NLWCA Node and Link Weighted Clustering Algorithm for Backbone-Assisted Mobile Ad Hoc Networks

2008 ◽  
Author(s):  
Adrian Andronache ◽  
Steffen Rothkugel
Keyword(s):  
Ad Hoc Networks ◽  
Mobile Ad Hoc Networks ◽  
Clustering Algorithm ◽  
Ad Hoc ◽  
Weighted Clustering ◽  
Mobile Ad Hoc ◽  
Hoc Networks

scholarly journals A Robust Clustering Algorithm for Mobile Ad-Hoc Networks

2010 ◽  
pp. 187-200 ◽  
Author(s):  
Zhaowen Xing ◽  
Le Gruenwald ◽  
K.K. Phang
Keyword(s):  
Ad Hoc Networks ◽  
Mobile Ad Hoc Networks ◽  
Clustering Algorithm ◽  
Ad Hoc ◽  
Clustering Algorithms ◽  
Cluster Head ◽  
Robust Clustering ◽  
Weighted Clustering ◽  
Mobile Ad Hoc ◽  
Hoc Networks

To mimic the operations in fixed infrastructures and to solve the routing scalability problem in large Mobile Ad Hoc Networks (MANET), forming clusters of nodes has been proven to be a promising approach. However, when existing weighted clustering algorithms calculate each node’s weight, they either consider only one metric or rely on some metrics collected from extra devices. This often leads to a higher rate of re-clustering. This chapter presents a robust weighted clustering algorithm, called PMW (Power, Mobility and Workload), to form and maintain more stable clusters. In PMW, the weight of each node is calculated by its power, mobility and workload, which can be easily collected and computed locally and cover the major factors that cause re-clustering. Clustering overhead of PMW is analyzed. The simulation results confirm that PMW prolongs lifetime of MANETs and has a lower cluster head change rate and re-affiliation rate than other existing algorithms.

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