Data structures and network algorithms
Data structures and network algorithms
Complexity of network synchronization
Journal of the ACM (JACM)
A new approach to the maximum-flow problem
Journal of the ACM (JACM)
An O(n2 log n) parallel max-flow algorithm
Journal of Algorithms
Linear programming and network flows (2nd ed.)
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Can a maximum flow be computed in o(nm) time?
Proceedings of the seventeenth international colloquium on Automata, languages and programming
Self-stabilization of dynamic systems assuming only read/write atomicity
PODC '90 Proceedings of the ninth annual ACM symposium on Principles of distributed computing
Token management schemes and random walks yield self-stabilizing mutual exclusion
PODC '90 Proceedings of the ninth annual ACM symposium on Principles of distributed computing
Information Processing Letters
Some recent advances in network flows
SIAM Review
A self-stabilizing algorithm for constructing spanning trees
Information Processing Letters
SFCS '91 Proceedings of the 32nd annual symposium on Foundations of computer science
A self-stabilizing algorithm for constructing breadth-first trees
Information Processing Letters
ACM Computing Surveys (CSUR)
Leader election in uniform rings
ACM Transactions on Programming Languages and Systems (TOPLAS)
Self-stabilizing depth-first search
Information Processing Letters
Self-stabilizing algorithms for finding centers and medians of trees
PODC '94 Proceedings of the thirteenth annual ACM symposium on Principles of distributed computing
An exercise in fault-containment: self-stabilizing leader election
Information Processing Letters
Memory requirements for silent stabilization
PODC '96 Proceedings of the fifteenth annual ACM symposium on Principles of distributed computing
Fault-containing self-stabilizing algorithms
PODC '96 Proceedings of the fifteenth annual ACM symposium on Principles of distributed computing
Theoretical Improvements in Algorithmic Efficiency for Network Flow Problems
Journal of the ACM (JACM)
Fault-containing network protocols
SAC '97 Proceedings of the 1997 ACM symposium on Applied computing
Self-stabilizing systems in spite of distributed control
Communications of the ACM
EFFICIENT GRAPH ALGORITHMS FOR SEQUENTIAL AND PARALLEL COMPUTERS
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A self-stabilizing algorithm for coloring planar graphs
Distributed Computing - Special issue: Self-stabilization
Messages, Clocks, and Gravitation
CEEMAS '01 Revised Papers from the Second International Workshop of Central and Eastern Europe on Multi-Agent Systems: From Theory to Practice in Multi-Agent Systems
Distributed algorithms for secure multipath routing in attack-resistant networks
IEEE/ACM Transactions on Networking (TON)
A self-stabilizing algorithm for the median problem in partial rectangular grids and their relatives
SIROCCO'07 Proceedings of the 14th international conference on Structural information and communication complexity
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Computer Networks: The International Journal of Computer and Telecommunications Networking
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The maximum flow problem is a fundamental problem in graph theory and combinatorial optimization with a variety of important applications. Known distributed algorithms for this problem do not tolerate faults or adjust to dynamic changes in network topology. This paper presents a distributed self-stabilizing algorithm for the maximum flow problem. Starting from an arbitrary state, the algorithm computes the maximum flow in an acyclic network in finitely many steps. Since the algorithm is self-stabilizing, it is inherently tolerant to transient faults. It can automatically adjust to topology changes and to changes in other parameters of the problem. The paper presents results obtained by extensively experimenting with the algorithm. Two main observations based on these results are (1) the algorithm requires fewer than n2 moves for almost all test cases and (2) the algorithm consistently performs at least as well as a distributed implementation of the well-known Goldberg-Tarjan algorithm for almost all test cases. The paper ends with the conjecture that the algorithm correctly computes a maximum flow even in networks that contain cycles.