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A cost-oriented approach for infrastructural design
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Source Symposium on Applied Computing archive
Proceedings of the 2004 ACM symposium on Applied computing table of contents
Nicosia, Cyprus
SESSION: Parallel and distributed systems (PDS) table of contents
Pages: 1431 - 1437  
Year of Publication: 2004
ISBN:1-58113-812-1
Authors
Danilo Ardagna  Politecnico di Milano, Milano, Italy
Chiara Francalanci  Politecnico di Milano, Milano, Italy
Marco Trubian  Università degli Studi di Milano, Milano, Italy
Sponsor
SIGAPP: ACM Special Interest Group on Applied Computing
Publisher
ACM  New York, NY, USA
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ABSTRACT

The selection of a cost-minimizing combination of hardware and network components that satisfy organizational requirements is a complex design problem with multiple degrees of freedom. Decisions must be made on how to distribute the overall computing load onto multiple computers, where to locate computers and how to take advantage of legacy components. The corresponding optimization problem not only embeds the structure of NP-hard problems, but also represents a challenge with a well-structured heuristic approach. A scientific approach has been rarely applied to cost minimization and a rigorous methodological support to cost issues of infrastructural design is still lacking. The methodological contribution of this paper is the representation of complex infrastructural design issues as a single cost-minimization problem. The problem is decomposed in four interwined cost-minimization sub-prolems; optimization is accomplished by sequentially solving these sub-problems with a heuristic approach and tuning their solution with a final tabusearch step. Results indicate that decomposition significantly reduces optimization time and solutions are also closer to the global optimum if results are compared to those identified without prior decomposition. Cost reductions are also significant when practicioners' solutions, obtained by applying simplified design rules from the professional literature, are considered.


REFERENCES

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Collaborative Colleagues:
Danilo Ardagna: colleagues
Chiara Francalanci: colleagues
Marco Trubian: colleagues

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