Size-restricted cluster formation and cluster maintenance technique for mobile ad hoc networks

2007 ◽  
Vol 17 (2) ◽  
pp. 171-194 ◽  
Author(s):  
Gayathri Venkataraman ◽  
Sabu Emmanuel ◽  
Srikanthan Thambipillai
Keyword(s):  
Ad Hoc Networks ◽  
Mobile Ad Hoc Networks ◽  
Ad Hoc ◽  
Cluster Formation ◽  
Mobile Ad Hoc ◽  
Hoc Networks ◽  
Cluster Maintenance

scholarly journals A mobility-based cluster formation algorithm for wireless mobile ad-hoc networks

2011 ◽  
Vol 14 (4) ◽  
pp. 311-324 ◽  
Author(s):  
Javad Akbari Torkestani ◽  
Mohammad Reza Meybodi
Keyword(s):  
Ad Hoc Networks ◽  
Mobile Ad Hoc Networks ◽  
Ad Hoc ◽  
Cluster Formation ◽  
Mobile Ad Hoc ◽  
Hoc Networks ◽  
Wireless Mobile

Cluster Maintenance in Mobile Ad-hoc Networks

2005 ◽  
Vol 8 (2-3) ◽  
pp. 111-118 ◽  
Author(s):  
Lan Wang ◽  
Stephan Olariu
Keyword(s):  
Ad Hoc Networks ◽  
Mobile Ad Hoc Networks ◽  
Ad Hoc ◽  
Mobile Ad Hoc ◽  
Hoc Networks ◽  
Cluster Maintenance

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

2017 ◽  
Vol 13 (6) ◽  
pp. 155014771771681 ◽  
Author(s):  
Masood Ahmad ◽  
Ataul Aziz Ikram ◽  
Rabo Lela ◽  
Ishtiaq Wahid ◽  
Riaz Ulla
Keyword(s):  
Ad Hoc Networks ◽  
Mobile Ad Hoc Networks ◽  
Honey Bee ◽  
Ad Hoc ◽  
Cluster Formation ◽  
Optimization Scheme ◽  
Bee Algorithm ◽  
Honey Bee Algorithm ◽  
Mobile Ad Hoc ◽  
Hoc Networks

Multi-Purpose DS-Based Cluster Formation and Management in Mobile Ad Hoc Networks

2011 ◽  
pp. 1-20
Author(s):  
V. S. Anitha ◽  
M. P. Sebastian
Keyword(s):  
Load Balancing ◽  
Ad Hoc Networks ◽  
Mobile Ad Hoc Networks ◽  
Ad Hoc ◽  
Dominating Set ◽  
Cluster Formation ◽  
Mobile Ad Hoc ◽  
Hoc Networks ◽  
The Stability

This chapter proposes a scenario-based and diameter-bounded algorithm for cluster formation and management in mobile ad hoc networks (MANETs). A (k, r) -Dominating Set is used for the selection of clusterheads and gateway nodes depending on the topology of the network. Here k is the minimum number of clusterheads per node in the network and r is the maximum number of hops between the node and the clusterhead. The non-clusterhead node selects the most qualified dominating node as its clusterhead from among the k dominating nodes. The quality of the clusterhead is a function of various metrics, which include connectivity, stability and residual battery power. The long-term service as a clusterhead depletes its energy, causing it to drop out of the network. Similarly, the clusterhead with relatively high mobility than its neighbors leads to frequent clusterhead election process. This perturbs the stability of the network and can adversely affect the network performance. Load balancing among the clusterheads and correct positioning of the clusterhead in a cluster are vital to increase the lifespan of a network. The proposed centralized algorithm periodically calculates the quality of all dominating nodes in the network and if it goes below the threshold level it resigns the job as the clusterhead and sends this message to all other members in the cluster. Since these nodes have k dominating nodes within the r -hop distance, it can choose the current best-qualified node as its clusterhead. Simulation experiments are conducted to evaluate the performance of the algorithm in terms of the number of elements in the (k, r)-DS, the load balancing factor, the number of re-affiliations per unit time and the number of dominating set updates per unit time. The results establish the potential of this algorithm for use in MANETs.

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