This paper presents a simulation approach of the problem of scheduling customers in a queuing networks using a fuzzy inference system. Usually, in the queuing systems there are rules as round robin, equiprobable, shortest queue, among others, to schedule customers, however the condition of the system like the cycle time, utilization and the length of queue is difficult to measure. We propose a fuzzy inference system in order to determine the status in the system using input variables like the length queue and utilization. Our simulation shows an improvement in the performance measures compared with traditional scheduling policies.
|Original language||English (US)|
|Pages (from-to)||263 - 274|
|Number of pages||12|
|Journal||Communications in Computer and Information Science|
|State||Published - Aug 27 2017|
Franco Franco, C. A., Figueroa-Garcia, J. C., & Lopéz-Santana, E. R. (2017). Simulation of Fuzzy Inference System to Task Scheduling in Queueing Networks. Communications in Computer and Information Science, 742, 263 - 274.