Distributed and energy efficient selforganization for onoff wireless sensor networks In this paper, we utilize clustering to achieve energy efficiency for the onxe2x80x93off wireless sensor network, whose member nodes alternate between active and inactive states. In the proposed Distributed and Energy Efficient Self Organization (DEESO) scheme, the head election is adjusted adaptively to the remaining battery levels of local active nodes, which is a completely distributed approach compared to LEACH that relying on other routing schemes to access global information. Furthermore, we apply the Adaptive Channel Assignment (ACA) to address the onoff topology changes. Simulation results show that DEESO delivers 184% amount of data to the base station as LEACH for the same amount of energy consumption and the effective network lifetime is extended by around 50%.

Clusterhead Selection Algorithm Based on Energy and Mobility in Wireless Mobile Sensor Networks Wireless Sensor Networks WSN are selforganizing networks composed of numerous sensor nodes dispersed in an environment communicating by radio technologies. These nodes have limited processing capacity with reduced energy and a mobility dependency. One of the biggest problems in these networks is maximizing the lifetime of the nodes, due to the lack of fixed infrastructure and centralized management. For this purpose, authors proposed the clustering technique to facilitate communication and minimize control traffic. In this paper, we propose a new clusterhead election algorithm in mobile sensor networks based on local information of sensor nodes: residual energy and mobility, supporting network selforganization to avoid isolated node and high blocking probabilities.