An Integrated Distributed Clustering Algorithm for Large Scale WSN (original) (raw)
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Clustering Structure and Deployment of Node in Wireless Sensor Network
International Journal of Information Technology and Computer Science, 2014
Generally, grouping sensor nodes into clusters has been widely adopted by the research community to satisfy the above scalability objective and generally achieve high energy efficiency and prolong network lifetime in large scale WSN environments. The corresponding hierarchical routing and data gathering protocols imply cluster based organization of the sensor nodes in order that data fusion and aggregation are possible, thus leading to significant energy savings. We propose a clustering approach which organizes the whole network into a connected hierarchy and discuss the design rationale of the different clustering approaches and design principles. Further, we propose several key issues that affect the practical deployment of clustering techniques in wireless sensor network applications. Index Terms-WSN (Wireless Sensor Network), Sensor Node (SN), Base Station (BS), Cluster Head (CH), Mobile ad hoc network (MANET).
Real-World Applications of Distributed Clustering Mechanism in Dense Wireless Sensor Networks
The World Academy of Research in Science and Engineering
Wireless sensors and wireless sensor networks have come up to the forefront of the scientific community freshly. Clustering is a flourishing topology control approach, which can lengthen the lifetime and raise scalability for wireless sensor networks. The most well-liked criterion for distributed clustering methodology is to choose cluster heads with more residual energy and to rotate them occasionally. Sensors at very heavy traffic locations swiftly deplete their energy resources and die in advance, leaving behind the network to collapse. The use of these sensors and the likelihood of organizing them into networks have discovered many research issues and have highlighted innovative ways to cope with certain problems. In this paper, the perception of distributed clustering mechanism has been elaborated elegantly and different areas where such distributed clustering methodology could be put to use in emerging real world wireless sensor network applications have been compiled and discussed.
Extending the longevity, is a significant job to be accomplished by these sensor networks. The traditional routing protocols could not be applied here, due to its nodes powered by batteries. Nodes are often clustered in to non-overlapping clusters, so as to provide energy efficiency. A concise overview on clustering processes, within wireless sensor networks is given in this paper. But it is difficult to replace the deceased batteries of the sensor nodes. A distinctive sensor node consumes much of its energy during wireless communication. This research work suggests the development of a hierarchical distributed clustering mechanism, which gives improved performance over the existing clustering algorithm LEACH. The two hiding concepts behind the proposed scheme are the hierarchical distributed clustering mechanism and the concept of threshold. Energy utilization is significantly reduced, thereby greatly prolonging the lifetime of the sensor nodes.
CLUSTERING IN WIRELESS SENSOR NETWORK
IJRCAR, 2014
Wireless sensor network consists of many tiny sensor nodes. Energy, bandwidth, processing power and memory nodes are limited. Hence reducing power consumption, increasing the network lifetime and scalability are the main challenges in sensor networks. Cluster based routing protocols are the most useful schemes for extending Wireless Sensor Networks lifetime through dividing the nodes into several clusters and electing of a local cluster head for aggregating of data from cluster nodes and transmitting a packet to Base Station. However, there are several energy efficient cluster-based methods in the literature. In this paper, we will review clustering in wireless sensor networks and LEACH algorithm
International Journal of Future Computer and Communication
The use of wireless sensor networks continue to increase in many fields (scientific, logistic, military or health, etc).The size of the sensors constitutes, however, an important limitation, mainly in term of energetic autonomy and therefore lifetime because the battery must be very small. For this reason, the improvement of energy efficiency is a critical issue for WSN protocols. Clustering in wireless sensor networks is an effective way of structuring the network. Its purpose is to identify a subset of nodes in the network and to assign a cluster head to it. Hierarchical routing or clustering routing is considered to be the most favorable approach in terms of energy efficiency. It is based on the concept (child node-parent node) where the child nodes forward their messages to their parent, who then routes them in the entire network via other parent nodes to the base station (sink).Two major approaches are derived from this type of protocol: chain-based approach and cluster-based approach. Low Energy Adaptive Clustering Hierarchy (LEACH) is considered as the first hierarchical routing protocol based on the second approach. It is also one of the most popular hierarchical routing algorithms for sensor networks. Another variant of LEACH, called Low-Energy Adaptive Clustering Hierarchy centralized (LEACH-C), is also presented. This paper presents an improvement of LEACH and LEACH-C protocol based on two modifications one on balancing energy distribution of network by means of changing range of nodes being cluster head and other by load balancing the number of nodes equally by fixing the average value N, so the lifetime of the network is increased. Simulation results show that Improved LEACH-C can improve system lifetime over its comparatives. Index Terms-Wireless sensor network (WSN), leach, LEACH-C, clustering algorithm. I. INTRODUCTION Recent advances in micro-manufacturing and wireless communication technologies have spawned a new generation of networks called Wireless Sensor Networks (WSN) [1]. They consist of a multitude of sensors distributed randomly in areas often hostile and / or inaccessible to humans. These sensors collect various information about the physical or environmental environment and transmit them to a remote base station via wireless communications. Sensor networks find applications in monitoring (forest fire, meteorological measurements, air quality control), connected objects etc. Sensors, also known as nodes in the remainder of the paper Manuscript
A distributed clustering scheme for wireless sensor networks
2014 6th Conference on Information and Knowledge Technology (IKT), 2014
Clustering is a promising solution to conserve sensor energy levels and to organize tasks among nodes. This paper presents a distributed energy efficient protocol to cluster wireless sensor networks using two techniques: local re-clustering and multi-criteria cluster formation. When a Cluster Head (CH) maintains an acceptable part of its remaining energy, it is not necessary to cooperate in consecutive clustering processes (global re-clustering). However, most of the previous algorithms have not considered the energy harvesting attained from local re-clustering, which is the process of selecting a new CH only when the previous CH has consumed a prespecified part of its energy. Besides, each node computes a multi-criteria score for being selected as a CH and running a round. Simulation results show that the proposed protocol prolongs the lifetime of WSNs by decreasing clustering overhead.
An Alternative Clustering Scheme in WSN
IEEE Sensors Journal, 2015
Despite significant advancements in wireless sensor networks (WSNs), energy conservation in the networks remains one of the most important research challenges. One approach commonly used to prolong the network lifetime is through aggregating data at the cluster heads (CHs). However, there is possibility that the CHs may fail and function incorrectly due to a number of reasons such as power instability. During the failure, the CHs are unable to collect and transfer data correctly. This affects the performance of the WSN. Early detection of failure of CHs will reduce the data loss and provide possible minimal recovery efforts. This paper proposes a self-configurable clustering (SCCH) mechanism to detect the disordered CHs and replace them with other nodes. Simulation results verify the effectiveness of the proposed approach.
Clustering in Wireless Sensor Networks- A Survey
International Journal of Computer Network and Information Security, 2016
Increased demand of Wireless Sensor Networks (WSN) in various applications has made it a hot research area. Several challenges imposed which include energy conservation, scalability, limited network resources etc. with energy conservation being the most important. Clustering improves the energy efficiency by making high power nodes as cluster heads (CHs) which reduces the chance of energy depletion of nodes. Scalability, fault tolerance, data aggregation, energy efficiency are some of the main objectives of clustering. This paper discusses various challenges associated with clustering and different methods or techniques developed to overcome these challenges. Various clustering approaches have been summarized and few prominent Quality of service (QoS) based clustering routing protocols for WSN have been identified. Comparison of these approaches and protocols is discussed based on some parameters.
Survey on Recent Clustering Algorithms in Wireless Sensor Networks
2013
The use of wireless sensor networks (WSNs) has grown enormously in the last decade, pointing out the crucial need for scalable and energy-efficient routing and data gathering and aggregation protocols in corresponding large-scale environments. To maximize network lifetime in Wireless Sensor Networks (WSNs) the paths for data transfer are selected in such a way that the total energy consumed along the path is minimized. To support high scalability and better data aggregation, sensor nodes are often grouped into disjoint, non overlapping subsets called clusters. Clusters create hierarchical WSNs which incorporate efficient utilization of limited resources of sensor nodes and thus extends network lifetime. The objective of this paper is to present a survey on clustering algorithms reported in the literature of WSNs. This paper presents taxonomy of energy efficient clustering algorithms in WSNs.
Enhanced Hybrid Clustering Scheme for Dense Wireless Sensor Networks
Every cluster comprise of a leader which is known as cluster head. The cluster head will be chosen by the sensor nodes in the individual cluster or be pre-assigned by the user. The main advantages of clustering are the transmission of aggregated data to the base station, offers scalability for huge number of nodes and trims down energy consumption. Fundamentally, clustering could be classified into centralized clustering, distributed clustering and hybrid clustering. In centralized clustering, the cluster head is fixed. The rest of the nodes in the cluster act as member nodes. In distributed clustering, the cluster head is not fixed. The cluster head keeps on shifting form node to node within the cluster on the basis of some parameters. Hybrid clustering is the combination of both centralized clustering and distributed clustering mechanisms. This paper gives a brief overview on clustering process in wireless sensor networks. A research on the well evaluated distributed clustering algorithm Low Energy Adaptive Clustering Hierarchy (LEACH) and its followers are portrayed artistically. To overcome the drawbacks of these existing algorithms a hybrid distributed clustering model has been proposed for attaining energy efficiency to a larger scale.