Abstract
Cloud computing can enhance the computing capability of mobile systems by offloading. However, the communication between the mobile device and the cloud is not free. Transmitting large data to cloud consumes much more energy than processing data in mobile device, especially in a low bandwidth condition. Further, some processing tasks can avoid transmitting large data between mobile device and server. Those processing tasks (encoding, rendering) are as the compress algorithm, which can reduce the size of raw data before it is sent to server. In this paper, we present an energy efficient task scheduling strategy (EETS) to determine what kind of task with certain amount of data should be chosen to be offloaded under different environment. We have evaluated the scheduler by using an Android smartphone. The results show that our strategy can achieve 99% of accuracy to choose the right action in order to minimize the system energy usage.
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