Intelligent Clustering for Balanced Energy Consumption in Wireless Sensor Networks (original) (raw)
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Energy is a valuable resource in wireless sensor networks. The status of energy consumption should be continuously monitored after network deployment. It can also be used to perform energy efficient routing in wireless sensor networks. In this neural network based energy efficient clustering and routing in wireless sensor network the life time of the network is maximized by balancing the energy consumption among different sensor nodes. In This paper we propose a neural network for energy efficient clustering and routing in wireless sensor network with the objective of maximizing the network life time. In This proposed system we use a selforganizing map neural network for clustering which can cluster nodes based on multiple parameters: Energy level and coordinate of sensor nodes. We applied some maximum energy nodes as weight on self organizing map units and form energy balanced clusters in order to better balance energy consumption in whole network which will prolong the network lif...
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Cluster based routing are the most frequently used energy efficient routing protocols in Wireless Sensor Networks which avoid single gateway architecture through dividing of network nodes into several clusters while in each cluster, Cluster Heads work as local Base stations. However, there is several energy efficient cluster-based protocols in the literature, most of them use the topological neighborhood or adjacency as main parameter to form the clusters. This paper present a new centralized adaptive Energy Based Clustering protocol through the application of Self organizing map neural networks (called EBC-S) which can cluster sensor nodes, based on their energy level and coordinates. We apply some maximum energy nodes as weights of SOM map units; so that the nodes with higher energy attract the nearest nodes with lower energy levels. So a cluster may not necessarily contain adjacent nodes. The new algorithm enables us to form energy balanced clusters and equally distribute energy ...
ieeexplore.ieee.org, 2003
Wireless Sensor Networks (WSNs) represent a new dimension in the field of networking. The collaboration of large numbers of networked sensors will revolutionize the multitude of applications where WSNs can be applied, in the near future. In this paper we suggest a self-adaptive clustering based scheme for WSNs. A dynamic clustering scheme for the self-configuration of nodes in the WSN is discussed. We also outline a self-adapting algorithm for optimizing the sleep times of the nodes in the cluster by adapting to varying traffic loads. Our discussion aims to produce a reliable and robust sensing network, that promises more energy saving, scalability, and increased lifetime for the WSN. We do not base our discussion in this paper on any specific application, and expect our scheme to hold for all generic applications where WSNs can be used.
2017
Wireless sensor networks are powered by limited battery resources. Thus energy efficiency is one of the most important issues and designing power-efficient is critical for prolonging the lifetime. Clustering techniques can reduce energy consumption and prolong sensor network lifetime. We proposed a Modified load balanced clustering algorithm for wireless sensor nodes on the basis of residual energy. The algorithm not only realizes load balance among sensor node, but also achieves selection of cluster head based on residual energy. Simulation results indicate our algorithm is more energy-efficient compared to previous algorithms. Our algorithm is to exploit efficiently the network energy, by reducing the energy consumed for cluster formation and also to avoid the formation of forced cluster head.
2010 International Conference on Computational Intelligence and Communication Networks, 2010
Since the energy constraint is one of the most important restrictions in wireless sensor networks so the issue of energy balancing is essential for prolonging the network lifetime. Hence this problem has been considered as a main challenge in the research of scientific communities. In the recent papers many algorithms have been proposed for clustering on wireless sensor network to balance the energy consumption such as multi-tier clustering protocol. In this work we propose the new clustering algorithm based on twotier network topology namely CAT. The cluster head selection algorithm in CAT is done in two stages. So there will be two cluster head in a cluster. This algorithm selects a best sensor node as a cluster head in two phases by different methods. Simulation Results show that the CAT prolongs the network lifetime about 45% and 19% compared to the LEACH and HEED, respectively.
Energy Efficient Clustering in Wireless Sensor Network
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...
International Journal of Advanced Smart Sensor Network Systems, 2020
Cluster-Based Routing Protocols is a renowned scheme to extend the lifetime and energy consumption simultaneously for the Wireless Sensor Network (WSN). Every sensor node work homogenously or heterogeneously which is energy constrained when energy and memory capacity is limited. Congregating information resourcefully in perilous situations in the sensor network for a large-scale area and huge time is required an effectual protocol. In this paper, we proposed a cluster-based hierarchical routing path protocol, namely SOM-PEG protocol, which is a modified PEGASIS protocol based on traditional PEGASIS with the employment of Self Organizing Map (SOM) neural network (NN). The simulation is performed on MATLAB simulation tool as well as NN GUI. The performance comparison shows that the proposed protocol provides better network lifetime and ensures less energy consumption compared with traditional PEGASIS protocol.
46 Survey on Efficient Clustering with Energy Aware Routing in Wireless Sensor Networks
2016
Wireless Sensor Networks (WSNs) are defined as dynamic, self-deployed, highly constrained structured network. The WSN is a special kind of network which consists of large number of sensors and minimum one base station. Main difference between the WSN and the traditional wireless networks is that sensors are extremely sensitive to energy consumption. Energy saving and load balancing are the crucial issue in designing the wireless sensor networks. Load balancing can be used to extend the lifetime of a sensor network by reducing energy consumption. Load balancing with clustering can increase network scalability and clustering can also use to achieve self-organization, power saving, channel access, routing. The lifetime of network, depends on various parameters such as number of nodes, strength, range of area and connectivity of nodes in the network. Sensor nodes in wireless sensor network are depends on battery power they have limited transmission and reception range thus energy effici...
A Fuzzy Based Clustering Protocol for Energy-efficient Wireless Sensor Networks
Proceedings of the 2nd International Conference on Computer Science and Electronics Engineering (ICCSEE 2013), 2013
Minimization of energy consumption is one of the most important research areas in Wireless Sensor Networks. Nowadays, the paradigms of computational intelligence (CI) are widely used in WSN, such as localization, clustering, energy aware routing, task scheduling, security, etc. Though many fuzzy based clustering techniques have been proposed earlier, many of them could not increase the total network life time in terms of LND (Last Node Dies) with comparing to LEACH. In this paper, a fuzzy logic based energy-aware dynamic clustering technique is proposed, which increases the network lifetime in terms of LND. Here, two inputs are given in the fuzzy inference system and a node is selected as a cluster head according to the fuzzy cost (output). The main advantage of this protocol is that the optimum number of cluster is formed in every round, which is almost impossible in LEACH (low-energy adaptive clustering hierarchy). Moreover, this protocol has less computational load and complexity. The simulation result demonstrates that this approach performs better than LEACH in terms of energy saving as well as network lifetime.
A Survey on Self-Organized Cluster-Based Wireless Sensor Network
Jurnal Teknologi, 2015
Study on Wireless Sensor Network (WSN) has been expended enormously in recent years. Sensor nodes are deployed in harsh environment which is operated autonomously. Network formation of WSNs are of two types, namely flat network and cluster-based network. Cluster-based network has various advantages as compare to flat network such as, efficient topology management, energy efficiency, minimized delay, better network communication, etc. Another important feature of cluster-based network is self-organized network. Self-organized enables new nodes joining to increase the coverage of the network and existing nodes leaving the network as node have limited energy. In recent years the demand of self-organized network is tremendously increasing to overcome the problem of node joining and leaving which maintain the smooth data communication. Thus, this survey addresses latest research works regarding self-organized cluster-based network. Moreover, a unique performance matrix is also investigat...