MODELING OF INTERNAL CONFLICTS OF AUTOMATED DATA COLLECTION AND DATA PROCESSING SYSTEMS

Abstract

The article deals with the problem of balancing the level of functional capabilities of automated data collection and processing systems (ADCPSs) with their potential. As a solution of the problem, it is proposed to develop a quantitative measure of the said processes, to be built into the structure of tools for control and management of ADCPS operation. A technique is described for calculation of model values of internal conflict intensity indicator (ICII), which is used as a quantitative measure of the current level and the potential of ADCPS. The technique is based on the model of ADCPS internal processes competition for resources that can be shared. A vector indicator is chosen as the ICII, which includes probability of finding a system in condition of conflict, the frequency of conflicts occurring in the interval of the system’s functioning, the average time of finding the system in the conflict condition. Conflicting processes are considered as queueing systems (QSOs) that process flows of requests to shared resources. Assumptions on the simplest type of flows of applications and on the exponential distribution of their service time make it possible to consider the processes occurring in competing CMOs to be Markov processes, making it possible to use the Erlang equations for the steady-state regime. To obtain characteristics of the vector exponent, the results obtained in the theory of impulse flows for coincident pulse sequences are used. A solution is given for the problem of calculating conflict intensity indicators for the case of competition between the two sides, generalized for a more complex case. It is concluded that ICII can be used for comparative analysis of the quality of several ADCPSs, and specifically, with other characteristics being equal, a better quality will be demonstrated by a system having s a lower value of the internal conflict indicator.