Distance-based Cluster Head Election for Mobile Sensing
Ruairí de Fréin, Liam O'Farrell · 2018
Energy-efficient, fair, stochastic leader-selection algorithms are designed for mobile sensing scenarios which adapt the sensing strategy depending on the mobile sensing topology. Methods for electing a cluster head are crucially important when optimizing the trade-off between the number of peer-to-peer interactions between mobiles and client-server interactions with a cloud-hosted application server. The battery-life of mobile devices is a crucial constraint facing application developers who are looking to use the convergence of mobile computing and cloud computing to perform environmental sensing. We exploit the mobile network topology, specifically the location of mobiles with respect to the gateway device, to stochastically elect a cluster head so that (1) different energy saving policies can be implemented and (2) battery lifetime is increased given an energy efficiency policy, in a fair way. We demonstrate that the battery usage can be made more fair by reducing the difference in battery life-time of mobiles by up to 66%.