Predator–prey optimization based clustering algorithm for wireless sensor networks

Panag, Tripatjot Singh; Dhillon, J.S.

doi:10.1007/s00521-020-05639-3

Cited by 10 publications

(4 citation statements)

References 70 publications

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“…The PPO algorithm selects the optimal pair of cluster leaders for each cluster and figures out the most efficient communication path between them, which may include many relay nodes. The optimization technique seeks to minimize data collecting and transmission costs while maintaining a constant energy budget for all wireless sensor nodes [24]m. We employed energy data, neighbor CH, neighbor info, neighbor status, and base station distance in this work.…”

Section: Related Workmentioning

confidence: 99%

A Systematic Study of Clustering Techniques for Energy Efficiency in Wireless Sensor Networks

Mutar¹,

Hammood²,

Hashem³

2023

IJCDS

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Recent advances in wireless sensor networks (WSNs) may be attributed to their increased accuracy and speed while gathering data, wireless communication, and data computation. Small, low-power sensor nodes present in these networks organize and set themselves up to do the activities that they are designed for. WSNs benefits are economical, simple to set up, adaptable, and efficient. However, there are some issues with longevity of networks and low energy consumption. By grouping nodes into a small number of clusters and choosing a cluster head (CH) to oversee data aggregation and transmission to the base station (BS), clustering has shown to be the most effective method for dealing with the difficulties of WSNs. Nevertheless, the insufficient CH selection and cluster construction methods, there are still a lot of challenges, including energy hole and isolated node difficulties. To learn more about this topic of how certain authors approach the aforementioned issues, we conducted an in-depth study of several meta-heuristic and non-heuristic approaches used in networks in a wide range of environments to choose CH and cluster creation, which are discussed in this paper.

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Section: Related Workmentioning

confidence: 99%

A Systematic Study of Clustering Techniques for Energy Efficiency in Wireless Sensor Networks

Mutar¹,

Hammood²,

Hashem³

2023

IJCDS

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“…This methodology presents better results than other popular techniques such as LEACH and GA for reducing packet loss and prolonging the network lifetime. (Panag et al, 2021) has presented a predator-prey optimization for identifying the cluster head and performs the routing. This method is mainly used to identify the optimal communication path for reducing energy consumption and delivering the number of packets to the base station.…”

Section: Problem Definition and Scopementioning

confidence: 99%

Hybrid Bacteria Foraging Algorithm With PSO and DE Algorithm for Optimal Cluster Head Selection in Wireless Sensor Networks

Bose

2022

International Journal of Cognitive Informatics and Natural Intelligence

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Network lifetime and energy constraint are the main issues for the applications of Wireless Sensor Network. Sensor nodes spend more energy in the communication process and affect the network lifetime. Clustering is the technique for choosing the optimal cluster head from the clusters. LEACH-C is the clustering protocol in WSN. BFA is applied in the LEACH-C protocol to form the optimal clusters. This optimization obtains more number of steps in the tumbling process and reaches the global optimum solution very slowly. This method directly affects the network lifetime. The above limitations are overcome by introducing the hybrid approach of Bacteria foraging algorithm by integrating the PSO and DE is applied in LEACH-C algorithm for finding the optimal cluster head. The best foraging solution utilized in the chemotactic behavior of the bacterium by using PSO and DE algorithm. The proposed methodology increases by 66% and 77% of the alive nodes when compared to FA and BFPSO.

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“…Routing issue is overcome by ACO and total live nodes issue is addressed by PSO algorithm [6]. The meta-heuristic algorithms may be implemented in an efficient manner on the basis of this work.…”

Section: Literature Surveymentioning

confidence: 99%

“…A group of nodes in similar networks can cover a large area. In order to transmit the gathered information from the sensor nodes to the sink nodes, performing a one-hop or direct communication is not possible [6]. There is an inconsistency in the distances between multiple nodes.…”

Section: Introductionmentioning

confidence: 99%

Optimized Wireless Sensor Node Multidimensional Routing using Fuzzy Clustering and Chaotic Gravitational Search Algorithm

Sivaganesan¹

2021

JSWS

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A network of tiny sensors located at various regions for sensing and transmitting information is termed as wireless sensor networks. The information from multiple network nodes reach the destination node or the base station where data processing is performed. In larger search spaces, the clustering mechanisms and routing solutions provided by the existing heuristic algorithms are often inefficient. The sensor node resources are depleted by un-optimized processes created by reduced routing and clustering optimization levels in large search spaces. Chaotic Gravitational Search Algorithm and Fuzzy based clustering schemes are used to overcome the limitations and challenges of the conventional routing systems. This enables effective routing and efficient clustering in large search spaces. In each cluster, among the available nodes, appropriate node is selected as the cluster head. Reduction in delay, increase in energy consumption, increase in network lifetime and improvement of the network clustering accuracy are evident from the simulation results.

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Predator–prey optimization based clustering algorithm for wireless sensor networks

Cited by 10 publications

References 70 publications

A Systematic Study of Clustering Techniques for Energy Efficiency in Wireless Sensor Networks

A Systematic Study of Clustering Techniques for Energy Efficiency in Wireless Sensor Networks

Hybrid Bacteria Foraging Algorithm With PSO and DE Algorithm for Optimal Cluster Head Selection in Wireless Sensor Networks

Optimized Wireless Sensor Node Multidimensional Routing using Fuzzy Clustering and Chaotic Gravitational Search Algorithm

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