Classical studies of Asynchronous Transfer Mode (ATM) switching elements and in particular the buffer behavior of the Shared Buffer Memory (SBM), assume that all read and write operations of cells to, respectively from, the SBM are executed simultaneously. However, in a real switching element, the inlets (outlets) are scanned sequentially for arriving (departing) cells during the so-called input (output) cycle. Furthermore, the input and output cycles are intermingled, each read operation being followed by a write operation. This is referred to as the Timeslot Interchange Mechanism (TIM). In this paper, we present the analysis of a queueing model that includes the TIM. We model the cell arrival processes on the inlets of the switching element as independent Bernoulli arrival processes. Moreover, we assume that cells are routed from the inlets to the outlets of the switching element according to an independent and uniform process, i.e., the destinations of consecutive cell arrivals on any given inlet are independent and for a given cell all destinations are equiprobable. Under these assumptions, we will derive expressions for the probability generating functions of the queue length in an individual routing group (a logical queue that contains all cells scheduled for the same destination), the (total) queue length in the SBM, and the cell waiting time. From these results, expressions for the mean values and the tail distributions of these quantities are calculated, and the influence of the TIM on the buffer behavior is studied through comparison with a model where all read and write operations occur simultaneously.

Discrete-time queueing models have been studied for many years because of their direct applicability in the performance evaluation of digital communication system and networks, where buffers are used to temporarily store information packets which cannot be transmitted instantaneously. In this paper, we investigate the behavior of a discrete-time multiserver buffer system with infinite buffer size. Packets arrive in the system according to a two-state correlated arrival process. The service times of the packets are assumed to be independent and identically distributed according to a geometric distribution. We present an analytical technique, based on the use of generating functions, for the analysis of the system. Explicit expressions are obtained for the mean values, the variances and the tail distributions of the system contents and the packet delay. The influence of the various model parameters on the behavior of the system is shown by means of some numerical examples.

In Cognitive Radio Networks (CRNs), spectrum sensing is performed by secondary (unlicensed) users to utilize transmission opportunities, so-called white spaces or spectrum holes, in the primary (licensed) frequency bands. Secondary users (SUs) perform sensing upon arrival to find an idle channel for transmission as well as during transmission to avoid interfering with primary users (PUs). In practice, spectrum sensing is not perfect and sensing errors including false alarms and misdetections are inevitable. In this paper, we develop a continuous-time Markov chain model to study the effect of false alarms and misdetections of SUs on several performance measures including the collision rate between PUs and SUs, the throughput of SUs and the SU delay in a CRN. Numerical results indicate that sensing errors can have a high impact on the performance measures.