Utility-based models and decision making problems for selected network processes

Purpose – The concept of utility was the first time applied in Economics. The paper reports its usefulness for the decision making in complex technological systems, in general and in computer networks, in particular. Three selected decision making problems are considered, corresponding solution algorithms are explained and results of numerical experiments are presented for the selected real-world case study. Design/methodology/approach – Referring to similar decision making problems in Economics, three problems of different time horizon are investigated: strategic investment planning, short-term network rate allocation and on-line network operating. Deterministic and uncertain versions are taken into account, and the latter one is handled more thoroughly. The formalism of uncertain variables is used to represent the parameter uncertainty which concerns users’ demands for service in computer networks as well as network links’ capacities. Corresponding optimization tasks are presented. Numerical experiments concerning a part of the computer network Pionier working in Poland confirmed the usefulness of the solution algorithms proposed. Findings – The carried out numerical experiments verified the importance and worth of the decision making algorithms for the Pionier computer network. It particularly concerns the game theory based algorithm solving the on-line network operating problem which enables calculating the rates for computer links distinctly, i.e. separately for every link. Research limitations/implications – More case studies should be considered to formulate more general corollaries. The application of utility concept for wireless sensor networks needs further studies on solution algorithms.. Practical implications – The results can be directly applied to a class of modern computer networks, e.g. content delivery networks, self-management networks, context aware networks, multilevel virtual networks. Originality/value – The paper presents the unified and systematic approach for individual results previously obtained, and it considers one case study.