LAUSR

Energy conservation is a challenging concern with the growing advancement in wireless technologies and is currently one of the attractive issues among researchers working in the Internet of Things (IoT) domain. In this paper, we address this issue by devising a dynamic sensor activation algorithm inspired by the popular PageRank algorithm called SensorRank. Unlike PageRank algorithm which only requires the outlinks to rank webpages, SensorRank, on the other hand, dynamically analyses the network topology in terms of relative distances and link qualities between devices and the remaining energies of the devices, based on which the sensors are ranked. An optimal subset of sensors are activated that take part in data fusion and the inactivated sensor data are regenerated with the help of compressing sensing technique. A quantitative study in terms of average energy gain is performed which shows an energy saving of up to 42% and a lifetime enhancement of up to 89% achieved through our proposed approach. Furthermore, comparison of SensorRank with random activation of sensors reveal that there is an overall lifetime enhancement of 34.68% with our proposed activation scheme.