Distributed Algorithm for Efficient Construction and Maintenance of Connected k-Hop Dominating Sets in Mobile Ad Hoc Networks

2008 ◽  
Vol 7 (4) ◽  
pp. 444-457 ◽  
Author(s):  
Hong-Yen Yang ◽  
Chia-Hung Lin ◽  
Ming-Jer Tsai
Keyword(s):  
Ad Hoc Networks ◽  
Mobile Ad Hoc Networks ◽  
Distributed Algorithm ◽  
Ad Hoc ◽  
Dominating Sets ◽  
Efficient Construction ◽  
Mobile Ad Hoc ◽  
Hoc Networks

Algorithms to Determine Stable Connected Dominating Sets for Mobile Ad Hoc Networks

2014 ◽  
pp. 249-274 ◽  
Author(s):  
Natarajan Meghanathan
Keyword(s):  
Ad Hoc Networks ◽  
Mobile Ad Hoc Networks ◽  
Ad Hoc ◽  
Stability Index ◽  
Dominating Sets ◽  
Connected Dominating Sets ◽  
Mobile Ad Hoc ◽  
Hoc Networks ◽  
The Stability ◽  
Node Size

This chapter presents three algorithms to determine stable connected dominating sets (CDS) for wireless mobile ad hoc networks (MANETs) whose topology changes dynamically with time. The three stability-based CDS algorithms are (1) Minimum Velocity (MinV)-based algorithm, which prefers to include a slow moving node as part of the CDS as long as it covers one uncovered neighbor node; (2) Node Stability Index (NSI)-based algorithm, which characterizes the stability of a node as the sum of the predicted expiration times of the links (LET) with its uncovered neighbor nodes, the nodes preferred for inclusion to the CDS in the decreasing order of their NSI values; (3) Strong Neighborhood (SN)-based algorithm, which prefers to include nodes that cover the maximum number of uncovered neighbors within its strong neighborhood (region identified by the Threshold Neighborhood Ratio and the fixed transmission range of the nodes). The three CDS algorithms have been designed to capture the node size—lifetime tradeoff at various levels. In addition to presenting a detailed description of the three stability-based CDS algorithms with illustrative examples, the authors present an exhaustive simulation study of these algorithms and compare their performance with respect to several metrics vis-à-vis an unstable maximum density-based MaxD-CDS algorithm that serves as the benchmark for the minimum CDS Node Size.

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