Optimal Route Evaluation Method Based on Principal Component Analysis for Wireless Sensor Networks

A novel optimal route evaluation method based on principal component analysis (OREPCA) is proposed to solve the transmission route sequencing problem appeared in the optimality evaluation process of wireless sensor networks. Sample routes information is firstly collected in a discrete time domain by using an ant colony algorithm. Then, a relevant evaluation index system of routes is constructed based on the deployment environment of the network, and a positive dimensionless method is given and is applied to the indicators of the set. The priority of all indicators is used to score each sample route and to obtain a vector of evaluation indicators. Finally, a correlation coefficient matrix among different indicators in the vector is calculated, and the principal component approach is used to obtain a route evaluation function and the weighting factor of each evaluation indicator in the function. The algorithm avoids the problem of subjective randomness caused by manually selecting weighting factors based on experience. Moreover, the evaluation function generated by the proposed method achieves the diversified evaluation and prompts dynamic server load balance in different monitoring environments. Comparisons with the multi-objective routing algorithm and the cluster based route optimisation and load balancing protocol, OREPCA can increase the lifetime of network by 14% and put down the delay of communication notably. © 2017, Editorial Office of Journal of Xi'an Jiaotong University. All right reserved.