A comparative study of clusterhead selection algorithms in wireless sensor networks

In Wireless Sensor Network, sensor nodes life time is the most critical parameter. Many researches on these lifetime extension are motivated by LEACH scheme, which by allowing rotation of cluster head role among the sensor nodes tries to distribute the energy consumption over all nodes in the network. Selection of clusterhead for such rotation greatly affects the energy efficiency of the network. Different communication protocols and algorithms are investigated to find ways to reduce power consumption. In this paper brief survey is taken from many proposals, which suggests different clusterhead selection strategies and a global view is presented. Comparison of their costs of clusterhead selection in different rounds, transmission method and other effects like cluster formation, distribution of clusterheads and creation of clusters shows a need of a combined strategy for better results.Comment: 12 pages, 3 figures, 5 tables, Int JournaL, International Journal of Computer Science & Engineering Survey (IJCSES) Vol.2, No.4, November 201

Survey on Multi Agent Energy Efficient Clustering Algorithms in Wireless Sensor Networks

In the last few years, there are many applications for Wireless Sensor Networks (WSNs). One of the main drawbacks of these networks is the limited battery power of sensor nodes. There are many cases to reduce energy consumption in WSNs. One of them is clustering. Sensor nodes partitioned into the clusters so that one is chosen as Cluster Head (CH). Clustering and selection of the proper node as CH is very significant in reducing energy consumption and increasing network lifetime. In this paper, we have surveyed a multi agent clustering algorithms and compared on various parameters like cluster size, cluster count, clusters equality, parameters used in CHs selection, algorithm complexity, types of algorithm used in clustering, nodes location awareness, inter-cluster and intra-cluster topologies, nodes homogeneity and MAC layer communications

Wireless sensor network as a distribute database

Wireless sensor networks (WSN) have played a role in various fields. In-network data processing is one of the most important and challenging techniques as it affects the key features of WSNs, which are energy consumption, nodes life circles and network performance. In the form of in-network processing, an intermediate node or aggregator will fuse or aggregate sensor data, which are collected from a group of sensors before transferring to the base station. The advantage of this approach is to minimize the amount of information transferred due to lack of computational resources. This thesis introduces the development of a hybrid in-network data processing for WSNs to fulfil the WSNs constraints. An architecture for in-network data processing were proposed in clustering level, data compression level and data mining level. The Neighbour-aware Multipath Cluster Aggregation (NMCA) is designed in the clustering level, which combines cluster-based and multipath approaches to process different packet loss rates. The data compression schemes and Optimal Dynamic Huffman (ODH) algorithm compressed data in the cluster head for the compressed level. A semantic data mining for fire detection was designed for extracting information from the raw data by the semantic data-mining model is developed to improve data accuracy and extract the fire event in the simulation. A demo in-door location system with in-network data processing approach is built to test the performance of the energy reduction of our designed strategy. In conclusion, the added benefits that the technical work can provide for in-network data processing is discussed and specific contributions and future work are highlighted

Adaptive technique for energy management in wireless sensor networks. Development, simulation and evaluation of adaptive techniques for energy efficient routing protocols applied to cluster based wireless sensor networks.

Recently, wireless sensor networks have become one of the most exciting areas for research and development. However, sensor nodes are battery operated, thus the sensor¿s ability to perform its assigned tasks is limited by its battery capacity; therefore, energy efficiency is considered to be a key issue in designing WSN applications. Clustering has emerged as a useful mechanism for trade-off between certain design goal conflicts; the network life time, and the amount of data obtained. However, different sources of energy waste still exist. Furthermore, in such dynamic environments, different data rate requirements emerge due to the current network status, thus adapting a response to the changing network is essential, rather than following the same principle during the network¿s lifespan. This thesis presents dynamic techniques to adapt to network changes, through which the limited critical energy source can be wisely managed so that the WSN application can achieve its intended design goals. Two approaches have been taken to decreasing the energy use. The first approach is to develop two dynamic round time controllers, called the minimum round time controller MIN-RC and the variable round time controller VAR-RC, whereas the second approach improves intra-cluster communication using a Co-Cluster head; both approaches show better energy utilisation compared to traditional protocols. A third approach has been to develop a general hybrid protocol H-RC that can adapt different applications requirements; it can also tolerate different data rate requirements for the same application during the system¿s lifetime