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2012, International Journal of Computer Applications
In numerous applications, self-organizing property of Wireless Sensor Networks (WSN) is an important characteristic. It calls for decompositions of the network into clusters of desirable bound. Cluster based WSN can enhance the whole networks lifetime. In every cluster, the cluster head (CH) plays an important role in aggregating and forwarding data sensed by other non-leader nodes. A major issue in the cluster based approach in WSN is the selection of proper cluster head and attainment of desirable cluster size by maximum number of clusters formed, keeping into consideration the inherent constraints such as limited battery energy, failure of nodes, selfish behavior of nodes, limited bandwidth etc, which inhibits superior message efficiency. This research paper presents a clustering approach termed as Sequential Multi-Clustering Protocol (SMCP) incorporating node deployment, which enhances the lifetime of the network. This Protocol is applied on some popular clustering algorithms like 'Expanding Ring', 'Rapid' and 'Persistent' along with our own clustering algorithm 'Message Based Memory Efficient Clustering Algorithm' (MMEC) to cluster an entire topology of the network. Simulation results mainly in MATLAB interpreter shows the effectiveness of clustering using SMCP protocol.
2014
Wireless sensor networks are an attractive field of researchers for several applications like industrial automation and environmental monitoring and military surveillances.Energy scarcity is a major issue on sensor networks. To meet out the requirement at various power management protocols are proposed by several researchers. Different cluster-based schemes are discussed as a solution for this problem. In this paper, analysis of the present-day classification and general grouping of clustering schemes are studied. It furthermore surveys different energy efficient clustering algorithms with QoS service enhancements.It also analyzes these clustering algorithms based on metrics such as energy efficiency, cluster stability, location awareness, node mobility and QoS support. Keywords-Sensor network, clustering, QoS, Lifetime, Energy efficiency -------------------------------------------------------------------------------------------------------------------------------Introduction Wirele...
International Journal for Scientific Research and Development, 2016
Today is the era of information technology, collect the information and use it for required application with technology support. Sensor nodes operating remotely are the popular approach for today's researcher for collecting real time information. But, facing difficulty due to constraints of energy resource for long life monitoring. So there is high need to have energy efficient communication scheme for the betterment of sensor network communication. Clustering protocol is the best option in designing routing protocol for Wireless Sensor Network (WSN). Though we have option of heterogeneity, Clustering approach enhances the energy efficiency of WSN by systematically sharing the load and hence prolongs the lifetime of the network. Most of the researchers achieve energy efficient approach in WSN, by adding different level high energy nodes and use clustering approach to prolong the lifetime of WSN. There are lots of efforts put in reality by researchers for the development of energy efficient schemes with WSN. This paper explored the contribution of different clustering scheme reported in published literature in the three sections as Clustering algorithm basic and its different attributes, suggested Cluster head selection criteria, literature survey and the identified gaps found in published material. The main aim of this paper is to present basic considered in designing clustering algorithm and metrics available for validation.
2019 IEEE International Conference on System, Computation, Automation and Networking (ICSCAN), 2019
Mobile wireless sensor network (MWSN) is an emerging technology, which is an extended form of wireless sensor network (WSN). It is employed in diverse real time applications due to its unique characteristics of self conFigure and mobility. We initiate a novel clustering technique by integrating super cluster head (SCH) concept with MTE protocolin this paper. The SCH are static and highly efficient sensor nodes which are placed inside the network to gather data from CHs. The use of SCH will reduce the distance of data transmission from CHs to BS and thereby increases the energy efficiency. The CHs transmit data to SCH and it will forward the data to BS. The incorporation of SCH with the MTE protocol will further increase the networks performance. The projected method is implemented and the results depicted the superiority of the projected method over another methods.
2024
The WSNs employ battery-powered sensors with limited energy, focusing on increasing network longevity through various techniques. The clustering algorithm focuses on improving network performance by optimizing energy usage. Within clustered Wireless Sensor Networks (WSNs), ordinary nodes collect data, relay it to cluster leaders, and subsequently dispatch it to the Base Station (BS). Clustering provides benefits such as the ability to handle larger loads, conserve energy, and minimize delays in data routing. This paper offers an extensive examination of clustering methods within the context of WSNs. The paper starts by outlining the goals of clustering, its key attributes, and its characteristics, followed by classifying clustering methods in WSNs based on network setups and methodologies. It also assesses recent clustering approaches, organizes them into different categories, and conducts a comparative analysis using a table.
2021
Wireless networks data aggregation allows in-network processing, reduces packet transmission and data redundancy, and thus helps extend wireless sensor systems to the full duration of their lives. There have been many ways of dividing the network into clusters, collecting information from nodes and adding it to the base station, to extend wireless sensor network life. Certain cluster algorithms consider the residual energy of the nodes when selecting clusterheads and others regularly rotate the selection head of the cluster. However, we seldom investigate the network density or local distance. In this report we present an energy-efficient clustering algorithm that selects the best cluster heads of the system after dividing the network into clusters. The cluster head selection depends on the distance between the base station nodes and the remaining power of this approach.Each node's residual energy is compared to the node count. Our results show that the solution proposed more ef...
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).
Ad Hoc & Sensor Wireless Networks, 2007
Data gathering is a common but critical operation in many applications of wireless sensor networks. Innovative techniques that improve energy efficiency to prolong the network lifetime are highly required. Clustering is an effective topology control approach in wireless sensor networks, which can increase network scalability and lifetime. In this paper, we propose a novel energy efficient clustering scheme (EECS) for single-hop wireless sensor networks, which better suits the periodical data gathering applications. Our approach elects cluster heads with more residual energy in an autonomous manner through local radio communication with no iteration while achieving good cluster head distribution; further more, it introduces a novel distance-based method to balance the load among the cluster heads. Simulation results show that EECS prolongs the network lifetime significantly against the other clustering protocols such as LEACH and HEED.
Wireless sensor networks (WSN) is a network which is formed with a maximum number of sensor nodes. Sensor nodes are equipped with self-battery power through which they can perform adequate operation and communication among neighboring nodes. Maximize the lifetime of the wireless sensor network; energy conservation measures are essential for improving the performance of wireless sensor network. Clustering plays a vital role in wireless sensor network. By use of clustering schemes and optimization techniques we can minimize the power consumption in WSN and increase the lifetime of network. The major concern of clustering schemes and cluster head election techniques are surveyed in this paper. Index Terms-Wireless Sensor network, Energy efficient clustering and network lifetime, cluster head election.
—A wireless sensor network comprises a number of small sensors that communicate with each other. Each sensor collects the data and communicates through the network to a single processing center that is a base station. The communication of node and process of message passing consumes energy. This energy consumption by the nodes to transmit data decreases the network lifetime significantly. Clustering is by far the best solution to save the energy consumption in the context of such network. Clustering divides the sensors into groups, so that sensors communicate information only to cluster heads and then the cluster heads communicate the aggregated information to the processing center so as to save energy. This paper studies and discusses various dimensions and approaches of some broadly discovered algorithms for clustering. It also presents a comparative study of various clustering algorithms and discussion about the potential research areas and the challenges of clustering in wireless sensor networks.
International Journal of Engineering Research and, 2016
Wireless Sensor Network has become progressively more demanding and has found their way into a variety of ways of application in real world. Wireless Sensor Network (WSN) consists of several small nodes called sensor, each capable of sensing, computing and transmitting of sensed real world information. As sensor nodes rely on the non-rechargeable energy source i.e. Small Battery, so energy consumption is a big issue here. Clustering is proved to be a good way to manage energy decapitation of WSN.
—Sensor nodes form a vital part in the wireless sensor network. These sensor nodes are used for sensing, transmitting and receiving the data from the other nodes. The energy of the sensor nodes used for transmitting the data depicts the life span of the network. As the sensor nodes are battery operated, energy consumption is one of the main issues in the wireless sensor network. Low is the energy consumed more is the life time of the network. For this problem various energy efficient algorithm were designed that were used for increasing the life time of the network thus making system more efficient. Modified LEACH is one of such energy efficient protocol that helps in saving the node energy and hence increasing networks lifetime. This paper presents a detailed study of modified LEACH protocol. Along with this various other energy efficient protocols are analyzed and the comparison is made. From the results obtained it is concluded that modified LEACH is better and efficient than the existing protocols.
Journal of Wireless Networking and Communications, 2013
Wireless sensor networks are application specific networks co mposed of large number of sensor nodes. Limited energy resource of sensor nodes make efficient energy consumption of nodes as main design issue. Energy efficiency is achieved from hardware level to network protocol levels. Clustering of nodes is an effective approach to reduce energy consumption of nodes. Clustering algorith ms group nodes in independent clusters. Each cluster has atleast one cluster head. Nodes send data to respective cluster heads. Cluster heads send data to base station. Clustering algorith ms prolong network lifetime by avoiding long distance communicat ion of nodes to base station. In literature various clustering approaches are proposed. Work of this paper discusses working o f few of them and distinguishes them according to operational mode and state of clustering. Work of this paper helps to understand classification of clustering schemes.
A COMPARATIVE ANALYSIS OF CLUSTERING PROTOCOLS OF WIRELESS SENSOR NETWORK, 2020
The study aims to understand the various types of fault-tolerant clustering algorithms from the existing literature. Clustering is one of the proven models for efficient energy management in a wireless sensor network (WSN). The resource-constrained architecture of WSN demands efficient protocols that can save energy when the WSN explicitly deployed in a harsh and hostile zone. The several considered factors for clustering are cluster count, size and density, location awareness, node deployment, heterogeneity of nodes, message count, and selection of cluster head, etc. Here, we present a short review of existing clustering algorithms based on probabilistic and non-probabilistic factors. During the review process, we have considered a few explicit factors to differentiate among the considered well-known clustering approaches.
International Journal of Information Technology and Computer Science, 2013
Wireless sensor networks have recently emerged as important computing platform. These sensors are power-limited and have limited computing resources. Therefore the sensor energy has to be managed wisely in order to maximize the lifet ime o f the network. Simp ly speaking, LEA CH requires the knowledge of energy for every node in the network topology used. In LEA CHs threshold which selects the cluster head is fixed so this protocol does not consider network topology environ ments. We proposed IELP algorith m, which selects cluster heads using different thresholds. New cluster head selection probability consists of the in itial energy and the nu mber of neighbor nodes. On rotation basis, a head-set member receives data from the neighboring nodes and transmits the aggregated results to the distant base station. For a given number of data collecting sensor nodes, the number of control and management nodes can be systematically adjusted to reduce the energy consumption, which increases the network life.
INTERNATIONAL JOURNAL OF RESEARCH AND ANALYTICAL REVIEWS (IJRAR), 2019
Wireless sensor networks are essentially attractive, but in fact, this feature makes them energy efficient as well as the result of this hard energy limit is the subject of this issue. We are also working. Ingesting of energy-managed nodes in the consumption of wireless sensor networks (WSNs) is a deadly softness in these n/w. Meanwhile, these nodes typically run on series, so determined utility network depends on the consumption of this energy. Though, novel emerging optimum energy ingesting algo's, protocols as well as system designs need an evaluation platform. This necessitates modeling methods that may type a quick as well as an accurate assessment of their behavior. To create a cluster aimed at routing, data management as well as communication management, division in the sensor network has proved to be a technique to confirm long-distance disposition as well as deal with inadequacies of sensor networks such as limited energy as well as small communication sequences. Choosing cluster heads inside every cluster is significant since cluster heads (CH) use their energy aimed at extra energy as well as this weight is closely related to the cluster of surrounding nodes. Numerous existing protocols either choose cluster headlights or procedure maximum continuing power of nodes.
Energy hole problem is one of the main problem in Wireless Sensor network. Sensor nodes near the sink acts as a relays because they are forwarding their data as well as sensors are far away from sink. Hence Energy depletion is faster in convey nodes. Suppose all the relay nodes die, far sensors can’t communicate to the sink node even though they have Energy and data. This is due to Energy holes. To overcome this problem Mobile sink is used. Finding the path of mobile sink is a hard task. In this paper Mobile sink-based Adaptive Clustering Protocol [MSIEEP] is enhanced to improve the network lifetime. Sink will be reenergized for every 10 rounds.
International Journal of Scientific Research and Management, 2017
The applications of Wireless Sensor Networks (WSNs) are growing at rapid pace and providing pervasive computing environments. Energy constraints is the most critical issue in sensor applications and that needs be optimized to prolong the life of resource constrained sensor network. Clustering is an efficient technique to group the sensor nodes of entire network into number of clusters to support high scalability and provide better data aggregation by efficient utilization of limited resources of sensor nodes and that prolongs network lifetime. In this paper, some widely explored clustering algorithms in WSNs are discussed on several aspects and characteristics such as clustering timings, clustering attributes, convergence rate etc. The advantages and disadvantages of corresponding clustering algorithms are also explained with suitable examples. The paper finally concludes with discussion on the challenges of clustering in WSNs with mentioning the future research topics.
2021
The primary challenges in defining and organizing the operation of wireless sensor networks are the enhancement of energy utilization and the life of the system. Clustering is a powerful approach to aligning the system to the associated order, adjusting the load and improving the life of the system. In a cluster-based network, the cluster head closer to the sink depletes its energy quickly resulting in hot spot problems. Numerous algorithms on unequal clustering are being considered to conquer this problem. The downside in these algorithms is that the nodes that join the same cluster head will overburden the cluster head. So in this paper, we propose an algorithm called fuzzy based unequal clustering to improve the execution of a cluster. The proposed study is tested using simulation. The proposed algorithm is compared to two algorithms, one with an identical clustering algorithm called LEACH and the other with an unequal clustering algorithm called EAUCF. The simulation results usi...
2010 IEEE International Conference on Industrial Technology, 2010
LEACH (low-energy adaptive clustering hierarchy) is a well-known self-organizing, adaptive clustering protocol of wireless sensor networks. However it has some shortcomings when it faces such problems as the cluster construction and energy management. In this paper, LEICP (low energy intelligent clustering protocol), an improvement of the LEACH protocol is proposed to overcome the shortcomings of LEACH. LEICP aims at balancing the energy consumption in every cluster and prolonging the network lifetime. A fitness function is defined to balance the energy consumption in every cluster according to the residual energy and positions of nodes. In every round the node called auxiliary cluster-head calculates the position of the clusterhead using Bacterial Foraging Optimization Algorithm (BFOA). After aggregating the data received, the cluster-head node decides whether to choose another cluster-head as the next hop for delivering the messages or to send the data to the base station directly, using Dijkstra algorithm to compute an optimal path. The performance of LEICP is compared with that of LEACH. Simulation results demonstrate that LEICP can prolong the lifetime of the sensor network by about 62.28% compared with LEACH and acquire uniform number of cluster-heads and messages in the network.
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