A randomized algorithm for finding a path subject to multiple QoS requirements

An important aspect of quality-of-service (QoS) provisioning in integrated networks is the ability to find a feasible route that satisfies a set of end-to-end QoS requirements (or constraints) while efficiently using network resources. In general, finding a path subject to multiple additive constrai...

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Bibliographic Details
Published in:Computer networks (Amsterdam, Netherlands : 1999) Vol. 36; no. 2; pp. 251 - 268
Main Authors: Korkmaz, Turgay, Krunz, Marwan
Format: Journal Article
Language:English
Published: Amsterdam Elsevier B.V 01.07.2001
Elsevier Sequoia S.A
Subjects:
Algorithms
Constraints
Heuristic
Jitter
Multi-constrained path selection
Networks
QoS-based routing
Quality of service
Routing
Scalable routing
Selection
Studies
QoS-based routing
Scalable routing
Multi-constrained path selection
ISSN:1389-1286, 1872-7069
Online Access:Get full text
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Summary:An important aspect of quality-of-service (QoS) provisioning in integrated networks is the ability to find a feasible route that satisfies a set of end-to-end QoS requirements (or constraints) while efficiently using network resources. In general, finding a path subject to multiple additive constraints (e.g., delay, delay-jitter) is an NP-complete problem. We propose an efficient randomized heuristic algorithm to this problem. Although the algorithm is presented as a centralized one, the idea behind it can also be implemented in a distributed manner. Our algorithm initially computes the cost of the best path from each node to a given destination with respect to individual link weights and their linear combination. In this initialization step, Reverse–Dijkstra's algorithm is used K+1 times per path request, where K is the number of additive constraints. The algorithm then randomly traverses the graph, discovering nodes from which there is a good chance of reaching the final destination. This randomized search is a modification of the breadth-first search (BFS). Using extensive simulations, we show that the proposed algorithm provides better performance than existing algorithms under the same order of computational complexity.
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ISSN:1389-1286
1872-7069
DOI:10.1016/S1389-1286(00)00209-7