Swarm intelligence based fuzzy routing protocol for clustered wireless sensor networks

Zahedi, Zeynab Molay; Akbari, Reza; Shokouhifar, Mohammad; Safaei, Farshad; Jalali, Ali

doi:10.1016/j.eswa.2016.02.016

Cited by 136 publications

(45 citation statements)

References 21 publications

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“…The CH was determined by help of Sugeno fuzzy inference system, which included residual energy of the nodes, the distance from the sink, and the distance from the centroid of the cluster as the input parameters. A similar work based on swarm‐intelligence–based fuzzy routing was performed recently, which helped to overcome the problems of random clustering . During random clustering, the nodes were associated to the nearest CH without proper load balancing, which leads to unequal energy conservation.…”

Section: Related Workmentioning

confidence: 99%

“…The coverage of the entire area of application is one of the main aims of designing any cluster-based WSN so that no sensor node is left out to become a part of the clusters. To ensure participation of all the left-out nodes, a parameter termed as network coverage (NC) is evaluated as given 24 in Equation 9:…”

Section: Multi-dimensional Multi-objective Fitness Function For Clumentioning

confidence: 99%

“…A similar work based on swarm-intelligence-based fuzzy routing was performed recently, which helped to overcome the problems of random clustering. 9 During random clustering, the nodes were associated to the nearest CH without proper load balancing, which leads to unequal energy conservation. This problem of unequal clustering is somewhat overcome using this technique leading to better energy efficiency.…”

Section: Introductionmentioning

confidence: 99%

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A novel residual energy‐based distributed clustering and routing approach for performance study of wireless sensor network

Ghosh

Chakraborty

2019

Int J Communication

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Summary Non‐uniform energy consumption during operation of a cluster‐based routing protocol for large‐scale wireless sensor networks (WSN) is major area of concern. Unbalanced energy consumption in the wireless network results in early node death and reduces the network lifetime. This is because nodes near the sink are overloaded in terms of data traffic compared with the far away nodes resulting in node deaths. In this work, a novel residual energy–based distributed clustering and routing (REDCR) protocol has been proposed, which allows multi‐hop communication based on cuckoo‐search (CS) algorithm and low‐energy adaptive‐clustering–hierarchy (LEACH) protocol. LEACH protocol allows choice of possible cluster heads by rotation at every round of data transmission by a newly developed objective function based on residual energy of the nodes. The information about the location and energy of the nodes is forwarded to the sink node where CS algorithm is implemented to choose optimal number of cluster heads and their positions in the network. This approach helps in uniform distribution of the cluster heads throughout the network and enhances the network stability. Several case studies have been performed by varying the position of the base stations and by changing the number of nodes in the area of application. The proposed REDCR protocol shows significant improvement by an average of 15% for network throughput, 25% for network scalability, 30% for network stability, 33% for residual energy conservation, and 60% for network lifetime proving this approach to be more acceptable one in near future.

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Section: Related Workmentioning

confidence: 99%

Section: Multi-dimensional Multi-objective Fitness Function For Clumentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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A novel residual energy‐based distributed clustering and routing approach for performance study of wireless sensor network

Ghosh

Chakraborty

2019

Int J Communication

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“…Trabajos como los mostrados en (Rodríguez et al, Cheng etal., 2016;Zahedi et al, 2016;Lefever et al, 2016) entregan resultados que garantizan un excelente funcionamiento bajo tráfico dinámico y con alta carga de stress.…”

Section: Algoritmos Genéticos (Ag)unclassified

Solución Metaheurística para el Problema de Enrutamiento (RWA) en Redes de Ópticas de Multiplexación por División de Longitud de Onda (WDM)

2017

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ResumenEl artículo muestra los resultados de una nueva metaheurística basada en el algoritmo Snake One que se ha denominado Snake Three. Se basa en la utilización de los enlaces hasta la lograr su congestión máxima. De esta forma se logra cierto orden de uso de los recursos dejando libre el resto de enlaces para satisfacer la demanda entrante o futura. La red utilizada en la simulación es la NSFNET de los Estados Unidos bajo parametrización similar a otras simulaciones, logrando estresar el sistema hasta los 180 Erlangs. Los resultados muestran una mejora en el indicador utilización de la red, aunque el indicador probabilidad de bloqueo no muestra mejora. La metaheurística Snake Three es la última de la serie Snake y ha demostrado su eficacia para poder ser utilizada en otros escenarios de multiplexación. Palabras clave: algoritmos heurísticos; algoritmos snake; redes ópticas; RWA; WDM Metaheuristic Solution for the Routing and Wavelength Assignment (RWA) Problem in Wavelength-Division Multiplexing (WDM) Optical Networks AbstractThe article shows the results of a new metaheuristic based on the Snake One algorithm that has been called Snake Three. It is based on the use of links until achieving maximum congestion. In this way, some order in the use of resources is achieved by leaving free the rest of the links to satisfy the incoming or future demand. The network used in the simulation is the NSFNET, of the United States, under parameterization similar to other simulations, achieving to stress the system up to 180 Erlangs. The results show improvement in the indicator utilization of the network, while the indicator probability of blocking does not show improvement. The Snake Three metaheuristic is the latest in the Snake series and has proved its effectiveness to be used in other multiplexing scenarios.

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“…The network lifetime is measured using the three parameters. The Equation (27) is the fitness function and its constrains, which are used to maximized the network lifetime formulated as follows [29]:…”

Section: Optimization Of And-based Fuzzy Rule Via Firefly Algorithmmentioning

confidence: 99%

Dynamic Multi-hop Routing Protocol Based on Fuzzy-Firefly Algorithm for Data Similarity Aware Node Clustering in WSNs

Misbahuddin

Ratna

Sari

2018

INT J COMPUT COMMUN

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In multi-hop routing, cluster heads close to the base station functionaries as intermediate nodes for father cluster heads to relay the data packet from regular nodes to base station. The cluster heads that act as relays will experience energy depletion quicker that causes hot spot problem. This paper proposes a dynamic multihop routing algorithm named Data Similarity Aware for Dynamic Multi-hop Routing Protocol (DSA-DMRP) to improve the network lifetime, and satisfy the requirement of multi-hop routing protocol for the dynamic node clustering that consider the data similarity of adjacent nodes. The DSA-DMRP uses fuzzy aggregation technique to measure their data similarity degree in order to partition the network into unequal size clusters. In this mechanism, each node can recognize and note its similar neighbor nodes. Next, K-hop Clustering Algorithm (KHOPCA) that is modified by adding a priority factor that considers residual energy and distance to the base station is used to select cluster heads and create the best routes for intra-cluster and inter-cluster transmission. The DSA-DMRP was compared against the KHOPCA to justify the performance. Simulation results show that, the DSA DMRP can improve the network lifetime longer than the KHOPCA and can satisfy the requirement of the dynamic multi-hop routing protocol.

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Swarm intelligence based fuzzy routing protocol for clustered wireless sensor networks

Cited by 136 publications

References 21 publications

A novel residual energy‐based distributed clustering and routing approach for performance study of wireless sensor network

A novel residual energy‐based distributed clustering and routing approach for performance study of wireless sensor network

Solución Metaheurística para el Problema de Enrutamiento (RWA) en Redes de Ópticas de Multiplexación por División de Longitud de Onda (WDM)

Dynamic Multi-hop Routing Protocol Based on Fuzzy-Firefly Algorithm for Data Similarity Aware Node Clustering in WSNs

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