Multi-objective optimization of IT service availability and costs

• A redundancy allocation problem for IT service design, the ITRAP, is developed.
• Petri net Monte Carlo simulation and meta-heuristics are used for optimization.
• Inter-component dependencies and defective operator interaction can be modeled.
• The ITRAP overcomes the assumption of independent component failures.
• A use case experiment demonstrates that the ITRAP provides more realistic results.

The continuous provision of highly available IT services is a crucial task for IT service providers in order to fulfill service level agreements with customers. Although the introduction of redundant components increases availability, the associated cost may be very high. Therefore, decision makers in the IT service design stage face a trade-off between cost and availability in order to define suitable service level objectives. Although this task can be seen as a redundancy allocation problem, the existing definitions in this area are not transferable to IT service design due to the assumption of independent component failures, which has been identified as unrealistic in IT systems.In this paper, a multi-objective redundancy allocation problem for IT service design is defined. Therefore, a Petri net Monte Carlo simulation is developed that estimates the availability and costs of a specific design. In order to provide (sub)optimal solutions to an IT service redundancy allocation problem, two meta-heuristics, namely a genetic algorithm and tabu search, are adapted. The approach is utilized to optimize the IT service design of an application service provider in terms of availability and cost to demonstrate its feasibility and suitability.