H.1 WHY QUEUEING ANALYSIS?........................................................................2! H.2 THE SINGLE-SERVER QUEUE......................................................................4! H.3 THE MULTISERVER QUEUE.........................................................................7! H.4 POISSON ARRIVAL RATE .........................................................................

This investigation deals with single server queueing system wherein the arrival of the units follow Poisson process with varying arrival rates in different states and the service time of the units is arbitrary (general) distributed. The server may take a vacation of a fixed duration or may continue to be available in the system for next service. Using the probability argument, we construct the ...

In many queueing systems the server processes several customers simultaneously. Although the capacity of a batch, that is the number of customers that can be processed simultaneously, is often variable in practice, nearly all batch-service queueing models in literature consider a constant capacity. In this paper, we extend previous work on a batch-service queueing model with variable server cap...

The arrival of a negative customer to a queueing system causes one ordinary customer to be removed (or killed) if any is present. The arrival of a disaster, on the other hand, kills all the customers in the system if any. In this paper, we extend the queueing theory on negative arrivals and disasters to the discrete-time Geo=Geo=1 queueing system. Speci2cally, we 2nd the ergodicity condition an...

integration paradigm, prototyping, parameter tuning, qualitative reasoning, real-time systems, synchronized queueing network There are a number of parameter tuning plans for improving a real-time system prototype performance. This paper describes the integration of real-time system prototyping with qualitative and quantitative methods by Bottleneck Diagnosis I Improvement Ex...

In this paper, we investigate the problem of assignment of K identical servers to a set of N parallel queues in a time slotted queueing system. The connectivity of each queue to each server is randomly changing with time; each server can serve at most one queue and each queue can be served by at most one server per time slot. Such multi-server queueing systems were widely applied in modeling th...

Obtaining (tail) probabilities from a transform function is an important topic in queueing theory. To obtain these probabilities in discrete-time queueing systems, we have to invert probability generating functions, since most important distributions in discrete-time queueing systems can be determined in the form of probability generating functions. In this paper, we calculate the tail probabil...

The authors study the queueing process in a single-server queueing system with state dependent service and with the input modulated by a semi-Markov process embedded in the queueing process. It is also assumed that the server capacity is r > 1 and that any service act will not begin until the queue accumulates at least r units. In this model, therefore, idle periods also depend upon the queue l...

point in this Letter is that numerical results have shown that, for small numbers of multiplexed sources, our earlier analysis [l] can be highly inaccurate. In this Letter we present a scheme for source aggregation (and therefore the solution of the overflow probability) which is applicable when multiplexing a small number of sources. As in the previous paper, we refer to the buffer fed by the ...

We consider a two node multiclass queueing network given by two machines each with two classes. There are two streams of jobs: One stream originates in machine 1, which feeds it for further processing to machine 2, and the other stream moves in the opposite direction. We describe a policy for this system which is stable and which keeps both machines busy at all times. We obtain explicit express...