An Optimal Jobs’ Admission Control System for Priority-Based Queue Network

Congestion control is a major factor in the management of queue networks in order to prevent wastages of network resources. Consequently, it is necessary to adequately prevent congestion as well as loss of jobs which could be denied immediate admission into the queue network. This study proposes a priority-based fuzzy admission control system to ensure queue network stability and control jobs’ losses. The control of jobs’ admission was achieved using fuzzy logic approach while the management of jobs was achieved using tree data structure. The proposed model, the Fuzzy Based Admission Control System, was benchmarked with PQSMRPS. OMNeT++ was used as a simulation framework while dataset were generated randomly. Results indicated that throughput was slightly higher with FBACS than PQSMRPS. While average queue size was 76.3 mbs for FBACS, it was 84.9 mbs for PQSMRPS. The average memory usage was 141.6 mbs and 135.7 mbs for FBACS and PQSMRPS respectively. While the average job loss for FBACS was 4.7 bytes, that of PQSMRPS was 186.8 bytes. These indicate a significant difference in the performance of both methods regarding average queue size, average memory usage and degree of job losses. However FBACS achieved a slightly worse performance of \(<0.3\%\) $<0.3\%$ on the average to PQSMRPS with regards to propagation delay. With these results, it was concluded that FBACS is more optimal with regards to ensuring queue network stability and control of job losses in queue networks.