A Mathematical Optimization Approach To Improve Server Scalability In Intermittently Synchronized Databases

Abstract

This paper addresses a scalability problem in the process of synchronizing the states of multiple client databases which only have deferred access to the server. It turns out that the process of client update file generation is not scalable with the number of clients served. In this paper we concentrate on developing an optimization model to address the scalability problem at the server by aiming for an optimal grouping of data fragments at the server given the "interest sets" of the clients - the set of fragments the client deals with for its"local" processing. The objective is to minimize the total cost of server operation which includes processing updates from all clients and transmission cost of sending the right set of updates to each client based on the client's interest set. An integer programming formulation is developed and solved with an illustrative problem, yielding interesting results.