Energy Consumption Model of WSN Based on Manifold Learning Algorithm

Abstract

Energy saving is one of the most important issues in wireless sensor networks. In order to effectively model the energy consumption -in wireless sensor network, a novel model is proposed based on manifold learning algorithm. Firstly, the components of the energy consumption by computational equations are measured, and the objective function is optimized. Secondly, the parameters in computational equations are estimated by manifold learning algorithm. Finally, the simulation experiments on OPNET and MATLAB Simulink are performed to evaluate the key factors influencing the model. The experimental results show that the proposed model had significant advantage in terms of synchronization accuracy and residual energy in comparison with other methods.

An Energy Efficient and Trust-based Quality of Service Routing in Mobile Adhoc Networks

“…If the node with a high priority forwards the data, the node with a low priority will discard the monitored data packets, thereby reducing the possibility of wasting node energy. The segment routing method designed by AsOR minimizes the average energy consumption by selecting the optimal number of nodes in the segment [10]; however, AsOR optimizes energy consumption from a global perspective and belongs to a centralized routing algorithm. CBEEOR proposed by Karyakarte, et al [11], is an improved algorithm based on the adjustable transmission energy model in EEOR, and calculates the forwarding energy by allowing multiple nodes to forward packets at the same time.…”