Selecting Energy Efficient Cluster-Head Trajectories for Collaborative Mobile Sensing

We study the design of energy-efficient stochastic leader-selection algorithms in environments which are sensed by mobile handsets. This work optimizes the energy usage of the interaction between mobile handsets and an application server. The energy- efficiency of mobile handset communications is of increasing importance given the convergence of mobile computing and cloud computing. In some scenarios the unavailability of WiFi signals forces mobile devices to expend additional energy transmitting application specific sensed data over cellular networks. This paper focuses on 1) fairly allocating the overhead of transmitting sensed data to a cellular base station amongst the mobile devices by selecting a cluster-head (Fairness is measured in terms of the relative energy expended); 2) successively improving the location of the selected leader such that the efficiency of the entire system is improved; and finally, 3) allowing the mobile devices to gradually forget what they have learned so that the life-time of the mobile devices is increased (without significantly affecting energy savings). We present two algorithms in this paper and demonstrate that the battery life-time associated with sensor data transmissions of the mobile handsets may be increased by 20-40% without incurring a sensing accuracy penalty.