Enhanced Zone Stable Election Protocol based on Fuzzy Logic for Cluster Head Election in Wireless Sensor Networks

Mary, S. A. Sahaaya Arul; Gnanadurai, Jasmine Beulah

doi:10.1007/s40815-016-0181-1

Cited by 20 publications

(4 citation statements)

References 43 publications

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“…distance,density, remaining energy, vulnerability index, Centrality and distance between CH to select the cluster head by using two step fuzzy logic. In [ [15] fuzzy logic is used for cluster head selection with three input parameters Remaining Energy, Distance to BS and Density. In [ [16]] fuzzy logic is used for the selection of cluster head with three parameters 'Energy', 'Distance to Base Station' and 'Density' with the concept of area division.…”

Section: Related Workmentioning

confidence: 99%

EEUCWFL: Energy Efficient Unequal Clustering With Multi-Input Multi-Output Fuzzy Logic

Pandey

Singh

2022

Preprint

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The Wireless Sensor Network (WSN) consists a group of sensors and a Base Station (BS) or sink. Sensors gather data from the sensing area and send these data to BS, either directly or through multi-hop data transmission. There are several methods of efficient data transmission. Clustering is one of them. WSN uses the many different algorithms for making the cluster to transmit the data from the physical environment to the BS. Clustering makes the WSN Network efficient and improves the network lifetime. Other data transmission methods like direct transmission consumes very much energy so the life span of the sensor nodes becomes low in comparison to the clustering algorithm. The disadvantage of multi-hop data transmission of clustering algorithm is that a cluster head closer to sink has to forward the data of its own cluster as well as the data of near by clusters. So the node near base station dies sooner. This problem is known as hot-spot problem. The solution of hot-spot problem is unequal clustering. Nodes near base station should be smaller in size to balance the remaining energy of the nodes. In this paper, we have proposed a clustering algorithm (EEUCWFL) which uses multi-input multi-output fuzzy logic to select an optimal cluster head with unequal cluster size. We compared our proposed algorithm with three best known algorithms LEACH, EEUC and CHEF. The Results show that our proposed algorithm optimize energy consumption and improves the network lifetime.

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Section: Related Workmentioning

confidence: 99%

EEUCWFL: Energy Efficient Unequal Clustering With Multi-Input Multi-Output Fuzzy Logic

Pandey

Singh

2022

Preprint

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“…Three linguistic variables were defined for each membership function as shown in Figure 1 The value for residual energy is divided evenly into low, medium, and high that has an interval of 0 to 0.5, 0.2 to 0.8, and 0.5 to 1, respectively. The linguistic variable for centrality is divided into 0 to 50 for near, 30 to 70 for satisfactory, and 50 to 100 for far [25]. Designed for RSSI, the linguistic variables are divided into -45 to 10 for good, -10 to 45 for acceptable, and 30 to 80 for bad [5].…”

Section: Fuzzy Logic Approachmentioning

confidence: 99%

Fuzzy-Logic-RSSI based approach for cluster heads selection in wireless sensor networks

Rahman

Kahar

Din

2020

IJEECS

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<span>Wireless Sensor Networks (WSNs) are defined as networks of nodes that work in a cooperative way in order to sense and control the surrounding environment. Several WSNs algorithms have been proposed by utilizing the Fuzzy Logic technique to select the cluster heads (CHs). Each technique employs a different combination of input parameters such as nodes density, communication cost, and residual energy. CHs determination is critical towards this goal, whereas the combination of input parameters is expected to play an important role. Nevertheless, the received signal strength (RSSI) is one of the main criteria which get little attention from researchers on the topic of CHs selection. In this study, an RSSI based scheme was proposed which utilizes Fuzzy Logic approach in order to be combined with residual energy and centrality of the fuzzy descriptor. In order to evaluate the proposed scheme, the performance Multi-Tier Protocol (MAP) and Stable Election Protocol (SEP) were compared. The simulation results show that the proposed approach has significantly prolonged the survival time of the network against SEP and MAP, while effectively decelerating the dead process of sensor nodes.</span>

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“…A collection of these type of sensor networks constitutes a Mobile Wireless Sensor Networks (MWSNs). MWSNs [12][13] [17][18][19][20][21] present many advantages compared with static WSNs in terms of energy consumption;improved coverage and enhanced target tracking ,they can also include mobile sink nodes to reduce the network density to the maximum in addition to the overall network cost . Since the topology of MWSNs is constantly changing, performing data routing to the destination becomes a challenging task .…”

Section: Introductionmentioning

confidence: 99%

First Out First Served Algorithm for Mobile Wireless Sensor Networks

Bouirden¹,

Azhari²,

Toumanari³

et al. 2018

ijacsa

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Wireless Sensor Networks (WSNs) have recently gained tremendous attention as they cover a vast range of applications requiring an important number of sensor nodes deployed in the area of interest to measure physiological types of data and send it back to the base station for further analysis and treatment. Many routing protocols have been proposed to perform data routing towards the destination in accordance with energy consumption,end-to-end delay and throughput. In this paper,the First Out First Served algorithm for cluster based routing in Mobile Wireless Sensor Networks was presented. The algorithm aims to increase packet reception within the cluster in a highly constrained environment.The results prove the efficiency of the proposed algorithm in increasing the reception of data packets by the cluster head and enhancing the Radio Coef f icient Dif f parameter of the network.

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Enhanced Zone Stable Election Protocol based on Fuzzy Logic for Cluster Head Election in Wireless Sensor Networks

Cited by 20 publications

References 43 publications

EEUCWFL: Energy Efficient Unequal Clustering With Multi-Input Multi-Output Fuzzy Logic

EEUCWFL: Energy Efficient Unequal Clustering With Multi-Input Multi-Output Fuzzy Logic

Fuzzy-Logic-RSSI based approach for cluster heads selection in wireless sensor networks

First Out First Served Algorithm for Mobile Wireless Sensor Networks

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