow-oriented greedy autonomous offload (WGAO) algorithm, an extension to the GAO algorithm. Thirdly, we propose a novel network I-O model to describe the bandwidth dependencies and allocation problem in mobile networks. This model lays the foundation for further objective developments such as the cost-based and adaptive bandwidth allocation schemes which we also present in this thesis. Lastly, we apply a game theoretical approach to model the non-cooperative behaviour of mobile cloud applications that reside on the same device. Mixed-strategy Nash equilibrium is derived for the offload game which further quantifies the price of anarchy of the system.

Item Type:	Thesis (PhD)
Subjects:	Q Science > QA Mathematics > QA76 Electronic computers. Computer science. Computer software
Library of Congress Subject Headings (LCSH):	Cloud computing, Mobile computing
Official Date:	June 2015
Dates:	Date Event June 2015 UNSPECIFIED
Institution:	University of Warwick
Theses Department:	Department of Computer Science
Thesis Type:	PhD
Publication Status:	Unpublished
Supervisor(s)/Advisor:	He, Ligang
Extent:	xvii, 161 leaves : charts
Language:	eng

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