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Concepts, Theory, and Techniques DISTRIBUTED COMPUTER SYSTEM DESIGN: A MULTICRITERIA DECISION‐MAKING METHODOLOGY *
Author(s) -
Jain Hemant K.,
Dutta Amitava
Publication year - 1986
Publication title -
decision sciences
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.238
H-Index - 108
eISSN - 1540-5915
pISSN - 0011-7315
DOI - 10.1111/j.1540-5915.1986.tb00237.x
Subject(s) - computer science , heuristic , operations research , isolation (microbiology) , process (computing) , decision support system , compromise , management science , mathematical optimization , industrial engineering , data mining , artificial intelligence , engineering , mathematics , social science , microbiology and biotechnology , sociology , biology , operating system
The design of distributed computer systems (DCSs) requires compromise among several conflicting objectives. For instance, high system availability conflicts with low cost which in turn conflicts with quick response time. This paper presents an approach, based on multi‐criteria decision‐making techniques, to arrive at a good design in this multiobjective environment. An interactive procedure is developed to support the decision making of system designers. Starting from an initial solution, the procedure presents a sequence of non‐dominated vectors to designers, allowing them to explore systematically alternative possibilities on the path to a final design. The model user has control over trade‐offs among different design objectives. This paper focuses on the details of the mathematical model used to provide decision support. Accordingly, a formulation of DCS design as a multicriteria decision problem is developed. The exchange search heuristic used to generate nondominated solutions also is presented. We argue that multicriteria models provide a more realistic formulation of the DCS design problem than the single‐criterion models used widely in the literature. While obtaining a clear definition of design objectives (single or multiple) is an important activity, by explicitly acknowledging the trade‐offs among multiple objectives in the design process, our methodology is more likely to produce a better overall design than methods addressing a single criterion in isolation.