No / An investigation is carried out on the nature of QoS measures for queues with correlated traffic in both discrete and continuous time domains. The study focuses on the single server GI(G)/M-[x]/1/N and GI(G)/Geo([x])/1/N queues with finite capacity, N, a general batch renewal arrival process (BRAP), GI(G) and either batch Poisson, M-[x] or batch geometric, Geo([x]) service times with general batch sizes, X. Closed form expressions for QoS measures, such as queue length and waiting time distributions and blocking probabilities are stochastically derived and showed to be, essentially, time domain invariant. Moreover, the sGGeo(sGGo)/Geo/l/N queue with a shifted generalised geometric (sGGeo) distribution is employed to assess the adverse impact of varying degrees of traffic correlations upon basic QoS measures and consequently, illustrative numerical results are presented. Finally, the global balance queue length distribution of the M-Geo/M-Geo/1/N queue is devised and reinterpreted in terms of information theoretic principle of entropy maximisation. (C) 2014 Elsevier Inc. All rights reserved.

No / Given only the traffic correlations of counts and intervals, a Batch Renewal Arrival Process (BRAP) is completely determined, as the least biased choice and thus, it provides the analytic means to construct suitable traffic models for the study of queueing systems independently of any other traffic characteristics. In this context, the BRAP and the Batch Markovian Arrival Process (BMAP) are employed in the continuous time domain towards the analysis of the stable BRAP/GE/1 and BMAP/GE/1 queues with infinite capacity, single servers and generalized exponential (GE) service times. Novel closed form expressions for the steady state probabilities of these queues are obtained, based on the embedded Markov chains (EMCs) technique and the matrix-geometric (M-G) method, respectively. Moreover, the stable GEsGGeo/GE/1 queue with GE-type service times and a GEsGGeo BRAP consisting of bursty GE-type batch interarrival times and a shifted generalized geometric (sGGeo) batch size distribution is adopted to assess analytically the combined adverse effects of varying degrees of correlation of intervals between individual arrivals and the burstiness of service times upon the typical quality of service (QoS) measure of the mean queue length (MQL). Moreover, a comprehensive experimental study is carried out to investigate numerically the relative impact of count and interval traffic correlations as well as other traffic characteristics upon the performance of stable BRAP/GE/1 and BMAP/GE/1 queues. It is suggested via a conjecture that the BRAP/GE/1 queue is likely to yield pessimistic performance metrics in comparison to those of the stable BMAP/GE/1 queues under the worst case scenario (i.e., a worst case scenario) of the same positive count and interval traffic correlations arising from long sojourn in each phase.