Copyright © 2002 Elsevier Science B.V. All rights reserved.
An efficient algorithm for finding a path subject to two additive constraints
Received 26 June 2000;
Abstract
One of the key issues in providing end-to-end quality-of-service (QoS) guarantees in packet networks is how to determine a feasible path that satisfies a number of QoS constraints. For two or more additive constraints, the problem of finding a feasible path is NP-complete that cannot be exactly solved in polynomial time. Accordingly, several heuristics and approximation algorithms have been proposed for this problem. Many of these algorithms suffer from either excessive computational cost or low performance. In this paper, we provide an efficient approximation algorithm for finding a path subject to two additive constraints. The worst-case computational complexity of this algorithm is within a logarithmic number of calls to Dijkstra's shortest path algorithm. Its average complexity is even much lower than that, as demonstrated by simulation experiments. The performance of the proposed algorithm is justified via theoretical bounds that are provided for the optimal version of the path selection problem. To achieve further performance improvement, several extensions to the basic algorithm are also provided at very low computational cost. Extensive simulations are used to demonstrate the high performance of the proposed algorithm and to contrast it with other path selection algorithms.
Author Keywords: Path selection; Additive constraints; QoS routing; Lagrangian techniques
Article Outline
- 1. Introduction
- 2. Hierarchical shortest path algorithm
- 3. Basic approximation algorithm for CPS
- 3.1. How the algorithm works
- 3.2. Binary search
- Performance boundsLemma 2. If the binary search fails to return a feasible path w.r.t. both the constraints, then it returns a path p that satisfies the constraint cj and whose wi( ) cost is upper bounded as follows:where f is a feasible path, k is the maximum value that the binary search determines at termination, and the pair (i,j) is either (1,2) or (2,1), depending on the phase.wi(p)≤wi(f)+(wj(f)−wj(p))/k
- 4. Extensions of the basic algorithm
- 5. Simulation results and discussion
- 5.1. Simulation model and performance measures
- 5.2. Results under homogeneous link weights
- 5.3. Performance under heterogeneous links
- 6. Conclusions and future work
- Acknowledgements
- References
Corresponding author. Tel.: +1-520-621-8731; fax: +1-520-621-3862; email: turgay@ece.arizona.edu






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