Improvements in LEACH based on K-means and Gauss algorithms

Elkamel, Rabiaa; Baccar, Noura; Cherif, Adnene

doi:10.1016/j.procs.2015.12.046

Cited by 22 publications

(20 citation statements)

References 5 publications

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“…Many studies have been conducted to evaluate the effect of K-Means on the LEACH protocol performance in WSN [1], [8]- [13]. Other studies, apply the Grid-sizes clustering on LEACH to enhance the WSNs performances as in [5], [8], [14], [15].…”

Section: Related Workmentioning

confidence: 99%

Enhancing QoS and Residual Energy by Using of Grid-Size Clustering, K-Means, and TSP Algorithms With MDC in LEACH Protocol

2022

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Some recent researches have shown that the energy consumption problem caused by data collection in a wireless sensor network (WSN) based on a static data collector is a main threat to the network lifetime. However, with the progress of the mobile terminal technology, the implementation of mobile data collectors (MDCs) has become more popular in large-scale WSNs, but it remains a big problem to improve the Quality of Service (QoS) criteria and minimize the energy consumption at the same time. However, most existing systems based on MDCs do not successfully strike a balance between routing energy consumption and QoS. In addition, most WSN protocols fail to maintain their impact when the network topology changes. Thus, for a dynamic WSN, it is important to support an intelligent MDC to continue data propagation despite the inevitable changes in the WSN topology. Considering all the above challenges, we propose a new intelligent MDC based on the traveling salesman problem (TSP) to determine the optimal path traveled by the MDC for energy efficiency and latency. Specifically, our proposed Mobile Data Collectors-Traveling Salesman Problem-Low Energy Adaptive Clustering Hierarchy-K-Means (MDC-TSP-LEACH-K) protocol uses K-Means and Grid clustering algorithm to decrease energy consumption in the cluster head (CH) election phase. Additionally, MDC is utilized as an intermediate between CH and the sink to further enhance the QoS of WSNs, to reduce delays while collecting data, and improve the transmission phase of the LEACH protocol.INDEX TERMS Energy consumption, large-scale wireless sensor networks, optimal path, QoS.

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Section: Related Workmentioning

confidence: 99%

Enhancing QoS and Residual Energy by Using of Grid-Size Clustering, K-Means, and TSP Algorithms With MDC in LEACH Protocol

2022

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“…The algorithm extends the network life by balancing the energy consumption of each node, but some nodes will produce ineffective energy consumption. In [11], an improved LEACH algorithm (LEACH-KM-GA) based on K-means clustering algorithm is proposed. This algorithm introduces the idea of K-means algorithm in the process of cluster head election, which can obtain more reasonable election results.…”

Section: Related Workmentioning

confidence: 99%

A Hierarchical Topology Control Algorithm for WSN, Considering Node Residual Energy and Lightening Cluster Head Burden Based on Affinity Propagation

Song

et al. 2019

Sensors

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The low energy adaptive clustering hierarchy (LEACH) is the classical hierarchical topology control algorithm and still widely used today in wireless sensor networks. There are some problems in LEACH such us an unreasonable selection and uneven distribution of cluster heads, not considering the residual energy of nodes, the cluster head is overloaded and there is a high energy consumption of data transmission. In this paper, a topology control algorithm with double cluster heads and multi-hop based on affinity propagation clustering (APDC-M) was proposed. In APDC-M, firstly, a cluster head election algorithm with double choices based on the affinity propagation clustering algorithm (AP) and reference node strategy (APDC) was proposed. APDC is responsible to elect the fusion cluster head for node clustering. Secondly, a forwarding cluster head is elected within each cluster. The forwarding cluster head is responsible for the data transmission in order to reduce the energy consumption of a single cluster head. Lastly, the forwarding cluster heads complete the data transmission from a cluster to the base station by the shortest path inter-cluster multi-hop mode. The comparison simulation results show that APDC-M can make the cluster head election more reasonable and the cluster head distribution more uniform, and effectively reduce the energy consumption of the cluster head nodes when transmitting data, thus prolonging the network life.

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“…The classification method based on k-means has been presented which is surveyed below. In [3,4] authors presented "a protocol that is a grouping of two practices k-means algorithm and Minimum Transmission Energy (MTE). The resulted practice has distance as a condition for choosing the nodes entitled to arrangement the cluster".…”

Section: Related Workmentioning

confidence: 99%

“…In [7,8] authors presented a better technique of CH selection based on minimum Euclidean distance to form the clusters and to find efficient cluster head. In [9,4] authors proposed an enhanced LEACH protocol that is based on the Elbow process is used to form the cluster and find to an optimal number of "k" by using the k-means algorithm. In [11,[14][15][16] authors presented distributed Clustering techniques and in [11,[17][18][19] authors presented centralized clustering technique.…”

Section: Related Workmentioning

confidence: 99%

Enhancement of the QoS Parameter of LEACH Protocol using Modified K -Means Algorithm

2019

IJRTE

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 Abstract: Wireless Sensor Network (WSN) is a collection of battery operated sensors deployed in the monitoring area. A massive quantity of energy of the nodes is used in the internal and external communications. There is a need of energy saving mechanism for effective and efficient communication. In this paper, we propose a new Modified-LEACH (MD-LEACH) protocol for enhancing the Quality of Services (QoS) parameters. This hierarchical routing protocol (MD-LEACH) is inspired by the k-means clustering technique to consolidate sensor networks into clusters and acquire an enhanced QoS parameter. The kmeans algorithm efforts to improve the clustering procedure of LEACH protocol using Euclidean distance and prolong the lifespan of the sensor network. This algorithm forms the optimized clusters by a distance of cluster head from cluster nodes and energy of the nodes for designated the cluster heads. To evaluate the performance of the proposed approach, we used NS-2 simulator, and consider the QoS parameter, namely: packet delivery ratio, energy consumption, bandwidth, and throughput. The simulations results show that the MD-LEACH algorithm outperforms then the LEACH protocol by optimizing all QoS parameters and improved network performance. Index Terms : cluster head-means algorithm, LEACH, MD-LEACH, QoS, and WSN.

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Improvements in LEACH based on K-means and Gauss algorithms

Cited by 22 publications

References 5 publications

Enhancing QoS and Residual Energy by Using of Grid-Size Clustering, K-Means, and TSP Algorithms With MDC in LEACH Protocol

Enhancing QoS and Residual Energy by Using of Grid-Size Clustering, K-Means, and TSP Algorithms With MDC in LEACH Protocol

A Hierarchical Topology Control Algorithm for WSN, Considering Node Residual Energy and Lightening Cluster Head Burden Based on Affinity Propagation

Enhancement of the QoS Parameter of LEACH Protocol using Modified K -Means Algorithm

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