An Economics-Driven Approach for Valuing Scalability in Distributed Architectures

Drawing on a case study that adequately represents a medium-size component-based distributed architecture, the contribution of this paper shows how existing performance repositories could be mined to value the ranges in which a given software architecture can scale to support likely changes in load. The mining is based on a financial analogy, where we utilize the concept of twin asset in financial engineering to justify mining relevant repositories. The mining process in then complemented with real options analysis for predicting the values resulted from the ranges in which an architecture can scale under uncertainty, where uncertainty is attributed to the unpredicted change in load. As the exact method for analyzing scalability is subject to debate, we focus the analysis on throughput as a way for measuring scalability. Using options analysis, we report on how ranges in which an architecture can scale, can inform the selection of distributed components technology and subsequently the selection of application server products.