Due to limitation of mobile device in terms of battery life and processing power, Mobile Cloud Computing (MCC) has become an attractive choice to leverage this shortcoming as the mobile computation could be offloaded to the cloud, which is so-called mobile computation offloading. Existing research on mobile computation offloading considers offloading a mobile computation to a single cloud. However, in the real world a computation service could be provided by multiple clouds and each computation service. Thus, a new and interesting research problem in mobile computation offloading is how to select a computation service for each of the computation tasks of a mobile computation such that the computation time of the mobile computation, the energy consumption of the mobile device and the cost of using the computation services are minimized. This is so called multi-site computation offloading in mobile cloud computing. In this paper we formulate the multi-site computation offloading problem, propose a heuristic algorithm for the multi-site computation offloading problem and evaluate the heuristic algorithm.
Enzai and Tang formulated the multisite computation offloading problem in MCC as a multiobjective combinatorial optimization problem such that the execution time of the mobile computation, the energy consumption of the MD, and the cost of using the cloud services are minimized and then transformed it into a weighted single-objective optimization problem REF .