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Top1. Introduction
A WSN contains varied sensors linked to the wireless medium. In WSN, the sensed data from SNs is typically forwarded to the BS, in which it is composed, evaluated, and specific actions are taken (Alagumuthukrishnan & Geetha, 2016; Yuvaraja & Sabrigiriraj, 2016; Ni et al. 2017). The WSN is used in a wide range of appliances, including meteorological data collection, weather forecasting and field observation, transportation, as well as health-care (Kang & Nguyen, 2012; Leu et al. 2015; Ajay & Verma, 2020). Even so, the SNs in WSN lack a rechargeable storage device as well as the capacity of researchable batteries. As a result, it is difficult to support any system with proficient power consumption (Wang et al. 2017; Kumar et al. 2018; Jia et al. 2016).
Clustering is a popular technique for making data transmission more efficient in terms of energy and power consumption (Mehra et al. 2018). Every cluster in the network has its own CH that is responsible for communicating information to the other SN in its cluster. The main task in such scenarios is to determine the optimal CH under a variety of constraints such as less energy utilization, delay, and so on (Al-Sodairi and Ouni, 2018; Nigam and Dabas, 2018; Priyadarshini and Sivakumar, 2018; Bhardwajm and Kumar, 2019). Thus, by forming clusters using data fusion and aggregation systems, there is EE in the network because the amount of data conveyed to BS is significantly reduced (Mahajan et al. 2014; Muthukumaran et al. 2018; Ni et al. 2017).
As a result, cluster-oriented schemes were also involved in extending network lifetime (Darabkh et al. 2019; Kannan & Raja, 2015; Mann & Singh, 2017). Furthermore, “APTEEN, TEEN, LEACH, PEGASIS, and FCM” are the most commonly used schemes (Kaur & Mahajan, 2018; Tianshu et al. 2018; Bhardwajm & Kumar, 2019; Dehghani et al. 2021). So far, a set of centralized cluster-oriented schemes based on meta-heuristic algorithms has been established. PSO, HSA, and other general algorithms are examples. However, the most demanding factors in modeling the routing protocol are EE, QoS, and network lifetime (Li et al. 2020).
Main contribution of the research study;
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Introduces optimal CHS approach via concerning distance, trust, delay, path quality, energy as well as security.
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Establishes SWFU-CMO algorithm for electing the optimal clusters in WSN.
Organization of the study: Section 2 reviews the related studies. Section 3 represents network architecture. Section 4 discusses the varied constraints considered for optimal selection of cluster heads. Section 5 portrays the suggested SWFU-CMO approach. Section 6 presents the outcomes as well as the study is ends in section 7.
Top2. Literature Review
In Daneshvar et al. (2019) introduced a novel clustering work with finest CHS through taking into account of 4 chief criterions like security, energy, distance, and delay. Furthermore, a novel approach known as FPU-DA is established to choosing the best CH. At last, the efficiency of developed approach was proven in terms of various measures.
In Ajay and Verma, (2020) proposed a DMEERP for balancing the energy utilization as well as path reliability ratio. The path reliability ratio was estimated in order to route the packets rapidly as well as without packet loss. Lastly the improvements in overhead, energy utilization, and so on were demonstrated.