학술논문

Density, distance and energy based clustering algorithm for data aggregation in wireless sensor networks
Document Type
Conference
Source
2017 IEEE/CIC International Conference on Communications in China (ICCC) Communications in China (ICCC), 2017 IEEE/CIC International Conference on. :1-5 Oct, 2017
Subject
Aerospace
Bioengineering
Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Computing and Processing
Engineering Profession
Fields, Waves and Electromagnetics
General Topics for Engineers
Photonics and Electrooptics
Power, Energy and Industry Applications
Robotics and Control Systems
Signal Processing and Analysis
Transportation
Wireless sensor networks
Clustering algorithms
Protocols
Load management
Monitoring
Energy consumption
Relays
Language
Abstract
Wireless sensor networks (WSNs) are wireless networks which consist of distributed sensor nodes monitoring physical and environmental conditions. Due to the energy limit of sensor nodes, prolonging lifetime of wireless sensor networks (WSNs) is a big challenge. In this paper, we propose a new clustering method called Density, Distance and Energy based Clustering (DDEC) to improve network performance. DDEC partitions the network into clusters with similar member number, so as to achieve load balancing. Then a cluster head is selected for each cluster based on three criteria: residual energy, distance and density, which achieves to minimize intra-communication cost and prolong cluster lifetime. In our performance analysis, we compare DDEC with another clustering method called DDCHS. The results show that DDEC outperforms DDCHS in terms of alive node number and energy consumption.