A threshold of ln n for approximating set cover
Journal of the ACM (JACM)
On calculating connected dominating set for efficient routing in ad hoc wireless networks
DIALM '99 Proceedings of the 3rd international workshop on Discrete algorithms and methods for mobile computing and communications
Computers and Intractability; A Guide to the Theory of NP-Completeness
Computers and Intractability; A Guide to the Theory of NP-Completeness
An efficient distributed algorithm for constructing small dominating sets
Distributed Computing - Special issue: Selected papers from PODC '01
Distributed Clustering for Ad Hoc Networks
ISPAN '99 Proceedings of the 1999 International Symposium on Parallel Architectures, Algorithms and Networks
Distributed construction of connected dominating set in wireless ad hoc networks
Mobile Networks and Applications - Discrete algorithms and methods for mobile computing and communications
An Extended Localized Algorithm for Connected Dominating Set Formation in Ad Hoc Wireless Networks
IEEE Transactions on Parallel and Distributed Systems
Constant-time distributed dominating set approximation
Distributed Computing
LATIN'08 Proceedings of the 8th Latin American conference on Theoretical informatics
A PTAS for the minimum dominating set problem in unit disk graphs
WAOA'05 Proceedings of the Third international conference on Approximation and Online Algorithms
Local construction of planar spanners in unit disk graphs with irregular transmission ranges
LATIN'06 Proceedings of the 7th Latin American conference on Theoretical Informatics
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Several researchers have considered using a routing backbone to perform routing in a wireless ad hoc network. Such a backbone can be created by finding a connected dominating set (CDS) in the underlying graph. We present a new distributed local algorithm to find a CDS in a unit disk graph (UDG), which is a commonly used model for ad hoc wireless networks. We assume that the nodes have information about their locations. The CDS produced by our algorithm is provably at most a constant times the size of the optimal CDS. We evaluate the performance of our algorithm in comparison with previously proposed algorithms in [6],[7],[15] and [17] via extensive simulations on randomly generated UDGs. Our results show that the CDS produced by our algorithm is 25% better than the next-best algorithm (which is however not local), and 28% better than the next-best local algorithm. Our algorithm is also computationally efficient and highly scalable.