A tree-based algorithm for distributed mutual exclusion
ACM Transactions on Computer Systems (TOCS)
Compression of correlated bit-vectors
Information Systems
Computers and Operations Research
Approximation algorithms for facility location problems (extended abstract)
STOC '97 Proceedings of the twenty-ninth annual ACM symposium on Theory of computing
Approximation schemes for Euclidean k-medians and related problems
STOC '98 Proceedings of the thirtieth annual ACM symposium on Theory of computing
Greedy strikes back: improved facility location algorithms
Journal of Algorithms
Analysis of a local search heuristic for facility location problems
Proceedings of the ninth annual ACM-SIAM symposium on Discrete algorithms
Approximating the weight of shallow Steiner trees
Discrete Applied Mathematics
Distributed Operating Systems and Algorithms
Distributed Operating Systems and Algorithms
Improved Approximation Algorithms for Metric Facility Location Problems
APPROX '02 Proceedings of the 5th International Workshop on Approximation Algorithms for Combinatorial Optimization
Proceedings of the 2003 ACM symposium on Applied computing
IPDPS '05 Proceedings of the 19th IEEE International Parallel and Distributed Processing Symposium (IPDPS'05) - Workshop 12 - Volume 13
Approximating k-hop minimum-spanning trees
Operations Research Letters
| Hi-index | 5.23 |
The d-Dimh-hops MST problem is defined as follows: given a set S of points in the d-dimensional Euclidean space and sεS, find a minimum-cost spanning tree for S rooted at s with height at most h. We investigate the problem for any constant h and d 0. We prove the first nontrivial lower bound on the solution cost for almost all Euclidean instances (i.e. the lower bound holds with high probability). Then we introduce an easy-to-implement, fast divide et impera heuristic and we prove that its solution cost matches the lower bound.