HEEL: A new clustering method to improve wireless sensor network lifetime

Abstract

In wireless sensor networks, some resources such as memory and energy are limited. In recent years, there has been an increasing interest in improving network lifetime. Node energy plays an important role in the network lifetime. Along with this remarkable growth in wireless sensor networks, however, there is an increasing concern over network lifetime. The principal purpose of this study is to develop an understanding of the effects of other parameters on selecting a cluster head. The methodological approach taken in this study is a mixed methodology typically based on the node's energy. The authors have operated four parameters to select the cluster head: Node energy, the energy of the node's neighbours, number of hops and number of links to neighbours. Each of these parameters has an impact in selecting the cluster head. They accurately observed hop size, energy of each sensor node, average energy of sensor neighbours, links to sensor nodes (HEEL) has better improvements in comparison of Node ranked Low Energy Adaptive Clustering Hierarchy (Nr-LEACH), Modified Low Energy Adaptive Clustering Hierarchy (ModLEACH), Low Energy Adaptive Clustering Hierarchy-B (LEACH-B), Low Energy Adaptive Clustering Hierarchy (LEACH), Power-Efficient Gathering in Sensor Information System (PEGASIS), energy-aware clustering scheme with transmission power control for sensor networks (EACLE) and hybrid energy efficient distributed clustering (HEED) algorithms in possible case of network lifetime and throughput.

Gaussian Regression Models for Evaluation of Network Lifetime and Cluster-Head Selection in Wireless Sensor Devices

“…Seyyedabbasi, A. et al [18], have developed an algorithm HEEL where the cluster head is selected based on node energy, the energy of node's neighbour, number of hops, and number of links to neighbours and shows improvement compared to Nr-LEACH, ModLEACH, LEACH-B, LEACH, PEGASIS energy-aware clustering scheme.…”

Cluster optimization in wireless sensor network based on optimized Artificial Bee Colony algorithm

“…Clustering is considered an effective methodology to date to ensure the proper use of energy in a single tier-network attribute. In clustered communication, single-tier attributes involve data aggregation and fusion to minimise the collision of packets along with redundancy [5][6][7]. LEACH is a prominent clustering hierarchy methodology that had been preferred [8].…”

Energy-Efficient Cluster Management Using a Mobile Charger for Solar-Powered Wireless Sensor Networks

“…Lastly, we explain several examples of the third method that select CHs, considering multiple factors, including the energy and location information. HEEL [ 27 ] selects CHs in consideration of four parameters per round: the node energy, energy of neighboring nodes, number of hops to a base station, and number of neighboring nodes. Each of these parameters has an impact in selecting the CH.…”

“…In the simulation, we compared the proposed scheme with other schemes, such as constructing clusters and finding the cluster heads (1) by considering the cohesion between the sensor nodes and the distance between the clusters(HSA-WSN) [ 13 ], (2) by taking only the energy into account (E-LEACH) [ 26 ], and (3) by considering multiple factors including its residual energy, number of hops to a base station, and number of neighboring nodes (HEEL) [ 27 ]. We deployed 400, 1000, and 1600 nodes in an area of 100 m × 100 m, and conducted experiments for 30 days of simulation time.…”