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An efficient algorithm for finding a path subject to two additive constraints
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Source Joint International Conference on Measurement and Modeling of Computer Systems archive
Proceedings of the 2000 ACM SIGMETRICS international conference on Measurement and modeling of computer systems table of contents
Santa Clara, California, United States
Pages: 318 - 327  
Year of Publication: 2000
ISBN:1-58113-194-1
Also published in ...
Authors
Turgay Korkmaz  Dept. of Elec. & Comp. Eng., University of Arizona, Tucson, AZ
Marwan Krunz  Dept. of Elec. & Comp. Eng., University of Arizona, Tucson, AZ
Spyros Tragoudas  Dept. of Elec. & Comp. Eng., Southern Illinois University, Carbondale, IL
Sponsor
SIGMETRICS: ACM Special Interest Group on Measurement and Evaluation
Publisher
ACM  New York, NY, USA
Bibliometrics
Downloads (6 Weeks): 6,   Downloads (12 Months): 36,   Citation Count: 12
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ABSTRACT

One of the key issues in providing end-to-end quality-of-service guarantees in packet networks is how to determine a feasible route that satisfies a set of constraints while simultaneously maintaining high utilization of network resources. In general, finding a path subject to multiple additive constraints (e.g., delay, delay-jitter) is an NP-complete problem that cannot be exactly solved in polynomial time. Accordingly, heuristics and approximation algorithms are often used to address to this problem. Previously proposed 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 much lower than that, as demonstrated by simulation results. The performance of the proposed algorithm is justified via theoretical performance bounds. To achieve further performance improvement, several extensions to the basic algorithm are also provided at low extra computational cost. Extensive simulations are used to demonstrate the high performance of the proposed algorithm and to contrast it with other path selection algorithms.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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CITED BY  12

Collaborative Colleagues:
Turgay Korkmaz: colleagues
Marwan Krunz: colleagues
Spyros Tragoudas: colleagues