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IEEE Transactions on Communications
Article . 1988 . Peer-reviewed
License: IEEE Copyright
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image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
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A k shortest path algorithm for adaptive routing in communications networks

Authors: D.M. Topkis;

A k shortest path algorithm for adaptive routing in communications networks

Abstract

The problem of finding k shortest loopless paths with distinct initial links from one node to each other node arises in several important contexts for adaptive routing in communication networks. One context is the construction or adaptive reconstruction of routing tables where a sequential routing algorithm is used, and another context is ``delta routing''. This paper presents an efficient and flexible algorithm for this k shortest path problem. Low-order polynomial bounds are established for the worst case time complexity of the algorithm, showing it to offer a substantial improvement over applying known algorithms to the problem. The algorithm can incorporate various extensions, including the ability to handle an algebraic objective, which enhance its applicability to diverse network models. In addition, the present k shortest path formulation and algorithm are proposed as a basis for network survivability measures where path length bounds exist.

Related Organizations
Keywords

network survivability measures, Deterministic scheduling theory in operations research, delta routing, Analysis of algorithms and problem complexity, Programming involving graphs or networks, shortest loopless paths, adaptive routing, Deterministic network models in operations research, communication networks, Low-order polynomial bounds, worst case time complexity

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    citations
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    71
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
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    Top 1%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
71
Top 10%
Top 1%
Top 10%
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