A Smart Energy Efficient Scheme for Dynamic Clustering in Wireless Sensor Network using Neural Networks
نویسندگان
چکیده
Wireless Sensor Networks (WSN) consists of large number of sensor nodes. The sensor nodes are battery powered devices, they communicate over a wireless medium and consumes energy during data transmission. In the past years various techniques have been proposed to reduce the battery consumption of wireless sensor networks. The previous approaches are based on the static clustering which follow the rules of LLC algorithm. In this paper, novel technique is been implemented which is based on the Dynamic clustering. The Cluster heads in each cluster have changed according to the network conditions. Dynamic clustering is being proposed in this paper which is based on the neural networks. The proposed technique is implemented in NS2 and simulation results show that novel technique will reduce network overhead and increase network lifetime.
منابع مشابه
Multi-layer Clustering Topology Design in Densely Deployed Wireless Sensor Network using Evolutionary Algorithms
Due to the resource constraint and dynamic parameters, reducing energy consumption became the most important issues of wireless sensor networks topology design. All proposed hierarchy methods cluster a WSN in different cluster layers in one step of evolutionary algorithm usage with complicated parameters which may lead to reducing efficiency and performance. In fact, in WSNs topology, increasin...
متن کاملAn Efficient Cluster Head Selection Algorithm for Wireless Sensor Networks Using Fuzzy Inference Systems
An efficient cluster head selection algorithm in wireless sensor networks is proposed in this paper. The implementation of the proposed algorithm can improve energy which allows the structured representation of a network topology. According to the residual energy, number of the neighbors, and the centrality of each node, the algorithm uses Fuzzy Inference Systems to select cluster head. The alg...
متن کاملA New Method for Clustering Wireless Sensor Networks to Improve the Energy Consumption
Clustering is an effective approach for managing nodes in Wireless Sensor Network (WSN). A new method of clustering mechanism with using Binary Gravitational Search Algorithm (BGSA) in WSN, is proposed in this paper to improve the energy consumption of the sensor nodes. Reducing the energy consumption of sensors in WSNs is the objective of this paper that is through selecting the sub optimum se...
متن کاملImproving Energy Consumption by Using Cluster Based Routing Algorithm in Wireless Sensor Networks
Multi-path is favorite alternative for sensor networks, as it provides an easy mechanism to distributetraffic, as well as considerate fault tolerance. In this paper, a new clustering based multi path routingprotocol namely ECRR (Energy efficient Cluster based Routing algorithm for improving Reliability) isproposed, which is a new routing algorithm and guarantees the achievement to required QoS ...
متن کاملHybrid Bio-Inspired Clustering Algorithm for Energy Efficient Wireless Sensor Networks
In order to achieve the sensing, communication and processing tasks of Wireless Sensor Networks, an energy-efficient routing protocol is required to manage the dissipated energy of the network and to minimalize the traffic and the overhead during the data transmission stages. Clustering is the most common technique to balance energy consumption amongst all sensor nodes throughout the network. I...
متن کاملAn Energy Efficient Clustering Method using Bat Algorithm and Mobile Sink in Wireless Sensor Networks
Wireless sensor networks (WSNs) consist of sensor nodes with limited energy. Energy efficiency is an important issue in WSNs as the sensor nodes are deployed in rugged and non-care areas and consume a lot of energy to send data to the central station or sink if they want to communicate directly with the sink. Recently, the IEEE 802.15.4 protocol is employed as a low-power, low-cost, and low rat...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2015