Preprint Article Version 1 This version is not peer-reviewed

Distance-Vector Algorithms for Distributed Shortest Paths on Dynamic Power-Law Networks

Version 1 : Received: 27 July 2017 / Approved: 28 July 2017 / Online: 28 July 2017 (06:06:35 CEST)

How to cite: D'Emidio, M.; Frigioni, D. Distance-Vector Algorithms for Distributed Shortest Paths on Dynamic Power-Law Networks. Preprints 2017, 2017070081 (doi: 10.20944/preprints201707.0081.v1). D'Emidio, M.; Frigioni, D. Distance-Vector Algorithms for Distributed Shortest Paths on Dynamic Power-Law Networks. Preprints 2017, 2017070081 (doi: 10.20944/preprints201707.0081.v1).

Abstract

Efficiently solving the problem of computing, in a distributed fashion, the shortest paths of a graph whose topology dynamically changes over time is a core functionality of many today’s digital infrastructures, probably the most prominent example being communication networks. Many solutions have been proposed over the years for this problem that can be broadly classified into two categories, namely Distance-Vector and Link-State algorithms. Distance-Vector algorithms are widely adopted solutions when scalability and reliability are key issues or when nodes have either limited hardware resources, as they result in being very competitive approaches in terms of both the memory and the computational point of view. In this paper, we first survey some of the most established solutions of the Distance-Vector category. Then, we discuss some recent algorithmic developments in this area. Finally, we propose a new experimental study, conducted on a prominent category of network instances, namely generalized linear preference (GLP) power-law networks, to rank the performance of such solutions.

Subject Areas

dynamic algorithms; distributed shortest paths; communication networks; routing protocols; power-law networks

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