Distributed computing: a locality-sensitive approach
Distributed computing: a locality-sensitive approach
Fast Distributed Approximations in Planar Graphs
DISC '08 Proceedings of the 22nd international symposium on Distributed Computing
Leveraging Linial's Locality Limit
DISC '08 Proceedings of the 22nd international symposium on Distributed Computing
Lower bounds for local approximation
PODC '12 Proceedings of the 2012 ACM symposium on Principles of distributed computing
ACM Computing Surveys (CSUR)
Brief announcement: a local approximation algorithm for MDS problem in anonymous planar networks
Proceedings of the 2013 ACM symposium on Principles of distributed computing
| Hi-index | 0.89 |
In recent years growing interest in local distributed algorithms has widely been observed. This results from their high resistance to errors and damage, as well as from their good performance, which is independent of the size of the network. A local deterministic distributed algorithm finding an approximation of a Minimum Dominating Set in planar graphs has been presented by Lenzen et al., and they proved that the algorithm returns a 130-approximation of the Minimum Dominating Set. In this article we will show that the algorithm is two times more effective than was previously assumed, and we prove that the algorithm by Lenzen et al. outputs a 52-approximation to a Minimum Dominating Set. Therefore the gap between the lower bound and the approximation ratio of the best yet local deterministic distributed algorithm is reduced by half.