TA-FSFT Thermal Aware Fail Safe Fault Tolerant algorithm for Wireless Body Sensor Network

Abstract

Availability of data from network has become mandatory for monitoring patient during critical conditions. Fault tolerant strategy requires availability of nodes during critical conditions and it should be thermal aware in nature. Thermal Aware-Fail Safe Fault Tolerant (TA-FSFT) algorithm serves as a solution to this problem forming fault tolerant, energy efficient network for Wireless Body Sensor Network. The lifetime enhancement by fault tolerant method is proposed by classifying the packets based on the subject's status, scheduling sensors and routing based on the residual energy of the node. The data from the sensor is used to classify the patient state. The Markov model helps in predicting the state of the subject and scheduling sensors based on its state. Minimizing the energy consumption of the node minimizes heat dissipation caused by the sensors, thereby making TA-FSFT algorithm thermal aware in nature. Simulation results of TA-FSFT algorithm outperform with 1.519 times increase in lifetime and 1.453 times increase in throughput. TA-FSFT algorithm decreases thermal dissipation avoiding tissue damage by implanted node and provides a thermal aware fault tolerant mechanism to the system. Unnecessary energy dissipation and heat dissipation of nodes is avoided thereby it is made fail safe. Under some intermittent fault conditions the node shares data to the sink via the healthy node ensuring the data connectivity during above normal and abnormal conditions. The network is ensured for close monitoring under extreme situation with fail safe and fault tolerant manner.