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The restricted battery of the sensors has always been a bottleneck for the WSNs. To withstand the network life for a elongated period, the network can be partitioned into clusters. To boost the network routine, a three-level heterogeneous clustering procedure is proposed in this paper. The three levels of heterogeneity split the sensors into three...
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Both minimal set cover and maximum coverage are known to be NP-Hard when using homogeneous and heterogeneous wireless sensor networks due to the lack of knowledge of the minimum set that can cover the area of interest, limited power reserves, monitoring and communication ranges, and so...To avoid these issues, this paper proposes to measure the dis...
Citations
... This model extends the network lifetime and increases data packets of the network. Researchers [91] have proposed three levelled heterogeneous routing protocol to improve the lifetime of WSN by utilizing the threshold and energy factors for HN selection. The nodes of three types i.e., super, middle, and normal are used for becoming the CH. ...
WSN having not a fixed architecture randomly deploys numerous sensing nodes over any measuring area and the collected information are sent to the head nodes through wireless media. In the area of lifetime of sensing elements as it is placed in uncertain areas or inaccessible zones with limited energy sources where the replacement or recharging of these sensor battery is just tends to impossible researches are working. Hence, researchers are trying to design a routing protocol that can effectively use the resources of sensor nodes. Low-energy adaptive clustering hierarchy (LEACH) have come up with several successors from distributed clustering to centralized clustering, single- hoping to multi-hoping, normal power source to renewable energy based etc. This survey paper is based on the LEACH and its successors. Primary focus of our examination is the manner by which these all-inclusive conventions operate in the request to increase the survival period and in what way quality steering conventions are developed for wireless sensor networks. Moreover, this paper features a portion of the issues considered by LEACH and furthermore clarifies how problems are controlled by the expanded variants of LEACH.
... ology that is inspired by the synergistic functions of fish schools and flocks of birds. PSO portrays cognitive radios as particles within a multidimensional search space, where each particle represents a potential routing solution, as applicable to CRNs [169,170]. As they explore the search space, these particles dynamically modify their positions in relation to their individual experiences and the swarm's collective knowledge. ...
In order to meet the growing needs for wireless communication in dynamic and diverse circumstances, Cognitive Radio Networks (CRNs) have evolved as a transformational model. The important area of intelligent routing in CRNs is examined in this review, along with the potential, problems, and developments that have shaped this emerging discipline. A close study is done on spectrum-aware routing, machine learning-based methods, game theory-inspired strategies, and bio-inspired processes to show how they help solve problems like changing spectrum access, security issues, and the need to efficiently distribute resources. The ever-changing nature of radio settings presents both possibilities and difficulties for innovation in the fields of signal processing, machine learning, and protocol design. The main conclusions of the study highlight how important intelligent routing is to changing how CRNs operate in the future. In the face of dynamic situations, it offers improved resilience, adaptation, and spectrum efficiency. Security innovations, human-centered strategies via intelligent interfaces, and fusion with cutting-edge technology like blockchain and machine learning all reveal novel perspectives on CRNs. With far-reaching ramifications, intelligent routing is positioned as a keystone for reimagining the potential of wireless communication. Future navigation offers a paradigm shift as cutting-edge technology and intelligent routing algorithms combine, opening up previously unimaginable possibilities in the constantly changing field of wireless communication. This study acts as a compass, pointing practitioners and academics in the direction of intelligent routing’s revolutionary potential in the development of CRNs.
... Clustering is a hierarchical strategy initially employed in cellular networks, where mobile phones interface with fixed infrastructures to facilitate data flow [12]. The strategy allows bandwidth to be reused to increase system capacity and makes the network more stable when nodes move around [13]. The clustering approach in a WSN environment has the positive potentials to improve network performance by grouping nodes into clusters and assigning a leader to each cluster known as a cluster head (CH) [14]. ...
... Using Eqs. (10)- (13), the new position is updated with ...
This paper proposes a hybrid metaheuristic approach to optimize a duty cycle framework based on Seagull and Mayfly Optimization (HSMO-DC) Algorithm. This approach becomes crucial as current clustering protocols are unable to efficiently tune the clustering parameters in accordance to the diversification of varying WSNs. The proposed HSMO-DC primarily has two parts, where the first part takes care of the online cluster head selection and network communication using the seagull algorithm while the second part performs parameter optimization using the mayfly algorithm. The seagull is aimed at improving the energy distribution in the network through an effective bandwidth allocation procedure while reducing the total energy dissipation. Comparatively, with other clustering protocols, our proposed methods reveal an enhanced network lifetime with an improved network throughput and adaptability based on selected standard metric of performance measurement.
... Unequal Clustering Approaches and Cluster-Based Routing Protocols Review (Han et al., 2020;Mishra & Verma, 2020;Priyadarshi, Rawat, et al., 2020) : These articles offer a comprehensive review of unequal clustering approaches, providing insights into their objectives, characteristics, and other pertinent details. Furthermore, they critically review cluster-based routing protocols within WSNs, shedding light on their functionality and significance in these networks. ...
Wireless sensor networks (WSNs) have emerged as a crucial component in the field of networking due to their cost-effectiveness, efficiency, and compact size, making them invaluable for various applications. However, as the reliance on WSN-dependent applications continues to grow, these networks grapple with inherent limitations such as memory and computational constraints. Therefore, effective solutions require immediate attention, especially in the age of the Internet of Things (IoT), which largely relies on the effectiveness of WSNs. This study undertakes a comprehensive review of research conducted between 2018 and 2020, categorizing it into six main domains: 1) Providing an overview of WSN applications, management, and security considerations. 2) Focusing on routing and energy-saving techniques. 3) Reviewing the development of methods for information gathering, emphasizing data integrity and privacy. 4) Emphasizing connectivity and positioning techniques. 5) Examining studies that explore the integration of IoT technology into WSNs, with an eye on secure data transmission. 6) Highlighting research efforts aimed with a strong emphasis on energy efficiency. The study addresses the motivation behind employing WSN applications in IoT technologies, as well as the challenges, obstructions, and solutions related to their application and development. It underscores that energy consumption remains a paramount issue in WSNs, with untapped potential for improving energy efficiency while ensuring robust security. Furthermore, it identifies existing approaches' weaknesses, rendering them inadequate for achieving energy-efficient routing in secure WSNs. This review sheds light on the critical challenges and opportunities in the field, contributing to a deeper understanding of WSNs and their role in secure IoT applications.
... New clusters are produced if the excess energy falls below the calculated threshold, and the CH election process starts. Using threshold and energy parameters, Priyadarshi et al. [40] select the CH from the competent nodes. The performance gain has been constrained due to node density and distance ignorance. ...
An essential concern in the modern period is the growing energy consumption in the Internet of Things (IoT) networks, particularly when connecting resource-constrained devices. Prolonging the network’s lifespan under these circumstances poses a significant challenge. Clustering is a prominent strategy to enhance the network’s operational duration. However, poor cluster heads (CH) selection rapidly drains energy from network nodes. In multi-hop clustering systems, CH consumes more power by forwarding the data from other CHs and its data, creating “hot spots” in the network. We propose a novel evolutionary multi-objective clustering protocol (EMCP) for heterogeneous IoT networks to prolong the network lifetime. In the initial stage, the genetic algorithm optimizes the CH selection process by considering the residual energy, communication radius, the distance between the edge node and CH, and the distance between CHs as fitness parameters. The distance between IoT nodes and CHs determines the clustering process. The energy monitoring module also keeps track of the CHs’ power consumption following each data transmission. If the CH’s remaining power drops to a threshold value, the new cluster head is one of the IoT nodes close to the previous cluster head with the highest residual energy. In addition, the simulation is performed with multiple edge servers to solve the hot spot problem. The suggested protocol’s performance is compared against state-of-the-art protocols for various parameters, including network stability, network longevity, the number of alive nodes, residual energy, and throughput. According to the simulation findings, the EMCP protocol achieves 15,347, 19,493, 24,187, 41,833 rounds, and 1,901,246 packets, respectively, for metrics such as network stability, half nodes dead, three-quarter node dead, last node dead, and throughput. Similarly, EMCP-MS has 17,565, 25,585, 30,410, 45,567 rounds, and 1,957,942 packets for the same metrics. Thus, the EMCP protocol has 94.55%, 80.54%, and 26.15% more life than the GAOC, DDMPEAwithANUM, and OptGACHE protocols. EMCP-MS has 75.49%, 56.55%, and 26.51% more longevity than multi-sink versions of the above-mentioned state-of-the-art protocols.
... In [2] the authors have introduced a heterogeneous clustering protocol with three-level for WSNs that adopts the highest residual energy nodes as Cluster Head (CH) by handling the energy & threshold elements. The proposed work focused on the improvement of the energy of node and the probability of cluster head to raise the stability sector of the network. ...
The Energy-Efficient wireless sensor network is needed in the present-day Scenario. The main problem in the area of WSN is energy consumption or low battery power. In such a case the best routing protocols are required to reduce the energy consumption and to improve the network lifetime. This paper is focused on how to minimize the nodes' energy depletion and then how to rise the network lifetime by efficient routing protocols in the WSN. In this paper, we have proposed an Energy-Aware Routing protocol for Homogeneous and Heterogeneous WSNs called MAX LEACH. The proposed protocol improves the total network lifetime. The proposed protocol is simulated using MATLAB and observed that the network lifetime was improved when compared to existing Homogeneous and Heterogeneous protocols. Various parameters like alive nodes, dead nodes, throughput, residual energy, and packet transmission from nodes to the sink are also compared.
... This leads to lesser network lifetime and if their energy is not preserved or saved the entire motive of the network fails. In order to save the batteries of these sensors and to increase network lifetime, the clustering approach has been put forward by various researchers in the past [12][13][14][15][16]. ...
Smart farming is becoming the need of the hour nowadays in an effort to boost productivity and protect the crops. This can be done using sensors and internet enabled devices in the farm. The underlying wireless sensor network can sense various environmental parameters and can pass data to the internet enabled devices to support smart farming. The sensor nodes are, however, powered by smaller batteries and have limited lifetime. Therefore, this paper presents a clustering protocol which aims at increasing the lifetime of the sensor nodes. These sensors are considered to be pressure sensors which are deployed in the network and whenever any animal encroaches the farm, a signal can be passed to the internet enabled alarm system which can help the farmer to fend off the animals and protect his crops. The sensor network is considered to have three level of energy heterogeneity among the nodes and the cluster head is selected in such a way that the cluster formed by the head consists of more number of high energy nodes. The proposed protocol has been simulated in MATLAB environment and compared with Stable Election Protocol (SEP), Distributed Energy Efficient Clustering (DEEC) and Improved Stable Election Protocol (ISEP) based on network lifetime and throughput. The network lifetime for proposed protocol was 6567 rounds which was higher than others with network going dead at 5472 for ISEP, at 2495 for DEEC and at 2316 for SEP. The protocol has shown better performance against these existing protocols.
... However, the structure proposed in the scheme confines the advanced nodes and the normal nodes within their predefined regional boundaries only, and no mixing of the nodes is allowed, limiting the scheme to be very application-specific. Also, the scheme considers only two levels of energy heterogeneity. Priyadarshi et al. [54] proposed an energy-efficient routing scheme for three-level HWSN inspired by [11], [15]. The scheme aims at efficient CH selection for the network operation based on the nodes' probability-dependent thresholds and residual energy. ...
Internet-of-Things (IoT)-based Heterogeneous Wireless Sensor Network (HWSN) has emerged as a prevalent technology that plays a significant role in developing various human-centric applications. Like in a wireless sensor network (WSN), energy is also the most crucial resource in IoT-based HWSN. The researchers have proposed many works to achieve energy-efficient network operations by minimizing energy usage. A vast proportion of these works emphasize using the clustering approach, which has proved its worth to a great extent. However, most schemes require the repeated formation of clusters incurring a significant amount of nodes’ energy in the clustering process. The protocol design of such schemes also varies with the changing levels of heterogeneity. In this work, a hybrid clustering scheme- An Energy-Efficient Hybrid Clustering Technique (EEHCT) has been proposed for IoT-based HWSN that minimizes the energy consumption in clusters’ formation and distributes the network load evenly irrespective of the heterogeneity level to prolong network lifetime. It appropriately utilizes dynamic and static clustering strategies to formulate the load-balanced clusters in the network. EEHCT establishes its supremacy over state-of-the-art schemes via an extensive set of simulations and experimentation in terms of multiple network performance metrics like stability, throughput, and network lifetime. Like, it achieves a gain up to 90.27% with respect to network lifetime over its peers in the standard operating conditions and under varying network configurations. In addition to quantitative analysis, a statistical analysis has also been provided to demonstrate the formation of energy-balanced clusters through the proposed scheme.
... A self-dependent distributed sensor hub is called the WSN, which can easily be employed in any framework to monitor the environmental condition [1]. In addition, the hubs in WSN have the capacity to broadcast the information from one to another end node [2]; the cluster mechanism in WSN was established to minimize energy consumption [3]. ...
Wireless Sensor Networks (WSN) have widely grown worldwide and are utilized in all innovative applications, yet there are problems such as data overloading, packet drop, and lower data transmission rate. All these issues have been engendered due to the high energy consumption problem. The node consumes more energy and has less lifetime that might be disabled during the data transmission. To address these problems, a novel Wolf Fuzzy-based Aggregator Node selection (WFbANS) protocol is designed for the WSN environment. Initially, the node's parameters were validated and selected for the cluster hub. Consequently, the workless node has been identified to enable the sleep state. Furthermore, the planned energy-optimized model is tested in the MATLAB environment. Finally, the data was transferred, and the communication parameters were noted and compared with other models. The presented model has recorded the finest throughput rate of 350 Kbps, a data transfer rate of 99.7%, less energy consumption of 0.7 J, less packet drop of 2%, and a minor communication delay of 90 ms.
... A sensor node's malfunctioning or death because of an energy depletion while routing or performing the network activities could influence the performance of the network, which could in turn trigger topological change, network reorganization and data packets rerouting in the network. Sensor nodes' energy has always represented a significant design challenge for clustering protocols in the wireless sensor network [1,38]. Accordingly, the WSN protocols mainly focus on using the limited sensor energy productively to achieve a smooth network operation and to extend the network lifespan. ...
Wireless sensor networks (WSNs) have turned into a leading area of research over the course of the last few decades as they have been employed in various application domains. Since traditional approaches configure WSNs statically, their dynamic reconfiguration represents a difficult challenge. To address this challenge, clustering techniques can be integrated into WSNs. In the present paper, we present a comprehensive review of some of the recently proposed clustering protocols (from the year 2003 to 2021) that have been applied to WSNs. In this survey, clustering algorithms are categorized into four classes, namely (1) cluster-based protocols for homogeneous nodes, (2) cluster-based protocols for heterogeneous nodes, (3) clustering protocols based on fuzzy logic methods, and (4) clustering protocols based on heuristic methods. This categorization was carried out based on these protocols’ network organization as well as the techniques used for managing the procedures of clustering. For the purpose of evaluating the efficiency of these protocols, we take into account features, performance as well as clustering methodologies as the main parameters used in the comparison of these four categories of clustering approaches.
