Abstract
Clustering in wireless sensor networks plays a vital role in solving energy and scalability issues. Although multiple deployment structures and cluster shapes have been implemented, they sometimes fail to produce the expected outcomes owing to different geographical area shapes. This paper proposes a clustering algorithm with a complex deployment structure called radial-shaped clustering (RSC). The deployment structure is divided into multiple virtual concentric rings, and each ring is further divided into sectors called clusters. The node closest to the midpoint of each sector is selected as the cluster head. Each sector’s data are aggregated and forwarded to the sink node through angular inclination routing. We experimented and compared the proposed RSC performance against that of the existing fan-shaped clustering algorithm. Experimental results reveal that RSC outperforms the existing algorithm in scalability and network lifetime for large-scale sensor deployments.
Highlights
In most applications, sensors are used on a large scale to improve reliability and efficiency.A wireless sensor network (WSN) comprises a large number of sensor nodes with sensing and communication capabilities
Clustering and routing are the fundamental processes in WSNs, and subsequent improvements have been made to the LEACH protocol
The researchers propose an angular inclination-based clustering system to address the challenges of fan-shaped clusters (FSCs), which grabs attention in the high-volume deployment of sensor networks
Summary
Sensors are used on a large scale to improve reliability and efficiency. In a network of sensor nodes, clustering techniques are used for data collection, where sensor nodes are grouped into clusters for the conservation of energy [7]. Clustering, based on the size and shape of the deployment area, is a method adopted commonly to collect and transmit data to reduce energy consumption considerably. The security of sensor nodes and the data collected from the sensors that has to be transmitted securely to the sink or another network is another challenging issue, in addition to the deployment structure and cluster optimization. To determine the shape of the deployment area and the coverage range based on the network area to ensure that no node is left unattended and to select the CH with energy optimization to achieve a balanced WSN with minimal energy requirements
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