department of informatics

Usage planning of flexible computing systems applying fuzzy mechanism


IT spending that is based on fix quantities does not always get aligned to actual demand and needed service levels. Customers who utilize flexible computing capacities expect to pay only for the amount of capacity that they really needed and used at a specific point in time. In order to pass this flexibility on to agreements with the customer also powerful capacity analysis and planning instruments are necessary. For a reasonably large server farm these instruments also produce large amounts of data. This data consists of actual usage data, as well as internal monitoring data. Usage data describes information on how much computing was actually by a specific host while monitoring data describes internal data that accumulate during operation of the server farm such as logs on maintenance processes or access logs.

Using these types of data, we can not only derive bills for customers, but can also recommend on optimal planning and booking of capacity baselines with regard to the evolving market and business needs, financial aspects and pricing models, the current state of  the server farm and the historical usage data.

Usage and capacity planning based on sales- or business trends are front-end requirements and business measures which require a complex and composed service model to deliver the planned service level agreements (SLAs). To guarantee business-focused SLAs with constantly changing and evolving usage requirements results in optimization problem solving across multiple domains (e.g. networking, computer systems, and software engineering). The landscape of today's IT service providers is inherently integrated. It consists of all kinds of elements, namely networks, servers, storage, and software stacks. The fulfilment of any higher-level objective requires proper enforcements on multiple resources at several levels.

This diploma thesis will help to predict the impact and relationships of an evolving business demand to the backend components to guarantee the SLAs of the end-user service whilst changing usage needs. The proposed IFCFIA framework at Information Systems Research Group Department of Informatics / University of Fribourg, will allow for implementing a flexible capacity model in a hosting environment based on business planning and market trends where the organization benefits by optimized investments in the IT infrastructure and capacity levels. This thesis can be the basis for a future capacity recommendation and planning system.

This work will include both, conceptual analysis (fuzzy logic and business related evaluation) as well as technical implementation aspects using IBM SW products, the Tivoli Usage and Account Manager (TUAM) and partly Tivoli Application Dependency & Discovery Manager (TADDM).

This student project can be primarily done in Fribourg, Suisse but includes also an on-site practical part at IBM Germany in Ehningen (near Stuttgart) and can also combined/extended with a local practicum.

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[Joshi et al. 2009] Joshi, Karuna; Joshi, Anupam; Yesha, Yelena; Kothari, Ravi: A Framework for Relating Frontstage and Backstage Quality in Virtualized Services. Available:, accessed 25thMarch 2012.

[Tai et al. 2008] Tai, Ling; Baker, Ron; Edmiston, Elizabeth; Jeffcoat, Ben: IBM Tivoli Common Data Model: Guide to Best Practices. Available:, accessed 25thMarch 2012.

[Schönefeld 1996] Schönefeld, Marc: Entwurf und Realisierung einer auf Fuzzy-Logik basierenden Entscheidungskomponente zur Integration in eine Workflow-Entwicklungsumgebung. Available:, accessed 25th March 2012.

 [Kolev/Ivanov 2009] Kolev, Boyan; Ivanov Ivaylo: Fault Tree Analysis in an Intuitionistic Fuzzy Configuration Management Database. Available:, accessed 25th March 2012.

 [Jacob et al. 2009] Jacob, Bart; Adhia, Bhavesh; Badr, Karim; Huang, Qing Chun; Lawrence, Carol S.; Marino, Martin; Unglaub-Lloyd, Petra: IBM Tivoli Application Dependency Discovery Manager: Capabilities and Best Practices. Available:, accessed: 25th March 2012.

 [Robinson/Buros 2007] Robinson, David; Buros, Karen: Using the Data Model to display data in TADDM.

Available:, accessed 25th March 2012.

 [Rinaldi et al. 2001] Rinaldi, Steven M.; Peerenboom, James P.; Kelly, Terrence K.: Identifying, Understanding, and Analyzing Critical Infrastructure Interdependencies. Available:, accessed 25th March 2012.

 Atanassov K. On Intuitionistic Fuzzy Sets Theory (Studies in Fuzziness and Soft Computing) Springer Berlin Heidelberg; 1st ed. 1999 Edition: 2010