Hybridization of Metaheuristic Algorithm for Dynamic Cluster-Based Routing Protocol in Wireless Sensor Networksx

Al-Otaibi, Shaha; Al-Rasheed, Amal; Mansour, Romany F.; Yang, Eunmok; Joshi, Gyanendra Prasad; Cho, Woong

doi:10.1109/access.2021.3087602

Cited by 64 publications

(36 citation statements)

References 18 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This analysis also depicts that the proposed SRFIS-CWOSRR technique could efficiently reduce the packet drop ratio by enabling the reliable and succesful data transmission in the network. Consequently, figure 7 validates the average residual analysis of both existing [29] and proposed techniques with respect to varying rounds of operations. The average delay is also estimated for both existing and proposed routing methods with respect to different number of nodes.…”

Section: Fig 2 Number Of Alive Nodes Vs Simulation Roundsupporting

confidence: 55%

A Novel Optimization based Energy Efficient and Secured Routing Scheme using SRFIS-CWOSRR for Wireless Sensor Networks

Rao

Reddy²,

Chand³

2022

IJEER

View full text Add to dashboard Cite

Ensuring the reliable and energy efficient data routing in Wireless Sensor Networks (WSNs) is still remains one of the challenging and demanding tasks due to its dynamic architecture. For this purpose, the different types of routing methodologies and security schemes have been developed in the conventional works. However, it faced the problems related to increased network overhead, high cost consumption, reduced Quality of Service (QoS), and inefficient bandwidth utilization. The main contribution of this work is to implement an optimization based secured routing methodology for establishing an energy efficient data communication in WSNs. For clustering the nodes, the parameters such as residual energy, trust score, and mobility have been considered, which also helps to simplify the networking operations. Moreover, the outliers in the network are detected with the help of Spatial Temporal Fuzzy Inference System technique, which generates the set of inference rules based on the distance, energy, and mobility measures. Also, the Crow-Whale Optimized Secured Robin Routing (CWOSRR) is used to enable the data transmission in the network through the optimized path, which avoids the loss of information. During the simulation analysis, the results of the proposed technique is validated and compared by using various performance measures.

show abstract

Section: Fig 2 Number Of Alive Nodes Vs Simulation Roundsupporting

confidence: 55%

A Novel Optimization based Energy Efficient and Secured Routing Scheme using SRFIS-CWOSRR for Wireless Sensor Networks

Rao

Reddy²,

Chand³

2022

IJEER

View full text Add to dashboard Cite

show abstract

“…Al-Otaibi et al [13] progressed a hybridization of meta-heuristic cluster based routing (HMBCR) approach for WSN. The HMBCR approach primarily contains a brainstorm optimization with levy distribution (BSO-LD) based clustering method utilizing a FF integrating 4 parameters like distance to neighbors, network load, energy, and distance to base station (DBS).…”

Section: Literature Reviewmentioning

confidence: 99%

Metaheuristic Secure Clustering Scheme for Energy Harvesting Wireless Sensor Networks

Roopa¹,

Anandababu²,

Amaran³

et al. 2023

Computer Systems Science and Engineering

View full text Add to dashboard Cite

Recently, energy harvesting wireless sensor networks (EHWSN) have increased significant attention among research communities. By harvesting energy from the neighboring environment, the sensors in EHWSN resolve the energy constraint problem and offers lengthened network lifetime. Clustering is one of the proficient ways for accomplishing even improved lifetime in EHWSN. The clustering process intends to appropriately elect the cluster heads (CHs) and construct clusters. Though several models are available in the literature, it is still needed to accomplish energy efficiency and security in EHWSN. In this view, this study develops a novel Chaotic Rider Optimization Based Clustering Protocol for Secure Energy Harvesting Wireless Sensor Networks (CROC-SEHWSN) model. The presented CROC-SEHWSN model aims to accomplish energy efficiency by clustering the node in EHWSN. The CROC-SEHWSN model is based on the integration of chaotic concepts with traditional rider optimization (RO) algorithm. Besides, the CROC-SEHWSN model derives a fitness function (FF) involving seven distinct parameters connected to WSN. To accomplish security, trust factor and link quality metrics are considered in the FF. The design of RO algorithm for secure clustering process shows the novelty of the work. In order to demonstrate the enhanced performance of the CROC-SEHWSN approach, a wide range of simulations are carried out and the outcomes are inspected in distinct aspects. The experimental outcome demonstrated the superior performance of the CROC-SEHWSN technique on the recent approaches with maximum network lifetime of 387.40 and 393.30 s under two scenarios.

show abstract

“…Al-Otaibi et al [ 13 ] developed a hybridization of the MH cluster-based routing (HMBCR) approach for WSNs. The HMBCR approach primarily contained a brainstorm optimization with levy distribution (BSO-LD)-based clustering employing an FF integrating four parameters: network load, distance to neighbors, energy, and distance to BS.…”

Section: Literature Reviewmentioning

confidence: 99%

Wavelet Mutation with Aquila Optimization-Based Routing Protocol for Energy-Aware Wireless Communication

Alangari

Obayya

Gaddah

et al. 2022

Sensors

View full text Add to dashboard Cite

Wireless sensor networks (WSNs) have been developed recently to support several applications, including environmental monitoring, traffic control, smart battlefield, home automation, etc. WSNs include numerous sensors that can be dispersed around a specific node to achieve the computing process. In WSNs, routing becomes a very significant task that should be managed prudently. The main purpose of a routing algorithm is to send data between sensor nodes (SNs) and base stations (BS) to accomplish communication. A good routing protocol should be adaptive and scalable to the variations in network topologies. Therefore, a scalable protocol has to execute well when the workload increases or the network grows larger. Many complexities in routing involve security, energy consumption, scalability, connectivity, node deployment, and coverage. This article introduces a wavelet mutation with Aquila optimization-based routing (WMAO-EAR) protocol for wireless communication. The presented WMAO-EAR technique aims to accomplish an energy-aware routing process in WSNs. To do this, the WMAO-EAR technique initially derives the WMAO algorithm for the integration of wavelet mutation with the Aquila optimization (AO) algorithm. A fitness function is derived using distinct constraints, such as delay, energy, distance, and security. By setting a mutation probability P, every individual next to the exploitation and exploration phase process has the probability of mutation using the wavelet mutation process. For demonstrating the enhanced performance of the WMAO-EAR technique, a comprehensive simulation analysis is made. The experimental outcomes establish the betterment of the WMAO-EAR method over other recent approaches.

show abstract

Hybridization of Metaheuristic Algorithm for Dynamic Cluster-Based Routing Protocol in Wireless Sensor Networksx

Cited by 64 publications

References 18 publications

A Novel Optimization based Energy Efficient and Secured Routing Scheme using SRFIS-CWOSRR for Wireless Sensor Networks

A Novel Optimization based Energy Efficient and Secured Routing Scheme using SRFIS-CWOSRR for Wireless Sensor Networks

Metaheuristic Secure Clustering Scheme for Energy Harvesting Wireless Sensor Networks

Wavelet Mutation with Aquila Optimization-Based Routing Protocol for Energy-Aware Wireless Communication

Contact Info

Product

Resources

About