Abstract
Operations of modern organizations critically depend on Data Centers (DC). Due to ad hoc additions from diverse business units over time, the IT resources in a DC get unwieldy and complex. Transformations of DC - server consolidation, migration, application/data simplification, technology standardization - are important for cost, efficiency and reliability. Even when a specific transformation is identified (“consolidate these 100 existing servers into these 48 new servers”) it is difficult to generate a detailed optimal project plan for its execution. The project plan must identify all the tasks involved, identify an optimal team (size and expertise) and generate a detailed work schedule that meets the and respects the constraints and dependencies among the tasks. We present a methodology to generate such a plan automatically from given ”high-level” IT transformation specifications (“as-is” and “to-be” states). We adopt a heuristic forward chaining metric temporal planner engine (SAPA) to generate a project plan that attempts to optimize the overall time and team-size. The idea is to capture the domain-knowledge as reusable planning action. This automation reduces the efforts and errors in manual project planning. The method can be extended to projects in other domains.
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Ahuja, A.L., Palshikar, G.K. (2012). Generating Project Plans for Data Center Transformations. In: Thielscher, M., Zhang, D. (eds) AI 2012: Advances in Artificial Intelligence. AI 2012. Lecture Notes in Computer Science(), vol 7691. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-35101-3_65
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DOI: https://doi.org/10.1007/978-3-642-35101-3_65
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