A Combination of K-means Algorithm and Optimal Path Selection Method for Lifetime Extension in Wireless Sensor Networks

Jlassi, Wadii; Haddad, Rim; Bouallègue, Ridha; Shubair, Raed M.

doi:10.1007/978-3-030-75078-7_42

Cited by 4 publications

(4 citation statements)

References 9 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Then, we compare the proposed algorithm with [22,23,27,17,25] algorithms under different scenarios to validate the network performance. For comparison, we use the metrics used in [28] and MATLAB R2016a as the simulator. We consider a network of 200 sensor nodes in an area of 200 m × 200 m. Sensor nodes have random uniform distribution, are placed in a fixed point with a unique identifier.…”

Section: Simulation and Analysis Of Resultsmentioning

confidence: 99%

“…The energy of sensor nodes is almost entirely consumed while transmitting, receiving packets, and processing data. The energy model used is the same one used in [28], which defines the following possibilities: free and multipath space. The quantity of energy depleted for forwarding and receiving k-bit packets is given respectively by ( 1), ( 2):…”

Section: Power Analysismentioning

confidence: 99%

See 1 more Smart Citation

Energy-Efficient Path Construction for Data Gathering Using Mobile Data Collectors in Wireless Sensor Networks

Jlassi,

Haddad,

Bouallegue

2023

RADIOENGINEERING

View full text Add to dashboard Cite

Energy is seen as a significant factor in wireless sensor networks (WSNs). It is a challenge to balance between battery lifetime of the different sensors and network lifetime. The main contribution of the proposed approach is to decrease the energy consumption of each sensor node, overcome unbalanced energy usage among sensor nodes, reduce the data gathering time and enhance the network lifetime. To achieve these goals, we combine the Hierarchical Agglomerative algorithm and an optimal path selection method. First, the suitable cluster heads (CHs) are elected based on the Euclidean distance and the residual energy of each sensor node. Then, the base station is situated at the center of the field, which will be partitioned into equal subareas, one for every mobile data collector (MDC). Second, the Kruskal algorithm is used to create an optimal data gathering path from each subset of elected cluster heads. Finally, each mobile data collector travels the optimal path to collect the data from the set of cluster heads of each subarea and returns periodically to the base station to upload gathered data. Computer simulation proves that the proposed approach outperforms existing ones in terms of data gathering time, residual energy and network lifetime.

show abstract

Section: Simulation and Analysis Of Resultsmentioning

confidence: 99%

Section: Power Analysismentioning

confidence: 99%

Energy-Efficient Path Construction for Data Gathering Using Mobile Data Collectors in Wireless Sensor Networks

Jlassi,

Haddad,

Bouallegue

2023

RADIOENGINEERING

View full text Add to dashboard Cite

show abstract

“…Lifetime of Wireless Sensor Network can be extended using a combination of K-Means algorithm and an Optimal Path Selection Method [15]. Firstly, centre of each cluster is chosen as a data-gathering location using the K-Means method.…”

Section: Related Workmentioning

confidence: 99%

K-Means and Fuzzy based Hybrid Clustering Algorithm for WSN

Angadi,

Kakkasageri

2023

International Journal of Electronics and Telecommunications

View full text Add to dashboard Cite

Wireless Sensor Networks (WSN) acquired a lot of attention due to their widespread use in monitoring hostile environments, critical surveillance and security applications. In these applications, usage of wireless terminals also has grown significantly. Grouping of Sensor Nodes (SN) is called clustering and these sensor nodes are burdened by the exchange of messages caused due to successive and recurring re-clustering, which results in power loss. Since most of the SNs are fitted with nonrechargeable batteries, currently researchers have been concentrating their efforts on enhancing the longevity of these nodes. For battery constrained WSN concerns, the clustering mechanism has emerged as a desirable subject since it is predominantly good at conserving the resources especially energy for network activities. This proposed work addresses the problem of load balancing and Cluster Head (CH) selection in cluster with minimum energy expenditure. So here, we propose hybrid method in which cluster formation is done using unsupervised machine learning based kmeans algorithm and Fuzzy-logic approach for CH selection.

show abstract

“…The quantity of energy in sensor nodes is almost entirely consumed while transmitting, receiving packets and processing data. The energy model used is the same one used in [28]. As defined in this model, there are two possibilities: the free and the multi-path (MP) space.…”

Section: Energy Modelmentioning

confidence: 99%

Increase of the Lifetime of Wireless Sensor Network using Clustering Algorithm and Optimal Path Selection Method

Jlassi¹,

Haddad²,

Bouallegue³

et al. 2022

RADIOENGINEERING

View full text Add to dashboard Cite

By the recent improvement of the internet of things (IoT), the need to implement wireless networks is increasing. It is a challenge to balance between battery lifetime of the different sensors and network lifetime. Many studies proved the importance of using clustering and Mobile Data Collectors (MDCs) to extend the operating time of sensor nodes. A mobile data collector is used to gather the data recorded by the nodes over a short transmission range. The proposed approach aims to decrease the energy consumption of each sensor node by using the Genetic Algorithm (GA) and mobile data collector. So, we suggest a clustering algorithm to find suitable Cluster Heads and form clusters. Then, we employ the genetic algorithm to construct an optimal data gathering path for MDC. Computer simulation proves that the proposed approach outperforms existing ones.

show abstract

A Combination of K-means Algorithm and Optimal Path Selection Method for Lifetime Extension in Wireless Sensor Networks

Cited by 4 publications

References 9 publications

Energy-Efficient Path Construction for Data Gathering Using Mobile Data Collectors in Wireless Sensor Networks

Energy-Efficient Path Construction for Data Gathering Using Mobile Data Collectors in Wireless Sensor Networks

K-Means and Fuzzy based Hybrid Clustering Algorithm for WSN

Increase of the Lifetime of Wireless Sensor Network using Clustering Algorithm and Optimal Path Selection Method

Contact Info

Product

Resources

About