Some WSN by a lot of immobile node and with the limited energy and without further charge of energy. Whereas extension of many sensor nodes and their operation. Hence it is normal.unactive nodes miss their communication in network, hence split the network. For avoidance split of network, we proposed a fault recovery corrupted node and Self Healing is necessary. In this Thesis, we design techniques to maintain the cluster structure in the event of failures caused by energy-drained nodes. Initially, node with the maximum residual energy in a cluster becomes cluster heed and node with the second maximum residual energy becomes secondary cluster heed. Later on, selection of cluster heed and secondary cluster heed will be based on available residual energy. We use Matlab software as simulation platform quantities. like, energy consumption at cluster and number of clusters is computed in evaluation of proposed algorithm. Eventually we evaluated and compare this proposed method against previous method and we demonstrate our model is better optimization than other method such as Venkataraman, in energy consumption rate. Recent advances in MEMS (Micro-electro-mechanical systems) and wireless network technology have made the development of small, inexpensive, low power distributed devices, which are capable of local processing and wireless communication, a reality. Such devices are called sensor nodes. Sensors provide an easy solution to those applications that are based in the inhospitable and low maintenance areas where conventional approaches prove to be impossible and very costly. Sensors are generally equipped with limited data processing and communication capabilities and are usually deployed in an ad-hoc manner to in an area of interest to monitor events and gather data about the environment. Examples include environmental monitoring- which involves monitoring air soil and water, condition based maintenance, habitat monitoring, seismic detection, military surveillance, inventory tracking, smart spaces etc. Sensor nodes are typically disposable and expected to last until their energy drains. Therefore, it is vital to manage energy wisely in order to extend the life of the sensors for the duration of a particular task. (1-6). Failures in sensor networks due to energy depletion are continuous and may increase. This often results in scenarios where a certain part of the network become energy constrained and stop operating after sometime. Sensor nodes failure may cause connectivity loss and in some cases network partitioning. In clustered networks, it creates holes in the network topology and disconnects the clusters, thereby causing data loss and connectivity loss (10). Good numbers of fault tolerance solutions are available but they are limited at different levels. Existing approaches are based on hardware faults and consider hardware components malfunctioning only. Some assume that system software's are already fault tolerant as in (7, 8). Some are solely focused on fault detection and do not provide any recovery
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