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Objective: The main objective of assigning tasks among sensor nodes in wireless sensor network environment is to recuperate the information loss due to network failures and to increase the network life time. Methods: The consummate way for downsizing energy consumption among nodes is to assign the task in an efficacious manner. The renovated version of Binary Particle Swarm Optimization (BPSO) is employed for assigning tasks in WSN. If any task assigned sensor node does not perform its operations, then those are considered as vulnerable nodes which can be pruned away from the network to avoid network failures. Results: In this paper, task assignment, information recuperation and topology permutation are proposed for improving the permanency of the sensor network. The task assignment problem for data recuperation was implemented in TCL language on NS2 running under windows environment. To gauge the adequacy and viability of this framework, results are compared with a technique that does not involve data recovery in its implementation. In the proposed system, the calculated execution time subtracts the execution time of the vulnerable sensor node. Subsequently, it minimizes the general execution time and improves the network performance and lifetime relies on upon fluctuating network size and tasks. Thus, the overall lifetime of the WSN and also fault tolerance level of the WSN is augmented. Conclusion: Task execution time, energy utilization and sensor network lifetime are considered in the fitness function to make a legitimate tradeoff among distinctive metrics and get the best overall executionin the fitness function to make a legitimate tradeoff among distinctive metrics and get the best overall execution.

Keywords

Failure Detection, Information Recuperation, Particle Swarm Optimization, Task Assignment, Wireless Sensor Network
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