Cluster Head Selection Algorithm Research Articles

Performance of Quasi Oppositional Butterfly Optimization Algorithm for Cluster Head Selection in WSNs

Abstract Wireless sensor networks (WSNs) technology is attracting the most of researchers and industry due to its application in wide contexts that include the military, surveillance, monitoring of habitat, health care, public safety and environmental monitoring. The consumption of energy is a crucial challenge faced in the WSN research. Clustering is an efficient technique for limiting the energy consumption of WSNs. But considering the hierarchical and cluster-based WSNs, the cluster heads utilize a high-level of energy because of data aggregation from various sensor nodes and transmit the same to the sink node. So, proper cluster head (CH) selection is required for sensor nodes’ energy conservation to prolong the network’s lifespan of the WSNs. In this paper, a CH selection protocol is proposed that is based on the quasi oppositional butterfly optimization algorithm (QOBOA). The proposed method is compared with original butterfly optimization along with certain existing algorithms with respect to the networks’ lifetime and efficiency of energy. Simulation results show that the QOBOA based CH selection scheme outperforms the existing ones.

Energy Efficient Diagonal Based Clustering Protocol in Wireless Sensor Network

In Wireless Sensor network (WSN), the sensor nodes have short life span due to its limited power source (i.e. battery). So its consumption needs to be optimized to increase the life span of WSN. We have developed and implemented a competent algorithm for cluster head selection and efficient transmission through hop by hop in WSN. In our proposed work, we have divided the area diagonally into two zones. The distance between sensor node and base station (BS) or transmission of data from SN to BS is decided by the zone in which node exists. In cluster based WSN, information gathered from every SN is sent to their respective coordinator or CH of every cluster. The simulation results were compared with state of the art algorithms depicting longer stability period, less dead nodes per round, larger average energy and extended lifetime.

An Efficient Cluster Based Resource Management Scheme and its Performance Analysis for V2X Networks

As the demand for VANETs data transmission continues to increase, the defined cellular band becomes a bottleneck to meet the demands for all vehicle-to-everything (V2X) users. To deal with this problem, an efficient cluster based resource management scheme and its performance analysis for V2X networks is suggested to discover exceptional needs for various types of VANETs connections, namely vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) connections, and to enhance the efficiency of cellular user with respect to sum ratio, packet received ratio and average throughput for V2I connections whereas maintaining constancy for each V2V link. To deal with the fast channel deviations because of high mobility, we developed an efficient cluster based resource management technique to attain spectrum sharing and power control that relies on large scale fading. In addition, we have also examined the resource management problem of VANETs and V2X users to minimize data communication effects. Primarily, the total cellular sum ratio of every V2I connections is employed as an analysis target to enhance the throughput and to minimize end-to-end latency of the whole V2I link. Moreover, efficient resource management and cluster head selection algorithms are developed which grant the optimum resource distribution. According to our results, the proposed scheme with efficient resource management improves cellular user sum rate, average packet received ratio and throughput in comparison with existing schemes.

A hybrid BFO-FOA-based energy efficient cluster head selection in energy harvesting wireless sensor network

This paper proposed a hybrid bacterial foraging optimisation (BFO) and fruitfly optimisation algorithm (FOA) for energy efficient cluster head (CH) selection in wireless sensor network. The bacterial foraging optimisation algorithm is inspired by the group foraging behaviour of bacteria such as E. coli and M. xanthus realising chemistry in the environment and moving away from specific signals. The FOA is simple framework and easy to implement for solving an optimisation problem with different characteristics. It is robust and fast algorithm and used to solve discrete optimisation problems. The performance metrics of the proposed method is evaluated for end to end delay, packet delivery, drop ratio, energy consumption, network lifetime and throughput. The simulation results show that the proposed method achieves better energy efficiency and network lifetime of 35%, 58%, and 67% compared to existing methods like ant colony optimisation, particle swarm optimisation and genetic algorithm.

Hybrid based Energy Efficient Cluster Head Selection using Camel Series Elephant Herding Optimization Algorithm in WSN

The rapid growth in wireless technology is enabling a variety of advances in wireless sensor networks (WSNs). By providing the sensing capabilities and efficient wireless communication, WSNs are becoming important factor in day to day life. WSNs have many commercial, industrial and telecommunication applications. Maximizing network lifespan is a primary objective in wireless sensor networks as the sensor nodes are powered by a non-rechargeable battery. The main challenges in wireless sensor networks (WSNs) are area of coverage, network’s lifetime and aggregating. Balanced node establishment (clustering) is the foremost strategy for extending the entire network's lifetime by aggregating the sensed information at the head of the cluster. The recent research trend suggests Meta-heuristic algorithms for the intelligent selection of ideal Cluster Heads (CHs). The existing Cluster Head Selection (CHS) algorithm suffers from the inconsistent trade-offs between exploration – exploitation and global best examine constraints. In this research, a novel Camel series Elephant Herding Optimization (CSEHO) algorithm is proposed to enhance the random occurrences of Camel algorithm by the Elephant Herding Optimization algorithm for optimal CHS. The Camel algorithm imitates the itinerant actions of a camel in the desert for the scavenging procedure. The visibility monitoring condition of the camel algorithm improves the efficiency of exploitation, whereas the exploration inefficiency of a Camel algorithm is compensated optimally by the Elephant Herding Optimization operator (Clan and separator). The superior performance of the proposed CSEHO algorithm is validated by comparing its performance with various other existing CHS algorithms. The overall attainment of the offered CSEHO algorithm is 21.01%, 31.21%, 44.08%, 67.51%, and 85.66%, better than that of EHO, CA, PSO, LEACH, and DT, respectively.

DistB-Condo: Distributed Blockchain-Based IoT-SDN Model for Smart Condominium

Condominium network refers to intra-organization networks, where smart buildings or apartments are connected and share resources over the network. Secured communication platform or channel has been highlighted as a key requirement for a reliable condominium which can be ensured by the utilization of the advanced techniques and platforms like Software-Defined Network (SDN), Network Function Virtualization (NFV) and Blockchain (BC). These technologies provide a robust, and secured platform to meet all kinds of challenges, such as safety, confidentiality, flexibility, efficiency, and availability. This work suggests a distributed, scalable IoT-SDN with Blockchain-based NFV framework for a smart condominium (DistB-Condo) that can act as an efficient secured platform for a small community. Moreover, the Blockchain-based IoT-SDN with NFV framework provides the combined benefits of leading technologies. It also presents an optimized Cluster Head Selection (CHS) algorithm for selecting a Cluster Head (CH) among the clusters that efficiently saves energy. Besides, a decentralized and secured Blockchain approach has been introduced that allows more prominent security and privacy to the desired condominium network. Our proposed approach has also the ability to detect attacks in an IoT environment. Eventually, this article evaluates the performance of the proposed architecture using different parameters (e.g., throughput, packet arrival rate, and response time). The proposed approach outperforms the existing OF-Based SDN. DistB-Condo has better throughput on average, and the bandwidth (Mbps) much higher than the OF-Based SDN approach in the presence of attacks. Also, the proposed model has an average response time of 5% less than the core model.

DistBlockBuilding: A Distributed Blockchain-Based SDN-IoT Network for Smart Building Management

Security, privacy, and transparency aspects of the Internet of Things (IoT) sensors have recently raised significant concerns among the public and policymakers. The distributed ledger and Blockchain technologies had brought solutions through transparently bridging two or multiple untrusted parties. In this research, a novel architecture for a smart building system, including a control system and automatic approaches, is proposed. An efficient cluster head selection algorithm is proposed to select the desired cluster head with the consideration of low energy consumption and fast head selection. An enhanced combination of IoT forwarding devices and Software-Defined Networking (SDN) technology is further advanced. Furthermore, the proposed “DistBlockBuilding” architecture is implemented for managing a safe and secure data transfer from one surface to another surface. Besides, Blockchain technology is performed for transferring data within the smart building. Finally, the performance of IoT-SDN based secured networks is evaluated.

Hybrid Bacteria Foraging Optimization with Cuckoo Search Algorithm for Optimal Clusterhead Selection in Wireless Sensor Networks

Wireless Sensor Networks (WSN) are operated on a battery source. The sensor nodes are required more energy for the communication and information processing and also reduced the network lifetime. An efficient clustering scheme is designed to reduce the energy utilization and prolonged the network lifetime. In this paper, a hybrid approach of Bacteria Foraging Optimization with Cuckoo Search algorithm is proposed in the LEACH-C algorithm. This proposed methodology improves the chemotaxis behavior of Bacteria Foraging Optimization by using the Cuckoo Search algorithm. The residual energy of the node and the minimum distance among the nodes are considered for selecting the optimal cluster head. The proposed methodology has been done in Network Simulator (NS-2) and the experimental results improve the network lifetime by increasing the alive nodes and minimize the energy consumption. The proposed methodology has provided 700 seconds of life duration to the nodes, which is significantly higher than the lifetime provided by any other conventional techniques.

An Efficient Variable Distance Measure K-Means [VDMKM] Algorithm for Cluster Head Selection in WSN

Wireless sensor networks (WSNs) provide an empirical and explorative ways to handle and collection of the data in the centralized way. In this paper an efficient variable distance measure k-means [VDMKM] algorithm for cluster heads (CHs) selection in WSN has been presented and analyzed. This approach is divided into two phases. In the first phase data preprocessing has been performed. In this phase size-based weight and threshold assignment have been done on the scaling factor of 1-10. In the second phase VDMKM approach has been applied. The main benefit of this approach is the capability of smaller distance assignments automatically based on different distance measures. The distance measures used here are Euclidean, Pearson coefficient and Manhattan correlation. The complete cluster correlated delay has been calculated along with the packet delivery time. Our distance measure based automatic distance adjustment approach provides better suited distance-based packet delivery in less time. The results are more prominent in the case of Euclidean and Manhattan.

ECHA: A Novel Energy Efficient Cluster Head Election Algorithm to Provide Energy-Aware Routing in WSN

Wireless Sensor Network (WSN) is composed of several low powered, tiny and cheap sensors deployed over a geographical area to monitor the environment. WSN can be set out in various real time applications like security and surveillance, healthcare monitoring, smart grids, smart buildings, environmental monitoring and industrial applications etc. A WSN includes numerous spatially dispersed sensor nodes or motes that sense the environment, transfer them to a computing device through hoping and processes them to result in useful information. Since motes are low-powered and operate on limited energy resource, prolong usage of same nodes to transfer data may lead to network failure. Clustering provides an efficient technique to increase the longevity of network by efficiently using the residual energy in the motes. We propose a reasonable energy aware routing protocol that implements energy efficient cluster formation through Energy efficient Custer Head Election (ECHA) algorithm that increases the network performance to a greater extent.

Two-level distributed clustering routing algorithm based on unequal clusters for large-scale Internet of Things networks

According to the recent advancements in communication technologies and the widespread use of smart devices, our environment can be transforming into the Internet of Things (IoT) because it can connect the physical, cyber, and biological world via smart sensors for different purposes. Wireless sensor networks are considered as one of the main infrastructures in the IoT systems. Therefore, decreasing the total energy consumption of sensor nodes and prolonging the network longevity are two important challenges that should be considered. To increase energy efficiency and to improve the network longevity, a two-level distributed clustering routing algorithm based on unequal clusters has been proposed for large-scale IoT systems. The main idea is to decrease the data transmission distances between member nodes and cluster heads to mitigate the hot spot problem by distributing two cluster heads in each cluster, which in turn leads to energy conservation and load balancing. The clustering method is two level due to the benefits it offers for the sensor nodes. First, each node can transfer its data to the nearest cluster head because a primary cluster head and a secondary cluster head have been considered for each cluster. Therefore, the nodes far from the primary cluster head can be organized based on their distances to the closest cluster head to reduce their data transmission distances to the cluster heads. Second, two cluster heads can be replaced with each other in different circumstances. This reduces the overhead of the cluster head selection algorithm in the proposed scheme. Third, the sensor nodes can benefit from the primary and secondary cluster heads to transfer the data to the sink through different paths with the minimum energy consumption. Simulation results indicate that the proposed algorithm has better performance in terms of total energy consumption, total network energy, and network longevity compared to previous similar schemes.

An energy‐efficient and balanced clustering approach for improving throughput of wireless sensor networks

SummaryMaximizing the lifespan of wireless sensor networks is currently drawing a lot of attention in the research community. In order to reduce energy consumption, sensor nodes that are far from the base station avoid sending data directly. As a result, several disjoint clusters are formed, and nodes within a cluster send their data through the cluster head to avoid long transmissions. However, several parameters related to transmission cost need to be considered when selecting a cluster head. While most of the existing research work considers energy and distance as the most stringent parameters to reduce energy consumption, these approaches fail to create a fair and balanced cluster. Consequently, unbalanced clusters are formed, resulting in the degradation of overall performance. In this research work, a cluster head selection algorithm is proposed that covers all parts of the sensing area in a balanced manner, saving a significant amount of energy. Furthermore, a capture effect–based intracluster communication mechanism is proposed that efficiently utilizes the time slot under various traffic conditions. A Näive Bayes classifier is used to adapt the window size dynamically according to the traffic pattern. Finally, a simulation model using OMNeT++ is developed to compare the proposed approach with the pioneer clustering approach, LEACH, and the contemporary LEACH‐MAC protocol in terms of performance. The results of the simulation indicate that the proposed approach improves the overall performance in terms of network lifetime, energy efficiency, and throughput.

Energy-Neutral Operation Based on Simultaneous Wireless Information and Power Transfer for Wireless Powered Sensor Networks

For energy-neutral operation (ENO) of wireless sensor networks (WSNs), we apply a wireless powered communication network (WPCN) to a WSN with a hierarchical structure. In this hierarchical wireless powered sensor network (WPSN), sensor nodes with high harvesting energies and good link budgets have energy remaining after sending their data to the cluster head (CH), whereas the CH suffers from energy scarcity. Thus, we apply the simultaneous wireless information and power transfer (SWIPT) technique to the considered WPSN so that the sensor nodes can transfer their remaining energy to the CH while transmitting data in a cooperative manner. To maximize the achievable rate of sensing data while guaranteeing ENO, we propose a novel ENO framework, which provides a frame structure for SWIPT operation, rate improvement subject to ENO, SWIPT ratio optimization, as well as clustering and CH selection algorithm. The results of extensive simulations demonstrate that the proposed ENO based on SWIPT significantly improves the achievable rate and reduces the energy dissipated in the network while guaranteeing ENO, in comparison with the conventional schemes without SWIPT.

An energy efficient stable clustering approach using fuzzy extended grey wolf optimization algorithm for WSNs

Wireless sensor network (WSN) is a cost-effective networking solution for information updating in the coverage radius or in the sensing region. To record a real-time event, a large number of sensor nodes (SNs) need to be arranged systematically, such that information collection is possible for a longer span of time. But, the hurdle faced by WSN is the limited resources of SNs. Hence, there is a high demand to design and implement an energy-efficient scheme to prolong the performance parameters of WSN. Clustering-based routing is the most suitable approach to support for load balancing, fault tolerance, and reliable communication to prolong performance parameters of WSN. These performance parameters are achieved at the cost of reduced lifetime of cluster head (CH). To overcome such limitations in clustering based hierarchical approach, efficient CH selection algorithm, and optimized routing algorithm are essential to design efficient solution for larger scale networks. In this paper, fuzzy extended grey wolf optimization algorithm based threshold-sensitive energy-efficient clustering protocol is proposed to prolong the stability period of the network. Analysis and simulation results show that the proposed algorithm significantly outperforms competitive clustering algorithms in the context of energy consumption, stability period and system lifetime.

Energy-Saving Optimization and Matlab Simulation of Wireless Networks Based on Clustered Multi-hop Routing Algorithm

Reducing the energy consumption of the wireless sensor network is an effective way to extend the lifetime of the wireless sensor network. This paper proposes a real-time routing protocol RRPBLC that combines location information and clustering technology. By dividing the monitoring area into cells, each cell is composed of a cluster, and the method of mixing cluster head elections and dynamically adjusting the forwarding transmission rate is adopted. The simulation results show that the clustering algorithm and cluster head election algorithm designed in this paper have good performance in balancing node load, which not only avoids the problem of “hot zone”, but also makes the node energy consumption uniform. At the same time, the performance of the algorithm in response to network performance degradation caused by node failure is also outstanding, even if 50% of nodes fail. The algorithm can still guarantee reliable monitoring data from the network, so it can greatly extend the network life cycle. The protocol not only can achieve energy balance of the network, extend the life cycle of the network, and has better real-time performance.

Multi-objective HSDE Algorithm for Energy-Aware Cluster Head Selection in WSN

Multi-objective HSDE Algorithm for Energy-Aware Cluster Head Selection in WSN

Adaptive Cuckoo Search and Squirrel Search Algorithm for Optimal Cluster Head Selection in WSN

Adaptive Cuckoo Search and Squirrel Search Algorithm for Optimal Cluster Head Selection in WSN

A Hierarchical Topology Control Algorithm for WSN, Considering Node Residual Energy and Lightening Cluster Head Burden Based on Affinity Propagation

The low energy adaptive clustering hierarchy (LEACH) is the classical hierarchical topology control algorithm and still widely used today in wireless sensor networks. There are some problems in LEACH such us an unreasonable selection and uneven distribution of cluster heads, not considering the residual energy of nodes, the cluster head is overloaded and there is a high energy consumption of data transmission. In this paper, a topology control algorithm with double cluster heads and multi-hop based on affinity propagation clustering (APDC-M) was proposed. In APDC-M, firstly, a cluster head election algorithm with double choices based on the affinity propagation clustering algorithm (AP) and reference node strategy (APDC) was proposed. APDC is responsible to elect the fusion cluster head for node clustering. Secondly, a forwarding cluster head is elected within each cluster. The forwarding cluster head is responsible for the data transmission in order to reduce the energy consumption of a single cluster head. Lastly, the forwarding cluster heads complete the data transmission from a cluster to the base station by the shortest path inter-cluster multi-hop mode. The comparison simulation results show that APDC-M can make the cluster head election more reasonable and the cluster head distribution more uniform, and effectively reduce the energy consumption of the cluster head nodes when transmitting data, thus prolonging the network life.

A Novel Framework to Secure CBWSNS Against the Selfishness Problem

Dynamic and cooperative nature of sensor nodes in Wireless Sensor Networks raises question on security. Various researchers work in this direction to spot malicious, selfish and compromised nodes. Various mechanisms followed are uniqueness of clustering, reputation system and an operation at specific nodes. LEACH is a hierarchical protocol in which most nodes transmit to cluster heads, and the cluster heads aggregate and compress the data and forward it to the base station (sink). Each node uses a stochastic algorithm at each round to determine whether it will become a cluster head in this round. Clustering process carried out in two stages takes the role of the reputation scheme and reveals specific operation at CH, IN and MNs beside their usual activities in cluster based wireless sensor networks. This paper mentioned the final structure of the security framework, corresponding attacks and defense mechanism of the model. It also discusses various security level processes of wireless sensor networks. Results implies that in a cluster-based protocol such as LEACH in which optimally 5% of the nodes are cluster heads it is likely that a significant portion of the network can be paralyzed or the entire network disabled, in the worst-case scenario, if these cluster heads are compromised. Our main contribution in this paper is our novel approach in maintaining trusted clusters through a trust-based decision-making cluster head election algorithm.

A Review on Cluster Head Selection Algorithms for Wireless Sensor Networks

International Journal of Computer Sciences and Engineering (A UGC Approved and indexed with DOI, ICI and Approved, DPI Digital Library) is one of the leading and growing open access, peer-reviewed, monthly, and scientific research journal for scientists, engineers, research scholars, and academicians, which gains a foothold in Asia and opens to the world, aims to publish original, theoretical and practical advances in Computer Science,Information Technology, Engineering (Software, Mechanical, Civil, Electronics & Electrical), and all interdisciplinary streams of Computing Sciences. It intends to disseminate original, scientific, theoretical or applied research in the field of Computer Sciences and allied fields. It provides a platform for publishing results and research with a strong empirical component. It aims to bridge the significant gap between research and practice by promoting the publication of original, novel, industry-relevant research.