A Multi-parameter Weighted Clustering Algorithm for Mobile Ad Hoc Networks

Wang, Feng; Liu, Gaixia; Liao, Yuxiang; Zhao, Wei

doi:10.12733/jics20102385

Cited by 2 publications

(3 citation statements)

References 18 publications

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“…The clustering scheme proposed in [7] takes into account the speed difference among vehicles as well as their position and direction during the cluster formation process, but its mobility model is only applicable for a highway environment. MWC (Multi-parameter Weighted Clustering) [8] considers residual power, connectivity, and average mobility in clustering formation and maintenance. Its comprehensive performance is good, but MWC is not specially designed for a highly dynamic network.…”

Section: Related Workmentioning

confidence: 99%

“…To assess the performance of the proposed SCBCS scheme, we make simulations and conduct a comparative analysis of MOBIC [6], DLDC [16], MPBC [18], SECA [15], MWC [8] and SCBCS. In the above algorithms, only SECA and MWC consider the residual battery energy in the cluster head election.…”

Section: Simulation and Analysismentioning

confidence: 99%

“…In our study, we assume that the energy is sufficient during the simulation time. Thus, we do not consider the effect of residual battery energy and set the weighting factor of the residual battery energy to zero in [15] and [8] to choose a cluster head. MWC has two types of algorithms, so we choose type b to simulate.…”

Section: Simulation and Analysismentioning

confidence: 99%

See 2 more Smart Citations

A Signal Characteristic Based Cluster Scheme for Aeronautical Ad Hoc Networks

Tian¹,

Ma²,

Ru³

et al. 2014

KSII TIIS

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Clustering is an effective method for improving the performance of large scale mobile ad hoc networks. However, when the moving speed is very fast, the topology changes quickly, which leads to frequent cluster topology updates. The drastically increasing control overheads severely threaten the throughput of the network. SCBCS (Signal Characteristic Based Cluster Scheme) is proposed as a method to potentially reduce the control overheads caused by cluster formation and maintenance in aeronautical ad hoc networks. Each node periodically broadcasts Hello packets. The Hello packets can be replaced by data packets, which preserve bandwidth. The characteristics of the received packets, such as the Doppler shift and the power of two successive Hello packets, help to calculate the relative speed and direction of motion. Then, the link connection lifetime is estimated by the relative speed and direction of motion. In the clustering formation procedure, the node with the longest estimated link connection time to its one-hop neighbors is chosen as the cluster head. In the cluster maintenance procedure, re-affiliation and re-clustering schemes are designed to keep the clusters more stable. The re-clustering phenomenon is reduced by limiting the ripple effect. Simulations have shown that SCBCS prolongs the link connection lifetime and the cluster lifetime, which can reduce the topology update overheads in highly dynamic aeronautical ad hoc networks.

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Section: Related Workmentioning

confidence: 99%

Section: Simulation and Analysismentioning

confidence: 99%

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A Signal Characteristic Based Cluster Scheme for Aeronautical Ad Hoc Networks

Tian¹,

Ma²,

Ru³

et al. 2014

KSII TIIS

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An efficient routing protocol for the QoS support of large‐scale MANETs

Nazhad

Shojafar

Shamshirband

et al. 2017

Int J Communication

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SummaryThe hierarchical routing algorithm is categorized as a kind of routing method using node clustering to create a hierarchical structure in large-scale mobile ad hoc network (LMANET). In this paper, we proposed a new hierarchical clustering algorithm (HCAL) and a corresponded protocol for hierarchical routing in LMANET. The HCAL is designed based on a cost metric in the form of the link expiration time and node's relative degree. Correspondingly, the routing protocol for HCAL adopts a reactive protocol to control the existing cluster head (CH) nodes and handle proactive nodes to be considered as a cluster in LMANET. Hierarchical clustering algorithm jointly utilizes table-driven and on-demand routing by using a combined weight metric to search dominant set of nodes. This set is composed by link expiration time and node's relative degree to establish the intra/intercommunication paths in LMANET. The performance of the proposed algorithm and protocol is numerically evaluated in average endto-end delay, number of CH per round, iteration count between the CHs, average CH keeping time, normalized routing overhead, and packet delivery ratio over a number of randomly generated benchmark scenarios. Furthermore, to corroborate the actual effectiveness of the HCAL algorithm, extensive performance comparisons are carried out with some state-of-the-art routing algorithms, namely, Dynamic Doppler Velocity Clustering, Signal Characteristic-Based Clustering, Dynamic Link Duration Clustering, and mobility-based clustering algorithms. KEYWORDScluster head (CH), clustering, cost metrics, hierarchical routing algorithm, mobile ad hoc networks (MANET)

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A Multi-parameter Weighted Clustering Algorithm for Mobile Ad Hoc Networks

Cited by 2 publications

References 18 publications

A Signal Characteristic Based Cluster Scheme for Aeronautical Ad Hoc Networks

A Signal Characteristic Based Cluster Scheme for Aeronautical Ad Hoc Networks

An efficient routing protocol for the QoS support of large‐scale MANETs

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