Node density control is one of the most important measures to save energy consumption in large Wireless Sensor Networks (WSNs), and it aims to minimize the number of on-duty nodes when maintaining the original network coverage. In this paper, CPSBC, a coveragepreserving self-scheduling protocol is proposed. CPSBC is based on a new sensing model--Cooperative Sensing Model (CSM) other than traditional Boolean Sensing Model (BSM), and multi-sensors' cooperative exploration is considered in it. With CPSBC, sensor nodes that have minimum contribution on coverage and satisfy Coverage Preserving Rule meanwhile will be scheduled to fall in asleep in each round. It has been verified by simulation that CPSBC can keep the original network coverage with less on-duty nodes than BSM mechanisms, thus results in higher energy efficiency.

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lxwandxf con,v163cor, yumax(sohucor and huhing 63con Abstract Energy balancing routing (EBR) is an efficient strategy to prolong the lifetime of wireless sensor networks (WSNs). In this paper, the network lifetime of minimum energy routing (MER) and energy balancing routing of multihop multi-to-one WSN is analyzed. A localized energy balancing routing (LEBR) algorithm is proposed. LEBR combines power control with routing based on geographical location information. LEBR utilizes local energy balancing to achieve global energy balancing, and it is a distributed and localized energy balancing strategy. The performance of LEBR is simulated and analyzed, and is compared with MER. The result shows that the performance of LEBR is better than MER, and it prolongs network lifetime efficiently.

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Coverage and energy efficiency are two important concerns in wireless sensor networks. In this paper, a coverage and energy efficient (CEE) task assigning strategy is presented. The basic idea of CEE is to assign tasks according to node's coverage degree and remaining energy. Based on this idea, grid-based coverage and energy efficient (GCEE) information gathering protocol is designed. GCEE is simulated with NS-2. How the various parameters affect the fraction of the survived nodes and the area energy balancing of the network is shown in simulation results.