An Efficient Cluster Head Selection Algorithm for Wireless Sensor Networks -Edrleach
TL;DR: Three algorithms based on density and distance based Cluster Head, An Energy Efficient Algorithm for Cluster-Head Selection in WSNs, Consumed Energy as a Factor for Cluster Head are analyzed and studied and a new algorithm called EDRLEACH is proposed through this paper.
Abstract: The Cluster-head Gateway Switch Routing protocol (CGSR) uses a hierarchical network topology. CGSR organizes nodes into clusters, with coordination among the members of each cluster entrusted to a special node named cluster-head. The cluster head selection is done with the help of any of the algorithm for cluster head selection. Energy is the primary constraint on designing any Wireless Networks practically. This leads to limited network lifetime of network. Low-Energy Adaptive Clustering Hierarchy (LEACH) and LEACH with deterministic cluster head selection are some of the cluster head algorithms that enable to optimize power consumption of WSN. There are various factors like density & distance, threshold based, power efficient. Load balancing and scalability are the other factors which plays important role in the selection of Cluster head. Algorithms based on load balancing reduce communication cost to a great extent. The algorithms that this study is focused are A Density and Distance based Cluster Head, An Energy Efficient Algorithm for Cluster-Head Selection in WSNs, Consumed Energy as a Factor for Cluster Head. These three algorithms are analyzed and studied in this paper. The analysis of these algorithms gave birth to a new algorithm called EDRLEACH, which is proposed through this paper. Keywords-Cluster head,energy efficient algorithms,selection head algorithms, wireless sensor,networks.
Citations
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TL;DR: A genetic algorithm-based, self-organizing network clustering (GASONeC) method that provides a framework to dynamically optimize wireless sensor node clusters and greatly extends the network life and the improvement up to 43.44 %.
Abstract: The dynamic nature of wireless sensor networks (WSNs) and numerous possible cluster configurations make searching for an optimal network structure on-the-fly an open challenge. To address this problem, we propose a genetic algorithm-based, self-organizing network clustering (GASONeC) method that provides a framework to dynamically optimize wireless sensor node clusters. In GASONeC, the residual energy, the expected energy expenditure, the distance to the base station, and the number of nodes in the vicinity are employed in search for an optimal, dynamic network structure. Balancing these factors is the key of organizing nodes into appropriate clusters and designating a surrogate node as cluster head. Compared to the state-of-the-art methods, GASONeC greatly extends the network life and the improvement up to 43.44 %. The node density greatly affects the network longevity. Due to the increased distance between nodes, the network life is usually shortened. In addition, when the base station is placed far from the sensor field, it is preferred that more clusters are formed to conserve energy. The overall average time of GASONeC is 0.58 s with a standard deviation of 0.05.
156 citations
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TL;DR: This chapter introduces a secure image processing and transmission schema in WSN using Elliptic Curve Cryptography (ECC) and Homomorphic Encryption (HE) and Secure Image Processing and Transmission Schema in Cluster-Based Wireless Sensor Network.
Abstract: WSN as a new category of computer-based computing platforms and network structures is showing new applications in different areas such as environmental monitoring, health care and military applications. Although there are a lot of secure image processing schemas designed for image transmission over a network, the limited resources and the dynamic environment make it invisible to be used with Wireless Sensor Networks (WSNs). In addition, the current secure data transmission schemas in WSN are concentrated on the text data and are not applicable for image transmission’s applications. Furthermore, secure image transmission is a big challenging issue in WSNs especially for the application that uses image as its main data such as military applications. The reason why is because the limited resources of the sensor nodes which are usually deployed in unattended environments. This chapter introduces a secure image processing and transmission schema in WSN using Elliptic Curve Cryptography (ECC) and Homomorphic Encryption (HE). Secure Image Processing and Transmission Schema in Cluster-Based Wireless Sensor Network
13 citations
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TL;DR: This research introduces a WSN's energy-aware and coverage preserve hierarchal clustering and routing model based on multi-objective bat swarm optimization algorithm that outperforms the LEACH routing and clustering protocol.
Abstract: This research expands the scope of wireless sensor network (WSN) optimization from single objective to multi objective optimization. It introduces a WSN's energy-aware and coverage preserve hierarchal clustering and routing model based on multi-objective bat swarm optimization algorithm. Two objectives are taken into consideration; coverage and nodes residual energies. The proposed model optimizes the WSN by selecting the best fitting set of nodes as cluster heads. It works to maximize the WSN's coverage and to minimize the nodes' consumed energy. This minimizes the number of active cluster heads while preserving a higher percentage of the covered nodes in WSN. It extends the longevity of the WSN's lifetime and achieves good functioning reliability. The proposed optimization model overcomes the WSN's coverage and lifetime challenges. The proposed model outperforms the LEACH routing and clustering protocol.
13 citations
Cites methods from "An Efficient Cluster Head Selection..."
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TL;DR: This chapter proposes a new clustering model for WSN used in dynamic environments that implies that the sensor nodes shared the burden of relaying messages and, hence, elongated the overall network life.
Abstract: To extend the longevity of a homogeneous WSN, the key is to avoid nodes deplete energy before the others. Accordingly, this chapter proposes a new clustering model for WSN used in dynamic environments. In each transmission round, the remaining energy of sensor nodes are fairly even with some fluctuations. That is, as a consequence of the proposed method, the variance among remaining energy is quite low, which implies that the sensor nodes shared the burden of relaying messages and, hence, elongated the overall network life. The main factors that are used in our proposed method for choosing a CH are the distance between the CH and BS, the remaining battery power, and the expected consumed energy.
11 citations
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TL;DR: In this chapter, the main models of WSN with their advantages and limitations are discussed, specially the clustering model and the existing secure clustering methods are discussed and evaluated based on a set of criteria.
Abstract: Generally, WSN consists of thousands of inexpensive devices, called sensor nodes, capable of computation, communication and sensing events in a specific environment [1, 2, 3]. WSNs have attracted intensive interest from both academia and industry due to their wide application in civil and military scenarios [4, 5, 6]. Enormous advances that are emerging in WSNs act as a revolution in all aspects of our life. WSNs have unique specifications describe it and different from other networks. Sensor nodes have energy and computational challenges. Moreover, WSNs may be prone to software failure, unreliable wireless connections, malicious attacks, and hardware faults; that make the network performance may degrade significantly over time. Recently, there is a great interest related to routing process in WSNs using intelligent and machine learning algorithms such as Genetic Algorithms [7, 8, 9]. Security aspects in routing protocols have not been given enough attention, since most of the routing protocols in WSNs have not been designed with security requirements in mind [10, 11, 12, 13, 14]. In this chapter, the main models of WSN with their advantages and limitations are discussed, specially the clustering model. In addition, it provides a literature of the existing clustering methods of WSN that aims to increase the network lifetime. After that, the security aspects are explained in details. Finally, the existing secure clustering methods are discussed and evaluated based on a set of criteria.
10 citations
References
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TL;DR: This brief article focuses on six key research challenges for wireless sensor networks and concludes with a brief mention of a number of other research challenges that must be met before WSN become pervasive.
Abstract: Wireless sensor networks (WSN) are currently receiving significant attention due to their unlimited potential. However, it is still very early in the lifetime of such systems and many research challenges exist. In this brief article, I concentrate on six key research challenges for wireless sensor networks. I conclude with a brief mention of a number of other research challenges that must be met before WSN become pervasive.
116 citations
Journal Article•
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23 Dec 2008-World Academy of Science, Engineering and Technology, International Journal of Electrical, Computer, Energetic, Electronic and Communication Engineering
TL;DR: An energy-aware distributed unequal clustering protocol (EADUC) in multihop heterogeneous WSNs is proposed and Simulation experiments show that EADUC can prolong the lifetime of the network significantly.
Abstract: Due to the imbalance of energy consumption of nodes in wireless sensor networks (WSNs), some local nodes die prematurely, which causes the network partitions and then shortens the lifetime of the network. The phenomenon is called “hot spot” or “energy hole” problem. For this problem, an energy-aware distributed unequal clustering protocol (EADUC) in multihop heterogeneous WSNs is proposed. Compared with the previous protocols, the cluster heads obtained by EADUC can achieve balanced energy, good distribution, and seamless coverage for all the nodes.Moreover, the complexity of time and control message is low. Simulation experiments show that EADUC can prolong the lifetime of the network significantly.
52 citations
Proceedings Article•
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TL;DR: Considering node density and the distance from cluster head in sensor networks can be more energy-efficient than considering only the distance between nodes in energy usage of Wireless Sensor Networks.
Abstract: Sensor Networks consist of massively distributed, small devices that have some limited sensing, processing, and communication capabilities. Due to the design of the topology of Sensor Networks, supporting energy-efficient routing protocol in the sensor networks is a challenging task. In this paper, we propose a Density and Distance based Cluster Head Selection (DDCHS) algorithm. The proposed algorithm divides cluster area into several perpendicular diameters, and then selects cluster head by the density of member nodes and the distance from cluster head. The simulation experiments shows that DDCHS algorithm has improves the network lifetime about 50% better than LEACH and about 10% better than HEED. From the results, considering node density and the distance from cluster head in sensor networks can be more energy-efficient than considering only the distance between nodes in energy usage of Wireless Sensor Networks.
30 citations
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TL;DR: This paper focuses on reducing power consumption by considering consumed energy as a factor for cluster head selection of each node to increase network life time of WSN rather than residual energy and proposes a new threshold formula of LEACH.
Abstract: Energy is the primary constraint on designing Wireless Sensor Networks (WSN) practically. This leads to limited network life time of WSN. Different communication protocols and algorithms are investigated to find ways to reduce power consumption. Low-Energy Adaptive Clustering Hierarchy (LEACH) and LEACH with deterministic cluster head selection are some of the cluster head algorithms that enable to optimize power consumption of WSN. However both rotation of cluster heads and metric of residual energy are not sufficient to balance the energy consumption across the network. This paper focuses on reducing power consumption by considering consumed energy as a factor for cluster head selection of each node to increase network life time of WSN rather than residual energy. Hence we propose a new threshold formula of LEACH. MATLAB simulation results show with this new approach, an increase of network lifetime by about 47-575% can be achieved.
26 citations
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