Deterministic coin tossing with applications to optimal parallel list ranking
Information and Control
Computing on an anonymous ring
Journal of the ACM (JACM)
Parallel symmetry-breaking in sparse graphs
SIAM Journal on Discrete Mathematics
SFCS '91 Proceedings of the 32nd annual symposium on Foundations of computer science
Locality in distributed graph algorithms
SIAM Journal on Computing
Linear programming without the matrix
STOC '93 Proceedings of the twenty-fifth annual ACM symposium on Theory of computing
A primal-dual parallel approximation technique applied to weighted set and vertex covers
Journal of Algorithms
SIAM Journal on Computing
Computing on Anonymous Networks: Part I-Characterizing the Solvable Cases
IEEE Transactions on Parallel and Distributed Systems
Self-stabilization
On the Distributed Complexity of Computing Maximal Matchings
SIAM Journal on Discrete Mathematics
An Effective Characterization of Computability in Anonymous Networks
DISC '01 Proceedings of the 15th International Conference on Distributed Computing
Local and global properties in networks of processors (Extended Abstract)
STOC '80 Proceedings of the twelfth annual ACM symposium on Theory of computing
Local computations on static and dynamic graphs
ISTCS '95 Proceedings of the 3rd Israel Symposium on the Theory of Computing Systems (ISTCS'95)
What cannot be computed locally!
Proceedings of the twenty-third annual ACM symposium on Principles of distributed computing
Some simple distributed algorithms for sparse networks
Distributed Computing
The price of being near-sighted
SODA '06 Proceedings of the seventeenth annual ACM-SIAM symposium on Discrete algorithm
Constant-time distributed dominating set approximation
Distributed Computing
Fault-Tolerant Clustering in Ad Hoc and Sensor Networks
ICDCS '06 Proceedings of the 26th IEEE International Conference on Distributed Computing Systems
Vertex cover might be hard to approximate to within 2-ε
Journal of Computer and System Sciences
Dynamic networks are as fast as static networks
SFCS '88 Proceedings of the 29th Annual Symposium on Foundations of Computer Science
Distributed weighted vertex cover via maximal matchings
ACM Transactions on Algorithms (TALG)
A simple local 3-approximation algorithm for vertex cover
Information Processing Letters
Distributed and parallel algorithms for weighted vertex cover and other covering problems
Proceedings of the 28th ACM symposium on Principles of distributed computing
A local 2-approximation algorithm for the vertex cover problem
DISC'09 Proceedings of the 23rd international conference on Distributed computing
Distributed algorithms for edge dominating sets
Proceedings of the 29th ACM SIGACT-SIGOPS symposium on Principles of distributed computing
Deterministic dominating set construction in networks with bounded degree
ICDCN'11 Proceedings of the 12th international conference on Distributed computing and networking
Analysing local algorithms in location-aware quasi-unit-disk graphs
Discrete Applied Mathematics
Distributed maximal matching: greedy is optimal
PODC '12 Proceedings of the 2012 ACM symposium on Principles of distributed computing
Lower bounds for local approximation
PODC '12 Proceedings of the 2012 ACM symposium on Principles of distributed computing
Weak models of distributed computing, with connections to modal logic
PODC '12 Proceedings of the 2012 ACM symposium on Principles of distributed computing
ACM Computing Surveys (CSUR)
Lower bounds for local approximation
Journal of the ACM (JACM)
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We present a distributed algorithm that finds a maximal edge packing in O(Δ + log* W) synchronous communication rounds in a weighted graph, independent of the number of nodes in the network; here Δ is the maximum degree of the graph and W is the maximum weight. As a direct application, we have a distributed 2-approximation algorithm for minimum-weight vertex cover, with the same running time. We also show how to find an $f$-approximation of minimum-weight set cover in O(f2k2 + fk log* W) rounds; here k is the maximum size of a subset in the set cover instance, f is the maximum frequency of an element, and W is the maximum weight of a subset. The algorithms are deterministic, and they can be applied in anonymous networks.