Fault Tolerance and QoS based Pervasive Computing using Markov State Transition Model

Fault-tolerance is significant in pervasive computing environments. Recently, few research works has been developed for reducing the fault, occurring in pervasive computing. However, there is a need for a fault tolerance mechanism to reduce the link failures and unwanted mobile node access (in pervasive computing environment). In order to overcome these limitations, Markov State Transition Based Fault Tolerance (MST-FT) Model is proposed. The main objective of MST-FT Model is to achieve resource efficient QoS in pervasive computing environment by avoiding the link failures and unwanted mobile node usages. Initially, the optimization of link failures is achieved by maintaining Markov chain of high energy mobile nodes on the wireless network communication path. The mobile nodes with higher energy and minimal drain rate are combined to form a chain in its corresponding path of communication in order to minimize the link failures in pervasive computing. Next, the inappropriate mobile node usage is avoided by selecting only the authorized mobile nodes for Markov chain construction to effective network communication, which resulting in improved fault tolerant rate. Therefore, MST-FT Model provides higher resource efficient QoS as compared to existing works. The performance of MST-FT Model is measured in terms of fault tolerant rate, execution time, energy consumption rate and quality of service level. The simulation results show that the MST-FT Model is able to improve the fault tolerant rate by 13% and also reduces the energy consumption rate of resource efficient QoS by 25%, when compared to previous works.