TEO-MCRP: Thermal exchange optimization-based clustering routing protocol with a mobile sink for wireless sensor networks

Yalçın, Sercan; Erdem, Ebubekir

doi:10.1016/j.jksuci.2022.01.007

Cited by 24 publications

(31 citation statements)

References 39 publications

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“…At the primary stage, the nodes in the WSN are initialized and communicated together. Then, the HBAC technique was executed to cluster the network and elect CHs [16,17]. The Honey badger algorithm (HBA) is a new meta-heuristic technique presented by Hashim et al [16] dependent upon the hunting performance of honey badgers.…”

Section: Design Of Hbac Techniquementioning

confidence: 99%

“…The aim of HBAC objective function (OF) is to allocate the node with minimal cost as CH and fitness parameter is determined in the following [17]. The residual energy (RE) is the fitness parameter, F res .…”

Section: Design Of Hbac Techniquementioning

confidence: 99%

“…The presented technique comes as an original technique that newly brings together the global search capabilities of particle swarm optimization (PSO) technique, variance operator of differential technique, and pheromone of ant colony optimization (ACO) technique for avoiding local search and maintaining diversity of populations. In [15], a novel Mobile Clustering Routing Protocol (MCRP) dependent upon Thermal Exchange Optimization (TEO) simulated as Newton's cooling law is named as TEO-MCRP was projected for heterogeneous WSN. During the present protocol, 2 distinct techniques are presented for CH selective and MS way recognition with main function containing independent fitness parameters.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Honey Badger Algorithm Based Clustering with Routing Protocol for Wireless Sensor Networks

Arutchelvan¹,

Priya²,

Bhuvaneswari³

2023

Intelligent Automation &Amp; Soft Computing

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Wireless sensor network (WSN) includes a set of self-organizing and homogenous nodes employed for data collection and tracking applications. It comprises a massive set of nodes with restricted energy and processing abilities. Energy dissipation is a major concern involved in the design of WSN. Clustering and routing protocols are considered effective ways to reduce the quantity of energy dissipation using metaheuristic algorithms. In order to design an energy aware cluster-based route planning scheme, this study introduces a novel Honey Badger Based Clustering with African Vulture Optimization based Routing (HBAC-AVOR) protocol for WSN. The presented HBAC-AVOR model mainly aims to cluster the nodes in WSN effectually and organize the routes in an energy-efficient way. The presented HBAC-AVOR model follows a two stage process. At the initial stage, the HBAC technique is exploited to choose an optimal set of cluster heads (CHs) utilizing a fitness function involving many input parameters. Next, the AVOR approach was executed for determining the optimal routes to BS and thereby lengthens the lifetime of WSN. A detailed simulation analysis was executed to highlight the increased outcomes of the HBAC-AVOR protocol. On comparing with existing techniques, the HBAC-AVOR model has outperformed existing techniques with maximum lifetime.

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Section: Design Of Hbac Techniquementioning

confidence: 99%

Section: Design Of Hbac Techniquementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Honey Badger Algorithm Based Clustering with Routing Protocol for Wireless Sensor Networks

Arutchelvan¹,

Priya²,

Bhuvaneswari³

2023

Intelligent Automation &Amp; Soft Computing

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“…where N cl denotes number of CHs; d CH i to MS ð Þand d avgCH i to MS ð Þdenotes distance average distance from CHs to BS, correspondingly [17]. Minimum value of F m dist represents that the present CH i is a candidate to be the succeeding relay node to BS.…”

Section: Process Involved In Irso-eamhr Techniquementioning

confidence: 99%

Improved Rat Swarm Based Multihop Routing Protocol for Wireless Sensor Networks

Manikandan¹,

Narasimhan²

2023

Intelligent Automation &Amp; Soft Computing

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Wireless sensor networks (WSNs) encompass a massive set of sensor nodes, which are self-configurable, inexpensive, and compact. The sensor nodes undergo random deployment in the target area and transmit data to base station using inbuilt transceiver. For reducing energy consumption and lengthen lifetime of WSN, multihop routing protocols can be designed. This study develops an improved rat swarm optimization based energy aware multi-hop routing (IRSO-EAMHR) protocol for WSN. An important intention of the IRSO-EAMHR method is for determining optimal routes to base station (BS) in the clustered WSN. Primarily, a weighted clustering process is performed to group the nodes into clusters and select cluster heads (CHs). Next, the IRSO-EAMHR approach derives a fitness function containing three input parameters (residual energy, distance, and node degree) for routing process. The IRSO technique was designed by the integration of Levy movement concepts into the traditional RSO algorithm. The experimental result analysis of the IRSO-EAMHR technique is carried out and the outcomes are examined in various aspects. The simulation outcomes demonstrate the promising performance of the IRSO-EAMHR technique over the recent state of art approaches.

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“…), and (g) network topology management (like scalability, etc.). While some previous studies support only one objective (eg, References 28,29), huge number of works support various objectives simultaneously (eg, References 25 and 30‐39).…”

Section: Related Workmentioning

confidence: 99%

An energy‐aware and lightweight routing algorithm using clustering and mobile sinks in wireless sensor networks

Adabi

Mohammadifar

Nezhad

2022

Trans Emerging Tel Tech

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A wireless sensor network (WSN) consists of a number of small sensors which are powered by low-cost irreplaceable batteries. Therefore, one of the main issues in WSN design is to prolong the battery life of the individual sensors. Clustering and utilization of mobile sinks in collaboration with base station (BS) are two common solutions to address energy consumption challenge. Based on these solutions, a new algorithm in name "Energy-aware Routing algorithm using Clustering and Mobile Sinks (ERCMS)" is proposed in this article. The distinguishing features of ERCMS are as follows: (1) a geometric pattern is applied to divide entire network area into some parts and make cluster in each part. This pattern adjusts the cluster size based on the distance from the sink. Thus, hotspot problem is expected to be reduced, (2) computational load is distributed over sensors, (3) length of messages are controlled and each message is defined in the format with minimum required information, (4) simple mathematics approaches those impose lightweight computations are adopted, and (5) accuracy of mobile sink dispatching procedure is improved in critical conditions of the network. The simulation results show that ERCMS outperforms DFCR, MDFCR, and TEO-MCRP in terms of consumed energy, delivery ratio, delay, routing overhead, and throughput.

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TEO-MCRP: Thermal exchange optimization-based clustering routing protocol with a mobile sink for wireless sensor networks

Cited by 24 publications

References 39 publications

Honey Badger Algorithm Based Clustering with Routing Protocol for Wireless Sensor Networks

Honey Badger Algorithm Based Clustering with Routing Protocol for Wireless Sensor Networks

Improved Rat Swarm Based Multihop Routing Protocol for Wireless Sensor Networks

An energy‐aware and lightweight routing algorithm using clustering and mobile sinks in wireless sensor networks

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