Abstract

In the era of continuously evolving applications of mobile devices in our daily routine, the processing capacity is posing as a bottleneck in offering a snappy experience to the users. Despite such impeccable technological advancements coming ever so swiftly in the industry, the resource constraints like processing power still dwarf the performance of certain types of computation-intensive or data-intensive applications. Cloud computing, with features like rapid scalability, ubiquitous network access, on-demand self-service seems to be the right solution to such problems. Mobile cloud computing has created a reverberation in the technology landscape around the world. In this paper, we focus on augmenting execution of mobile applications using cloud resources, more often known as offloading. The approach uses application partitioning, resource monitoring and computation offloading to address the performance or speedup issues. It monitors the available resources both at mobile and cloud side and then adaptively offloads different components of partitioned application to optimize the execution performance of the application. Genetic algorithm is used to find the optimum offloading scenario and the results are evaluated by simulating our approach and comparing it with the all mobile-side execution and all cloud-side execution.

Keyword

Mobile cloud computing, application partitioning, offloading, makespan.

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