Collaborative location-based sleep scheduling to integrate wireless sensor networks with mobile cloud computing
Chunsheng Zhu, Victor C. M. Leung, Laurence Tianruo Yang, Xiping Hu, Lei Shu · 2013
Mobile cloud computing (MCC) is a very hot research focus of both academia and industries, since it can greatly relieve the hardware limitation of mobile devices as well as create new fascinating mobile services with its tremendous storage and processing ability. Moreover, wireless sensor networks (WSNs) have been attracting attention for about two decades, because of its powerful capability to detect physical or environmental conditions. Motivated by incorporating the advantages of both MCC and WSNs, a lot of schemes which integrate MCC with WSNs have been proposed for exploiting the cloud to share the data gathered by WSNs to mobile users. Particularly, all current integration frameworks utilize the always-on WSNs to collect sensory data for cloud clients, since the data requests of mobile users generally require being responded in real-time. However, these MCC and WSNs integration schemes ignore the following two observations: 1) the specific data cloud clients request usually depends on the current location of cloud clients 2) most sensors are usually equipped with non-rechargeable batteries with limited energy. In this paper, motivated by the above two issues, we present two novel collaborative location-based sleep scheduling (CLSS) schemes for WSNs to integrate with MCC. Based on the location of mobile user, CLSS dynamically determines the awake or asleep status of each sensor node to save energy consumption of WSNs. Theoretical and simulation results show that the proposed scheme can achieve a prolonged network lifetime of WSNs while still satisfy the data requests of mobile users.