LAUSR.org creates dashboard-style pages of related content for over 1.5 million academic articles. Sign Up to like articles & get recommendations!

A Novel Energy-Aware Clustering Method via Lion Pride Optimizer Algorithm (LPO) and Fuzzy Logic in Wireless Sensor Networks (WSNs)

Photo from wikipedia

Recent technological advances and developments in the field of communication information systems, especially in microelectro mechanical systems have provided the ground for the production and setup of small nodes which… Click to show full abstract

Recent technological advances and developments in the field of communication information systems, especially in microelectro mechanical systems have provided the ground for the production and setup of small nodes which are supplied with batteries with limited batteries. These nodes have wireless communications with each other. A WSN includes a large number of sensor nodes which are located densely or scatteredly within a phenomenon or with a little distance from it. However, it should be noted that sensor nodes have low computational capability, little storage space and limited battery power. Due to resource limitations, a compromise should be made between processing precision and power optimization in WSNs. In this paper, using LPO algorithm and fuzzy logic, we proposed a novel energy-aware clustering method which lightweight and has relatively high precision. In the proposed method, clustering is done according to two main parameters, i.e. node’s remaining energy and distance from the sink. The results of simulating the proposed method via OPNET 11.5 revealed that the proposed method contributed to the reduction of average delay, input packet, power consumption and enhanced network lifetime.

Keywords: method; aware clustering; energy; novel energy; energy aware; fuzzy logic

Journal Title: Wireless Personal Communications
Year Published: 2019

Link to full text (if available)


Share on Social Media:                               Sign Up to like & get
recommendations!

Related content

More Information              News              Social Media              Video              Recommended



                Click one of the above tabs to view related content.