Residual Energy Based Clustering for Energy EfficientWireless Sensor Networks

Shigei, Noritaka; Morishita, Hiroki; Miyajima, Hiromi; Maeda, Michiharu

doi:10.1007/978-90-481-3517-2_18

Cited by 8 publications

(8 citation statements)

References 7 publications

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“…LEACH-distributed versus LEACH-distributed [8] [9] In this section is exposed a comparison with the results of the simulations of Normal LEACH, Distributed LEACH, and federal leach. The evaluate consequences as explain above are related to the number of rounds done until half of the nodes are dead or when the first node is dead, where the latter case is also called network lifetime.…”

Section: Experimental Setup and Resultsmentioning

confidence: 99%

“…Evaluation parameter: the effectiveness of the proposed methods is demonstrated by numerical simulation. The proposed methods are compared with the conventional methods LEACH [9]. In the simulation, 25 sensor nodes are aimlessly distributed in the square region of the simulation is performed for N = 100, 300 and 1000.…”

Section: Experimental Setup and Resultsmentioning

confidence: 99%

“…In the simulation, 25 sensor nodes are aimlessly distributed in the square region of the simulation is performed for N = 100, 300 and 1000. For Energy Model [9] d075 m ,Eelec 50 nJ/ bit, Efusion 5 nJ/ bit, εfs 100 pJ/ bit/ m2, εmp 1.3 fJ/ bit/ m4,Initial battery level 0.5 Joule,Energy for data aggregation 5 nJ/ bit/ signal For Packet Model,Data packet size 800 bit,Broadcast packet size200 bit, Packet header siz 200 bit,For Distributed Method, Rinf 20 meters, Ren 55 meters. Half-dead network and First node dead: It can be seen the dissimilarity in the outcomes of both protocols.…”

Section: Experimental Setup and Resultsmentioning

confidence: 99%

See 2 more Smart Citations

Implementation of an Energy Efficient Routing Protocol for WSNs

Dubey¹,

Shastri²,

Khandelwal³

2014

IJCA

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The wireless sensor network technology is an enter constituent for universally acclaimed communication. A wireless sensor network consists of a huge number of sensor nodes. Each sensor node senses environmental circumstances such as temperature, light, force and sends the sensed data to a base station which is an extensive way rancid in universe. Since the sensor nodes are powered by inadequate power batteries, is regulate to lengthen the life time of the network, low energy expenditure is important for sensor nodes. A technique is proposed for optimization of power consumption in wireless sensor network. Here some energy efficient protocols are present, developed from conventional clustering protocol of Federal and distributed clustering protocol. The simulations are performed on omnet++ and which prove that the proposed protocol is better than LEACH and other approaches available.

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Section: Experimental Setup and Resultsmentioning

confidence: 99%

Section: Experimental Setup and Resultsmentioning

confidence: 99%

Section: Experimental Setup and Resultsmentioning

confidence: 99%

See 1 more Smart Citation

Implementation of an Energy Efficient Routing Protocol for WSNs

Dubey¹,

Shastri²,

Khandelwal³

2014

IJCA

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show abstract

“…In centralized clustering methods, such as K-means, a central repository contains the information about the entire system and performs clustering. In contrast, in a distributed approach, nodes have only local information and obtain aggregate information about other nodes by communicating [22,23,26]. Depending on the changes in their composition, clustering can be static or dynamic.…”

Section: Clustering As the Enabling Mechanism Of Decentralizationmentioning

confidence: 99%

Dynamic, self-organized clusters as a means to supply and demand matching in large-scale energy systems

Čaušević

Warnier

Brazier

2017

2017 IEEE 14th International Conference on Networking, Sensing and Control (ICNSC)

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CopyrightOther than for strictly personal use, it is not permitted to download, forward or distribute the text or part of it, without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license such as Creative Commons. Takedown policyPlease contact us and provide details if you believe this document breaches copyrights. We will remove access to the work immediately and investigate your claim. Centralized management of power systems is becoming more challenging due to the increased introduction of distributed renewable energy resources, along with demand increase and aging infrastructures. To address these challenges, this paper proposes new mechanisms for decentralized energy management. Based on self-organization of consumers, prosumers and producers into virtual groups, called clusters, supply and demand of electricity is locally matched. Distributed multi-agent systems are used as a way to represent virtual cluster members. The mechanisms are illustrated, and static and dynamic virtual clusters are compared. Dynamic reconfiguration is achieved by varying the time periods for which clustering is performed. The proposed clustering mechanisms demonstrate that large-scale centralized energy systems can operate in a decentralized fashion when only local information is available.

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“…In our previous papers, an energyefficient MAC protocol [14] and a network coding method [7] have been proposed for wide area sensor networks. In this paper we focus on clustering algorithms, which generally depends on whether the network is centralized or decentralized, [21]. Because we assume that the UAV has all the information of the network, a centralized clustering solution is used.…”

Section: Related Workmentioning

confidence: 99%

Cluster-based communication topology selection and UAV path planning in wireless sensor networks

Grøtli

Sujit

et al. 2013

2013 International Conference on Unmanned Aircraft Systems (ICUAS)

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In conventional wireless sensor networks (WSNs) to conserve energy Low Energy Adaptive Clustering Heirarchy (LEACH) is commonly used. Energy conversation is far more challenging for large scale deployments. This paper deals with selection of sensor network communication topology and the use of Unmanned Aerial Vehicle (UAV) for data gathering. Particle Swarm Optimzation (PSO) is proposed as an optimization method to find the optimal clusters in order to reduce the energy consumption, bit error rate (BER), and UAV travel time. PSO is compared to LEACH using a simulation case and the results show that PSO outperforms LEACH in terms of energy consumption and BER while the UAV travel time is similar. The numerical results further illustrate that the performance gap between them increases with the number of cluster head nodes. The reduced energy consumption means that the network life time can be significantly extended and the lower BER will increase the amount of data received from the entrie network.

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Residual Energy Based Clustering for Energy EfficientWireless Sensor Networks

Cited by 8 publications

References 7 publications

Implementation of an Energy Efficient Routing Protocol for WSNs

Implementation of an Energy Efficient Routing Protocol for WSNs

Dynamic, self-organized clusters as a means to supply and demand matching in large-scale energy systems

Cluster-based communication topology selection and UAV path planning in wireless sensor networks

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