Abstract
Providing Infrastructure as a Service ( <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">IaaS</i> ) is becoming increasingly competitive due to its growing world market. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">IaaS</i> requires significant physical resources, e.g., network connections, bandwidth, load balancers, and servers. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">IaaS</i> providers of any size and reach, but especially private and public regional ones, have to manage the capacity of their resources properly to reduce costs and meet other business goals. Comprehensive capacity management by <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">IaaS</i> providers involves objective and subjective analyses and it is thus, challenging. Complexity arises, for instance, as one tries to factor management behavior in analyses of business impact and infrastructure performance to produce indicators in support of interventions related to service capacity. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">IaaS</i> managers frequently rely on their own expertise, experience, and knowledge to identify whether an apparent capacity deficiency may be due to an infrastructure problem or to an unexpected demand burst. This article presents a business-driven simulation model based on System Dynamics (SD), Balanced Scorecard (BSC) and Analytic Hierarchy Process (AHP) concepts to support capacity management decisions by <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">IaaS</i> providers in real-life operating scenarios. A case study in a real-world, public regional <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">IaaS</i> provider illustrates the model’s support to non-trivial decisions that are aligned with managers’ experiences and business expectations.
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