Cluster head selection using hesitant fuzzy in Wireless Sensor Networks

Rayenizadeh, Mojgan; Rafsanjani, Marjan Kuchaki; Saeid, Arsham Borumand

doi:10.1109/cfis.2018.8336656

Cited by 5 publications

(4 citation statements)

References 23 publications

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“…They compared their result with other intelligence techniques and showed how their research works efficiently. Research also states that the optimal path has lower travel time consumption, In the year 2018, Mojgan Rayenizadeh [12] perform work on selecting Cluster Head (CH) using hesitant Fuzzy logic in (WSN). In this paper,theclustering technique is provided and analyzed to solve the energy consumption problem in WSN.…”

Section: Literature Surveymentioning

confidence: 99%

Biologically Inspired Energy Efficient Routing Protocol in Disaster Situation

Chavan,

Thorat,

Gunjal

et al. 2022

International Journal of Electronics and Telecommunications

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Wireless sensor network (WSN) plays a crucial role in many industrial, commercial, and social applications. However, increasing the number of nodes in a WSN increases network complexity, making it harder to acquire all relevant data in a timely way. By assuming the end node as a base station, we devised an Artificial Ant Routing (AAR) method that overcomes such network difficulties and finds an ideal routing that gives an easy way to reach the destination node in our situation. The goal of our research is to establish WSN parameters that are based on the biologically inspired Ant Colony Optimization (ACO) method. The proposed AAR provides the alternating path in case of congestion and high traffic requirement. In the event of node failures in a wireless network, the same algorithm enhances the efficiency of the routing path and acts as a multipath data transmission approach. We simulated network factors including Packet Delivery Ratio (PDR), Throughput, and Energy Consumption to achieve this. The major objective is to extend the network lifespan while data is being transferred by avoiding crowded areas and conserving energy by using a small number of nodes. The result shows that AAR is having improved performance parameters as compared to LEACH, LEACH-C, and FCM-DS-ACO.

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Section: Literature Surveymentioning

confidence: 99%

Biologically Inspired Energy Efficient Routing Protocol in Disaster Situation

Chavan,

Thorat,

Gunjal

et al. 2022

International Journal of Electronics and Telecommunications

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“…A dynamic cluster head selection method (DCHSM) for WSN has been introduced in [19], that dynamically selects a CH based on their residual energy and dynamically changes the CH after the death of the previous CH. In [20] the authors use the approach of hesitant fuzzy for CH selection by analysing their distance from the centre of the cluster and their range from the base station (BS) location. Similarly, in [21] the concept of nominating a CH based on their position on a WSN cluster is combined with their energy consumption while assuming a uniform distribution of SNs.…”

Section: A Related Workmentioning

confidence: 99%

An Energy Efficient Cluster-Heads Re-Usability Mechanism for Wireless Sensor Networks

Haider

Jamshed

Jiang

et al. 2019

2019 IEEE International Conference on Communications Workshops (ICC Workshops)

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Wireless sensor networks (WSNs) are formed using a cluster of sensor nodes (SNs), deployed randomly to perform sensing operations in an area under observation. Due to the unavailability of an external power source, the energy efficiency considered as one of the critical issues in WSNs. Selection of a sensor node (SN) from a wireless sensor network (WSN) cluster to serve as an aggregator or cluster head (CH), considered as an efficient method to increase the lifetime of wireless sensor network (WSN). In this paper, we have proposed an energy efficient CH selection scheme for WSN, to enhance the lifetime and average residual energy of a single WSN cluster. The proposed strategy nominates a group SNs as CHs, based on their channel condition with the base station (BS) and their residual energy. The proposed algorithm is helpful in solving the problem of unbalanced energy consumption in WSNs. Furthermore, the mechanism of using mobile sink during the hand-off stage helps to overcome the delay in data transmission. Moreover, the incorporation of energy harvesting significantly increases the lifetime of WSN. In comparison to a state-of-art technique available in the literature, our scheme shows a 33% increase in lifetime and presents a steady decrease in residual energy for the same rounds of data transmission.Index Terms-Wireless sensor network (WSN), lifetime, cluster head selection, average residual energy.

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“…Moreover, the motes or sensor nodes of the WSNs may be a collection of mobile, static, or combination of mobile and static nodes that possess the predominance of interacting with one another with the objective to ensure data exchange in an effective and reliable manner . The WSNs that comprise a complete set of sensor nodes being dynamic in movement around the considered application area of deployment is termed as mobile wireless sensor networks (MWSNs) . These MWSNs are determined to be ideally suitable in applications that are related to military, civil, and commercial context, since they require the advantage of continuous location sensing and event detection with monitoring .…”

Section: Introductionmentioning

confidence: 99%

“…3 The WSNs that comprise a complete set of sensor nodes being dynamic in movement around the considered application area of deployment is termed as mobile wireless sensor networks (MWSNs). 4 These MWSNs are determined to be ideally suitable in applications that are related to military, civil, and commercial context, since they require the advantage of continuous location sensing and event detection with monitoring. 5 However, the sensor nodes of MWSNs incorporate limited capabilities of computation power under sensing, energy resources, and buffer storage space.…”

Section: Introductionmentioning

confidence: 99%

An availability predictive trust factor‐based semi‐Markov mechanism for effective cluster head selection in wireless sensor networks

Amuthan

Arulmurugan

2019

Int J Communication

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Summary The longevity of the sensor networks purely depends on the effectiveness of a cluster head selection process that attributes towards effective network management in wireless sensor networks. However, the majority of the cluster head selection schemes are considered an unrealistic condition which ponders the sensor nodes that have the possibility of being selected as cluster heads are highly energy competitive and trustworthy. In this paper, an availability predictive trust factor‐based semi‐Markov mechanism (APTFSMM) was proposed for facilitating effective cluster head selection with the view to enhance its degree of longevity degree in wireless sensor networks. This proposed APTFSMM inherited the merits of semi‐Markov process for estimating availability predictive trust factor that quantifies the maximum likelihood probability under which it is selected as the cluster head through maximized exploration of multiple transition states of the sensors in the networks. This proposed APTFSMM is determined to be predominant in enhancing the lifetime of the sensor network by 31% with a significantly reduced energy consumption rate of 38% compared with the benchmarked cluster head selection approaches considered for investigation.

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Cluster head selection using hesitant fuzzy in Wireless Sensor Networks

Cited by 5 publications

References 23 publications

Biologically Inspired Energy Efficient Routing Protocol in Disaster Situation

Biologically Inspired Energy Efficient Routing Protocol in Disaster Situation

An Energy Efficient Cluster-Heads Re-Usability Mechanism for Wireless Sensor Networks

An availability predictive trust factor‐based semi‐Markov mechanism for effective cluster head selection in wireless sensor networks

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