Sleep scheduling with load balancing in sensor-cloud based on mobile user location

The mobile cloud computing (MCC) with wireless sensor networks (WSNs) technology gets a more attraction by researchers, because its combines the data gathering ability of sensors with the data processing capacity of the cloud. This new approach overcomes the limitation of data storage capacity and computational ability of sensor nodes. Finally, the stored data are sent to the mobile users when the user sends the request. The most of the integrated sensor-cloud schemes fail to observe the following criteria: 1) The mobile users request the specific data to the cloud based on their present location 2) One of the predominant issues in WSN is power consumption since most of them are equipped with non-rechargeable batteries. Mostly the sensors are deployed in hazardous and remote areas. This paper focuses on above observations and introduces the novel approaches known as collaborative location-based sleep scheduling (CLSS) schemes. Both awake and asleep status of each sensor node dynamically devised by schedulers and the scheduling is done purely based on the of mobile users current location with load balancing; in this manner, the performance of WSN is increased.