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Link Reversal Algorithms [Mīkstie vāki]

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Link reversal is a versatile algorithm design technique that has been used in numerous distributed algorithms for a variety of problems. The common thread in these algorithms is that the distributed system is viewed as a graph, with vertices representing the computing nodes and edges representing some other feature of the system (for instance, point-to-point communication channels or a conflict relationship). Each algorithm assigns a virtual direction to the edges of the graph, producing a directed version of the original graph. As the algorithm proceeds, the virtual directions of some of the links in the graph change in order to accomplish some algorithm-specific goal. The criterion for changing link directions is based on information that is local to a node (such as the node having no outgoing links) and thus this approach scales well, a feature that is desirable for distributed algorithms.

This monograph presents, in a tutorial way, a representative sampling of the work on link-reversal-based distributed algorithms. The algorithms considered solve routing, leader election, mutual exclusion, distributed queueing, scheduling, and resource allocation. The algorithms can be roughly divided into two types, those that assume a more abstract graph model of the networks, and those that take into account more realistic details of the system. In particular, these more realistic details include the communication between nodes, which may be through asynchronous message passing, and possible changes in the graph, for instance, due to movement of the nodes.

We have not attempted to provide a comprehensive survey of all the literature on these topics. Instead, we have focused in depth on a smaller number of fundamental papers, whose common thread is that link reversal provides a way for nodes in the system to observe their local neighborhoods, take only local actions, and yet cause global problems to be solved. We conjecture that future interesting uses of link reversal are yet to be discovered.
Acknowledgments ix
1 Introduction
1(4)
2 Routing in a Graph: Correctness
5(14)
2.1 Abstract Link Reversal
5(7)
2.2 Vertex Labels
12(3)
2.3 Link Labels
15(4)
3 Routing in a Graph: Complexity
19(18)
3.1 Work Complexity
19(10)
3.1.1 Vertex Labeling
19(1)
3.1.2 Link Labeling
20(6)
3.1.3 FR vs. PR with Game Theory
26(3)
3.2 Time Complexity
29(8)
3.2.1 Full Reversal
29(5)
3.2.2 General LR and Partial Reversal
34(3)
4 Routing and Leader Election in a Distributed System
37(8)
4.1 Distributed System Model for Applications
37(1)
4.2 Routing in Dynamic Graphs
38(5)
4.2.1 Overview of TORA
38(2)
4.2.2 Route Creation
40(1)
4.2.3 Route Maintenance
41(2)
4.2.4 Erasing Routes
43(1)
4.2.5 Discussion
43(1)
4.3 Leader Election in Dynamic Graphs
43(2)
5 Mutual Exclusion in a Distributed System
45(14)
5.1 Mutual Exclusion in Fixed Topologies
45(11)
5.1.1 LRME Algorithm
46(2)
5.1.2 Correctness of LRME Algorithm
48(8)
5.2 Mutual Exclusion for Dynamic Topologies
56(3)
6 Distributed Queueing
59(8)
6.1 The Arrow Protocol
59(1)
6.2 Correctness of Arrow
60(5)
6.3 Discussion
65(2)
7 Scheduling in a Graph
67(14)
7.1 Preliminaries
67(6)
7.2 Analysis for Trees
73(1)
7.3 Analysis for Non-Trees
74(5)
7.4 Discussion
79(2)
8 Resource Allocation in a Distributed System
81(6)
8.1 Chandy and Misra's Algorithm
82(1)
8.2 Correctness of Chandy and Misra's Algorithm
83(4)
9 Conclusion
87(2)
Bibliography 89(4)
Authors' Biographies 93