Practical Heterogeneous Placeholder Scheduling in Overlay Metacomputers: Early Experiences
JSSPP '02 Revised Papers from the 8th International Workshop on Job Scheduling Strategies for Parallel Processing
A Parallel FPT Application For Clusters
CCGRID '03 Proceedings of the 3st International Symposium on Cluster Computing and the Grid
On efficient fixed-parameter algorithms for weighted vertex cover
Journal of Algorithms
Solving large FPT problems on coarse-grained parallel machines
Journal of Computer and System Sciences - Special issue on Parameterized computation and complexity
Refined memorization for vertex cover
Information Processing Letters
Scalable Parallel Algorithms for FPT Problems
Algorithmica
Improved parameterized upper bounds for vertex cover
MFCS'06 Proceedings of the 31st international conference on Mathematical Foundations of Computer Science
Parameterized Complexity
Hi-index | 0.00 |
We present the first investigation of the well-known memorization technique for solving the k-Vertex Cover problem in a distributed setting. Memorization was introduced by Robson [15] in his paper on solving the Maximum Independent Set problem. The idea is to augment a recursive algorithm with the capability to store subproblem instances and solutions of bounded size in a table that can be quickly referenced, so that subproblems are guaranteed to be solved exactly once. This approach has recently been applied with success to improve the complexity of the fixed-parameter tractable algorithms for solving the k-Vertex Cover problem [12,5]. We present a general parallel approach for using memorization to solve the k-Vertex Cover problem where the subgraphs are precomputed [12]. In this case, the subgraphs and corresponding solutions are generated in a preprocessing step, rather than during the recursion. Our technique makes efficient use of the processors generating the lookup table, while at the same time requiring less space. We describe a distributed algorithm using this technique, well-suited to cluster or grid computing platforms.