SENSOR NETWORK PERIODICAL DATA ASSEMBLY USING IMBALANCED CLUSTERING ENERGY EFFICIENT MECHANISM

Fast technical advances and development in wireless communication resulted in the huge consumption of wireless sensor networks. The nodes in these networks are ready to be sensed, processing the data and transmitting radio units. While several research works have been conducted related to the power-aware and energy-efficiency using Cooperative Networking protocol (CONET) that reforms clusters but the multiple rate remains to be explored. Due to the huge constraint in energy, the resources of sensor networks should be aimed at increasing the lifetime of sensors. This motivates us to seek a different way for severe energy constraint to overcome the limitations of the previous works by utilizing periodical data assembly in which energy efficiency and network scalability is achieved for inter-cluster communication using imbalanced clustering and multi hop routing. In this approach, ICEE focuses on two main strategies, attain efficiency in energy and increase scalability of network by making a cluster head choose a relay node accordingly to its residual energy and distance to base station. To start with first the focus is made on Imbalanced Clustering Energy Efficient (ICEE) mechanism for periodical data assembly where cluster heads are elected by localized competition in wireless sensor networks. The ICEE partitions enables the nodes into clusters of imbalanced size and clusters closer to the base station have lesser sizes than those farther away from the base station. The cluster heads nearer to the base station keep some energy for the data forwarding during inter-cluster. The implications of the research reveals that Imbalanced Cluster Energy Efficient mechanism ensures inter-cluster communication with the help of energy-aware multi hop routing protocol and not only decide on correct power level but also help to create clusters of imbalanced size. Numerical results measured in terms of communication energy, power consumption and cluster head probability ratio in wireless sensor network depict superior performance in comparison with CONET using ns2 simulator.