Recently, much research has proposed to integrate mobile cloud computing (MCC) with wireless sensor networks (WSNs) so that powerful cloud computing can be exploited to process the data gathered by ubiquitous WSNs and share the results with mobile users. However, all current MCC-WSN integration schemes ignore the following two observations: 1) the specific data mobile users request usually depend on the current locations of mobile users 2) most sensors are usually equipped with non-rechargeable batteries with limited energy. In this paper, motivated by these two observations, two novel collaborative location based sleep scheduling (CLSS) schemes are proposed for WSNs integrated with MCC. Based on the locations of mobile users, CLSS dynamically determines the awake or asleep status of each sensor node to reduce energy consumption of the integrated WSN. Particularly, CLSS1 focuses on maximizing the energy consumption saving of the integrated WSN while CLSS2 considers also the scalability and robustness of the integrated WSN. Theoretical and simulation results show that for WSNs integrated with MCC, both CLSS1 and CLSS2 can prolong the WSN lifetime while still satisfying the data requests of mobile users.
Keywords : Mobile cloud computing, wireless sensor networks, integration, location, network lifetime, sleep scheduling.