Resource-aware Approach in the Design of Complex Information Systems as a Problem of Multicriteria Optimization

Abstract

One of the modern information society tasksis the design of complex multiprocessor information systems, taking into account the rational use of system resources. It includes the development of a new resourceaware approach for the design of next generation information systems, such as smart home systems, autonomous transport, cyber-physical systems, etc. The paper has an educational character and is intended for novice researchers with the aim of introducing them to the subject area. It considers a demonstrative explanation of the problem of resource allocation in the design of complex information systems. It describes the basics of the problem of complex assessments of the technical solutions and the formal approach for solving this problem, including the methods from the theory of Data Mining and Operation Research. It also considers the problem of finding a trade-off between system parameters when looking for new solutions. Approaches to the comparative assessment of multiprocessor systems are demonstrated using simple examples. The ranking of the multiprocessor systems is performed in accordance with a complex criterion. Due to the specifics of technical solutions the formation of such a complex criterion is a rather difficult task, therefore many criteria (parameters) are used to make the assessment. The problem of finding the optimal variant of a multiprocessor system is presented as a problem of multicriteria optimization. The use of multicriteria optimization makes it possible to search for a trade-off between several alternatives or to find the non-dominant solutions, where none of them is better than the other in all the considered parameters and therefore have the same importance. In this case, many solutions are allowed, each of which is acceptable in the absence of preliminary information about the importance of the criteria. From the set of several non-dominated solutions obtained as a result of multicriteria optimization, it is possible to choose one that is most preferable for a specific applied problem.