Towards reliable self-clustering Mobile Ad Hoc Networks

Wang, Wei; Zeng, Guosun; Yao, Jing; Wang, Hanli; Tang, Daizhong

doi:10.1016/j.compeleceng.2011.11.018

Cited by 11 publications

(8 citation statements)

References 15 publications

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“…In the work by Wang et al, 19 the trust is used for cluster formation to improve the scalability and searching efficiency of MANETs. The Bayesian analysis is used for trust's evaluation, and clusters are formed with partial knowledge.…”

Section: Trust-based Model and Other Techniquesmentioning

confidence: 99%

“…Node degree is an important parameter in a cluster-based routing and is not considered by Chatterjee et al, 14 and Sinha et al 22 Irrespective of node mobility, the neighbor quality which is described in section ''Proposed honey bee algorithm-based clustering'' is not considered in many studies. [11][12][13][14][15][16][17][18][19][20][21][22][23] In our proposed scheme, multi-objective function is optimized using the parameters such as node degree, node remaining power, relative mobility (speed and direction), and neighbor quality.…”

Section: Selected Clustering Schemesmentioning

confidence: 99%

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Honey bee algorithm–based efficient cluster formation and optimization scheme in mobile ad hoc networks

Ahmad

Ikram

Lela

et al. 2017

International Journal of Distributed Sensor Networks

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In mobile ad hoc networks, topology changes very frequently due to node's mobility. Frequent change in topology increases traffic signaling that may arise energy and scalability issue. Cluster-based routing is the energy-efficient technique in mobile ad hoc networks to address the scalability issue and to minimize control messages. In this article, honey bee algorithm is used for dividing the mobile ad hoc network nodes into different clusters. The bees work to gather in groups to perform their activities. The proposed honey bee algorithm-based clustering forms clusters in an efficient manner with fewer resources such as energy and bandwidth utilization. A node is selected as cluster head based on node degree, neighbor's behavior, mobility direction, mobility speed, and remaining energy. Due to the efficient nature of bees and maximum parameter's consideration, the proposed technique inspired from the foraging behavior of honey bees gives efficient and stable cluster formation. The control message overhead is also avoided. The work is validated mathematically, and simulation has been performed for different scenarios. Simulation results are compared with existing clustering schemes. The simulation results show that the honey bee algorithm-based clustering technique used for clustering outperforms the existing schemes under consideration.

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Section: Trust-based Model and Other Techniquesmentioning

confidence: 99%

Section: Selected Clustering Schemesmentioning

confidence: 99%

Honey bee algorithm–based efficient cluster formation and optimization scheme in mobile ad hoc networks

Ahmad

Ikram

Lela

et al. 2017

International Journal of Distributed Sensor Networks

View full text Add to dashboard Cite

show abstract

“…The shorter the distance between two nodes is, the less the energy consumption for transferring information between them is. Therefore, for consuming less energy, while transferring information, a node with a shorter distance with its neighbors should be selected as the cluster head [ 24 ]. In fact a cluster head with closer distance from its neighbors requires less energy for transferring information which increases the cluster's stability.…”

Section: Virtual Links Weight-based Clustering Algorithm (Vlwbc)mentioning

confidence: 99%

A Novel Clustering Algorithm for Mobile Ad Hoc Networks Based on Determination of Virtual Links’ Weight to Increase Network Stability

Karimi

Afsharfarnia

Zarafshan

et al. 2014

The Scientific World Journal

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The stability of clusters is a serious issue in mobile ad hoc networks. Low stability of clusters may lead to rapid failure of clusters, high energy consumption for reclustering, and decrease in the overall network stability in mobile ad hoc network. In order to improve the stability of clusters, weight-based clustering algorithms are utilized. However, these algorithms only use limited features of the nodes. Thus, they decrease the weight accuracy in determining node's competency and lead to incorrect selection of cluster heads. A new weight-based algorithm presented in this paper not only determines node's weight using its own features, but also considers the direct effect of feature of adjacent nodes. It determines the weight of virtual links between nodes and the effect of the weights on determining node's final weight. By using this strategy, the highest weight is assigned to the best choices for being the cluster heads and the accuracy of nodes selection increases. The performance of new algorithm is analyzed by using computer simulation. The results show that produced clusters have longer lifetime and higher stability. Mathematical simulation shows that this algorithm has high availability in case of failure.

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“…The source node continues to accept RREP packets from the various nodes and compares RREP (RREP R1, RREP R2) which actually compares the destination hop count of two route replies and selects the route reply with high destination hop count if the difference between two hop counts is not significantly high. In [20] Wang et al proposed an approach to improve the scalability and efficiency of MANETs by arranging the nodes on the basis of trust mechanism. In our method, the trust value is calculated on the basis of cooperation between nodes.…”

Section: Related Workmentioning

confidence: 99%

A Novel Approach for Preventing Black-Hole Attack in MANETs

Seehra¹

2014

IJASA

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A black-hole attack in the Mobile Ad-hoc NETwork (MANET) is an attack occurs due to malicious nodes, which attracts the data packets by falsely advertising a fresh route to the destination. In this paper, we present a clustering approach in Ad-hoc On-demand Distance Vector (AODV) routing protocol for the detection and prevention of black-hole attack in MANETs. In this approach every member of the cluster will ping once to the cluster head, to detect the peculiar difference between the number of data packets received and forwarded by the node. If anomalousness is perceived, all the nodes will obscure the malicious nodes from the network.

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Towards reliable self-clustering Mobile Ad Hoc Networks

Cited by 11 publications

References 15 publications

Honey bee algorithm–based efficient cluster formation and optimization scheme in mobile ad hoc networks

Honey bee algorithm–based efficient cluster formation and optimization scheme in mobile ad hoc networks

A Novel Clustering Algorithm for Mobile Ad Hoc Networks Based on Determination of Virtual Links’ Weight to Increase Network Stability

A Novel Approach for Preventing Black-Hole Attack in MANETs

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