Optimal Redesign Policies to Support Dynamic Processing of Applications on a Distributed Relational Database System

An application processing center consists of a set of well-de ned, well-designed and well-tested applications that are dynamically executed over a period of time. We assume that there is a set of candidate distributed database designs each of which is optimal for some applications. The random execution of applications on a distributed database design is modeled as a discrete Markov process, and the problem of selecting the candidate design for each execution of an application is solved by using sequential Markovian decision process analysis to generate an optimal redesign policy vector. The scope of the methodology developed in this paper is applicable to environments similar to application processing centers. The viability of this methodology is illustrated by means of a case study conducted at Georgia Tech.