• Title/Summary/Keyword: Cluster-head Selection Algorithm

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An Energy Efficient Cluster-head Selection Algorithm Using Head Experience Information in Wireless Sensor Networks (무선 센서 네트워크환경에서 헤드 경험정보를 이용한 에너지 효율적인 클러스터 헤드 선정 알고리즘)

  • Kim, Hyung-Jue;Kim, Seong-Cheol
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.13 no.3
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    • pp.608-614
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    • 2009
  • In wireless sensor networks, there are hundreds to thousands of small battery powered devices which are called sensors. As sensors have a limited energy resources, there is a need to use it effectively. A clustering based routing protocol forms clusters by distributed algorithm. Member nodes send their data to their cluster heads then cluster heads integrate data and send to sink node. In this paper we propose an energy efficient cluster-head selection algorithm. We have used some factors(a previous cluster head experience, a existence of data to transmit and an information that neighbors have data or not) to select optimum cluster-head and eventually improve network lifetime. Our simulation results show its effectiveness in balancing energy consumption and prolonging the network lifetime compared with LEACH and HEED algorithms.

ECS : Energy efficient Cluster-head Selection algorithm in Wireless Sensor Network (무선 센서 네트워크에서의 에너지 효율적인 클러스터 헤드 선출 알고리즘)

  • Choi, Koung-Jin;Yun, Myung-Jun;Sim, In-Bo;Lee, Jai-Yong
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.32 no.6B
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    • pp.342-349
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    • 2007
  • Clustering protocol of Wireless sensor networks(WSNs) not only reducing the volume of inter-node communication by the nodes's data aggreation but also extending the nodes's sleep times by cluster head's TDMA-schedule coordination. In order to extend network lifetime of WSNs, we propose ECS algorithm to select cluster-head using three variables. It consists of initial and current energy of nodes, round information and total numbers which have been selected as cluster head until current round.

Trust Predicated Routing Framework with Optimized Cluster Head Selection using Cuckoo Search Algorithm for MANET

  • Sekhar, J. Chandra;Prasad, Ramineni Sivarama
    • IEIE Transactions on Smart Processing and Computing
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    • v.4 no.2
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    • pp.115-125
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    • 2015
  • This paper presents a Cuckoo search algorithm to secure adversaries misdirecting multi-hop routing in Mobile ad hoc networks (MANETs) using a robust Trust Predicated Routing Framework with an optimized cluster head selection. The clustering technique designed in this framework leads to efficient routing in MANETs. The heavy work load in the node causes an energy drop in cluster head, which leads to re-clustering of the group, and another cluster head is selected to avoid packet loss during data transmission. The problem in the re-clustering process is that the overall efficiency of the routing process is reduced and the processing time is increased. A Cuckoo search based optimization algorithm is proposed to solve the problem of re-clustering by selecting the secondary cluster head within the initially formed cluster group and eliminating the reclustering process. The proposed framework enables a node to select a reliable and secure route for MANET and the performance can be evaluated by comparing the simulated results with the AODV routing protocol, which shows that the performance of the proposed routing protocol are improved significantly.

Energy-Efficient Cluster Head Selection Method in Wireless Sensor Networks (무선 센서 네트워크에서 에너지 효율적 클러스터 헤드 선정 기법)

  • Nam, Choon-Sung;Jang, Kyung-Soo;Shin, Ho-Jin;Shin, Dong-Ryeol
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.10 no.2
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    • pp.25-30
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    • 2010
  • Wireless sensor networks is composed of many similar sensor nodes with limited resources. They are randomly scattered over a specific area and self-organize the network. For guarantee of network life time, load balancing and scalability in sensor networks, sensor networks needs the clustering algorithm which distribute the networks to a local cluster. In existing clustering algorithms, the cluster head selection method has two problems. One is additional communication cost for finding location and energy of nodes. Another is unequal clustering. To solve them, this paper proposes a novel cluster head selection algorithm revised previous clustering algorithm, LEACH. The simulation results show that the energy compared with the previous clustering method is reduced.

Development of Energy-sensitive Cluster Formation and Cluster Head Selection Technique for Large and Randomly Deployed WSNs

  • Sagun Subedi;Sang Il Lee
    • Journal of information and communication convergence engineering
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    • v.22 no.1
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    • pp.1-6
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    • 2024
  • Energy efficiency in wireless sensor networks (WSNs) is a critical issue because batteries are used for operation and communication. In terms of scalability, energy efficiency, data integration, and resilience, WSN-cluster-based routing algorithms often outperform routing algorithms without clustering. Low-energy adaptive clustering hierarchy (LEACH) is a cluster-based routing protocol with a high transmission efficiency to the base station. In this paper, we propose an energy consumption model for LEACH and compare it with the existing LEACH, advanced LEACH (ALEACH), and power-efficient gathering in sensor information systems (PEGASIS) algorithms in terms of network lifetime. The energy consumption model comprises energy-sensitive cluster formation and a cluster head selection technique. The setup and steady-state phases of the proposed model are discussed based on the cluster head selection. The simulation results demonstrated that a low-energy-consumption network was introduced, modeled, and validated for LEACH.

Optimal LEACH Protocol with Improved Bat Algorithm in Wireless Sensor Networks

  • Cai, Xingjuan;Sun, Youqiang;Cui, Zhihua;Zhang, Wensheng;Chen, Jinjun
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.13 no.5
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    • pp.2469-2490
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    • 2019
  • A low-energy adaptive clustering hierarchy (LEACH) protocol is a low-power adaptive cluster routing protocol which was proposed by MIT's Chandrakasan for sensor networks. In the LEACH protocol, the selection mode of cluster-head nodes is a random selection of cycles, which may result in uneven distribution of nodal energy and reduce the lifetime of the entire network. Hence, we propose a new selection method to enhance the lifetime of network, in this selection function, the energy consumed between nodes in the clusters and the power consumed by the transfer between the cluster head and the base station are considered at the same time. Meanwhile, the improved FTBA algorithm integrating the curve strategy is proposed to enhance local and global search capabilities. Then we combine the improved BA with LEACH, and use the intelligent algorithm to select the cluster head. Experiment results show that the improved BA has stronger optimization ability than other optimization algorithms, which the method we proposed (FTBA-TC-LEACH) is superior than the LEACH and LEACH with standard BA (SBA-LEACH). The FTBA-TC-LEACH can obviously reduce network energy consumption and enhance the lifetime of wireless sensor networks (WSNs).

A Token Based Clustering Algorithm Considering Uniform Density Cluster in Wireless Sensor Networks (무선 센서 네트워크에서 균등한 클러스터 밀도를 고려한 토큰 기반의 클러스터링 알고리즘)

  • Lee, Hyun-Seok;Heo, Jeong-Seok
    • The KIPS Transactions:PartC
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    • v.17C no.3
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    • pp.291-298
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    • 2010
  • In wireless sensor networks, energy is the most important consideration because the lifetime of the sensor node is limited by battery. The clustering is the one of methods used to manage network energy consumption efficiently and LEACH(Low-Energy Adaptive Clustering Hierarchy) is one of the most famous clustering algorithms. LEACH utilizes randomized rotation of cluster-head to evenly distribute the energy load among the sensor nodes in the network. The random selection method of cluster-head does not guarantee the number of cluster-heads produced in each round to be equal to expected optimal value. And, the cluster head in a high-density cluster has an overload condition. In this paper, we proposed both a token based cluster-head selection algorithm for guarantee the number of cluster-heads and a cluster selection algorithm for uniform-density cluster. Through simulation, it is shown that the proposed algorithm improve the network lifetime about 9.3% better than LEACH.

Clustering Algorithm with using Road Side Unit(RSU) for Cluster Head(CH) Selection in VANET (차량 네트워크 환경에서 도로 기반 시설을 이용한 클러스터 헤드 선택 알고리즘)

  • Kwon, Hyuk-joon;Kwon, Yong-ho;Rhee, Byung-ho
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2014.10a
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    • pp.620-623
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    • 2014
  • Network topology for communication between vehicles are quickly changing because vehicles have a special movement pattern, especially character which is quickly changed by velocity and situation of road. Because of these feature, it is not easy to apply reliable routing on VANET(Vehicular Ad-hoc Network). Clustering method is one of the alternatives which are suggested for overcoming weakness of routing algorithm. Clustering is the way to communicate and manage vehicles by binding them around cluster head. Therefore choosing certain cluster head among vehicles has a decisive effect on decreasing overhead in relevant clustering and determining stability and efficiency of the network. This paper introduces new cluster head selection algorithm using RSU(Road Side Unit) different from existing algorithms. We suggest a more stable and efficient algorithm which decides a priority of cluster head by calculating vehicles' velocity and distance through RSU than existing algorithms.

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A Study of Cluster Head Election of TEEN applying the Fuzzy Inference System

  • Song, Young-il;Jung, Kye-Dong;Lee, Seong Ro;Lee, Jong-Yong
    • International journal of advanced smart convergence
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    • v.5 no.1
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    • pp.66-72
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    • 2016
  • In this paper, we proposed the clustering algorithm using fuzzy inference system for improving adaptability the cluster head selection of TEEN. The stochastic selection method cannot guarantee available of cluster head. Furthermore, because the formation of clusters is not optimized, the network lifetime is impeded. To improve this problem, we propose the algorithm that gathers attributes of sensor node to evaluate probability to be cluster head.

Opportunity Coefficient for Cluster-Head Selection in LEACH Protocol

  • Soh, Ben;AlZain, Mohammed;Lozano-Claros, Diego;Adhikari, Basanta
    • International Journal of Computer Science & Network Security
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    • v.21 no.1
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    • pp.6-11
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    • 2021
  • Routing protocols play a pivotal role in the energy management and lifespan of any Wireless Sensor Network. Lower network lifetime has been one of the biggest concerns in LEACH protocol due to dead nodes. The LEACH protocol suffers from uneven energy distribution problem due to random selection of a cluster head. The cluster head has much greater responsibility compared to other non- cluster head nodes and consumes greater energy for its roles. This results in early dead nodes due to energy lost for the role of cluster- head. This study proposes an approach to balance the energy consumption of the LEACH protocol by using a semi-deterministic opportunity coefficient to select the cluster head. This is calculated in each node with the battery energy level and node ID. Ultimately, based on the opportunity cost, cluster head will be selected and broadcasted for which other nodes with higher opportunity cost will agree. It minimizes the chances of nodes with lower battery level being elected as cluster head. Our simulation experiments demonstrate that cluster heads chosen using our proposed algorithm perform better than those using the legacy LEACH protocol.