A Multihop Clustering Algorithm for Energy Saving in Wireless Sensor Networks

One of the important problems for wireless sensor networks is increasing the network lifetime. Clustering is an efficient technique for prolonging the lifetime of wireless sensor networks. This papers propose a multihop clustering algorithm (MHC) for energy saving in wireless sensor networks. MHC selects the clusterheads according to the two parameters the remaining energy and node degree. Also cluster heads select their members according to the two parameters of sensor the remaining energy and the distance to its cluster head. MHC is done in three phases quickly. Simulation results show that the proposed algorithm increases the network lifetime more than 16 percent compared of the LEACH protocol. 1. Introduction Along recent advances in microsensors, VLSI technologies, and wireless communication fields, another kind of wireless network named wireless sensor networks (WSN) has been appeared. The sensor networks can be used for various application areas (e.g., health, military, and home) [1]. For different application areas, there are different technical issues that researchers are currently resolving. A sensor network is composed of a large number of sensor nodes that are densely deployed either inside the phenomenon or very close to it [1]. They are usually made up with wireless sensor nodes, small, cheap, and resource-limited devices sensing the environment and Communicating with each other [2]. Wireless distributed microsensor systems will enable the reliable monitoring of a variety of environments for both civil and military applications. For example, for a security system, acoustic, seismic, and video sensors can be used to form an ad hoc network to detect intrusions. Microsensors can also be used to monitor machines for fault detection and diagnosis. communication between the sensor nodes and the base station is expensive, and there are no high-energy nodes through which communication can proceed. Reliable environment monitoring is important in a variety of commercial and military applications [3]. These networks have many limits in the network lifetime such as processing power, memory, and transmitter power. Energy conservation has been identified as the key challenge in the design and operation of these networks. Dense positioning of sensor nodes can improve network connectivity and fault tolerance; the main drawback of such deployment is obvious: data collected by neighboring nodes is highly spatially corelated. Hence, if the raw sensor readings are to be sent to the sink, considerable amount of redundant data would have to be communicated