An efficient management algorithm for clustering in mobile ad hoc network

El-Bazzal, Zouhair; Kadoch, Michel; Agba, Basile L.; Gagnon, François; Bennani, Maria

doi:10.1145/1163653.1163660

Cited by 14 publications

(7 citation statements)

References 4 publications

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“…The Efficient Management Algorithm for Clustering (EMAC) [2] utilizes factors such as the node degree, remaining battery power, transmission power, and node mobility for the cluster heads' election. It is based on the clusters' capacity and it uses the link lifetime instead of the node mobility for the maintenance procedure.…”

Section: Clustering In Manetmentioning

confidence: 99%

Performance of distributed clustering with weighted optimization algorithm for MANET Cognitive Radio

Bednarczyk

Gajewski

2015

2015 International Conference on Military Communications and Information Systems (ICMCIS)

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Mobile Ad-Hoc networks (MANET) are widely used for data communication between mobile nodes on the digital battlefield. Clustering has evolved as an important research topic in military MANETs in reference to supporting the ability of C4I system reconfiguration in highly dynamic operation. Clustering is a process that divides the network nodes into groups according to the command system. Each cluster has a Cluster Head (CH) as a coordinator within the cluster. For policy-based MANET Cognitive Radio (CR) it is very important to have an appropriate set of policies according to the variety of specific scenarios of the data network usage. A few algorithms have been recently studied and proposed for distributed clustering. The presented algorithm is based on the multi-criteria decision using the weighted function of the main network parameters. An appropriate selection of weights values for each particular scenario is critical for the effectiveness of MANET-CR. As the simulations have shown, the number of clusters within the network and the number of nodes in the clusters determine the ability of CR adaptation according to better usage of the available spectrum resources. The performances of the proposed algorithm has been evaluated through the simulations using OMNeT++ simulator and the results are encouraging.

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Section: Clustering In Manetmentioning

confidence: 99%

Performance of distributed clustering with weighted optimization algorithm for MANET Cognitive Radio

Bednarczyk

Gajewski

2015

2015 International Conference on Military Communications and Information Systems (ICMCIS)

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“…Rotating the CH role distributes this higher burden among the nodes, thereby preventing the CH from dying prematurely [5,7,12,13,[15][16][17][18][19].…”

Section: B Rotating the Role Of The Chmentioning

confidence: 99%

Energy Efficient Clustering Algorithms for Wireless Sensor Networks

Wei

Kaplan

Chan

2008

ICC Workshops - 2008 IEEE International Conference on Communications Workshops

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Energy efficiency is a major concern in Wireless Sensor Networks (WSNs). Many clustering algorithms have been proposed for such a purpose. This paper investigates the existing clustering algorithms. The algorithms have been classified and some representatives are described in each category. After analyzing the strengths and the weaknesses of each category, an important characteristic of WSNs is pointed out for further improvement of energy efficiency for WSNs.

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“…In [3] when two cluster heads come in range they both give up roles and the initiated reclustering procedure yields only one new cluster head rather than two. In [6] a re-clustering protocol is proposed where a weighted metric that combines system-wide parameters is used for the cluster head selection.…”

Section: Related Workmentioning

confidence: 99%

Consistent Re-Clustering in Mobile Ad Hoc Networks

Tselikis

Douligeris

Mitropoulos

et al. 2008

2008 International Wireless Communications and Mobile Computing Conference

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Abstract-In this paper we revisit some considerations relative to the performance of re-clustering algorithms in MANET. We recommend that for a secure MANET the design of re-clustering algorithms should not only provide for clustering stability, but also for network robustness in terms of network connectivity, of message reliability, of tolerance against the attacks that target the cluster head nodes and of tolerance to random node failures due to energy drains. We also take into account the possibility of malicious users that might thwart the network protocol by advertising false topology information. We propose a distributed mechanism that for unbiased cluster head election first demands certain levels of consistency to be reached among the nodes.

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An efficient management algorithm for clustering in mobile ad hoc network

Cited by 14 publications

References 4 publications

Performance of distributed clustering with weighted optimization algorithm for MANET Cognitive Radio

Performance of distributed clustering with weighted optimization algorithm for MANET Cognitive Radio

Energy Efficient Clustering Algorithms for Wireless Sensor Networks

Consistent Re-Clustering in Mobile Ad Hoc Networks

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