Server side measurements from several Wi-Fi hot-spots deployed in a nationwide network over different types of venues from small coffee shops to large enterprises are used to highlight differences in traffic volumes and patterns. We develop a common modeling framework for the number of simultaneously present customers. Our approach has many novel elements: (a) We combine statistical clustering with Poisson regression from Generalized Linear Models to fit a non-stationary Poisson process to the arrival counts and demonstrate its remarkable accuracy; (b) We model the heavy tailed distribution of connection durations through fitting a Phase Type distribution to its logarithm so that not only the tail but also the overall distribution is well matched; (c) We obtain the distribution of the number of simultaneously present customers from an Mt/G/∞ queuing model using a novel regenerative argument that is transparent and avoids the customarily made assumption of the queue starting empty at an infinite past; (d) Most importantly, we validate our models by comparison of their predictions and confidence intervals against test data that is not used in fitting the models.

We describe and analyze a novel algorithm called Limited Chain Relay for on-demand multimedia content distribution over digital networks. Using VoD as an example, we show that this peer assisted scheme provides bandwidth and processing savings comparable to a periodic multicast without incurring subscriber delays inherent in the latter. This scheme's success does not depend upon the ability to forecast demand accurately. It uses minimal storage in participating peer CPEs. It incorporates many features to facilitate fast set up, redundancy to handle peer failures, and centralized OS functions including billing. It can be used in a wide variety of networks such as Fiber to the Home and Fiber to the Curb and with transport technologies like IP and ADSL. It can be used also for streaming content where individual clients may not store the entire content.

Motivated by field data which showed a large number of link changeovers and incidences of link oscillations between in-service and out-of-service states in common channel signalling (CCS) networks, a number of analyses of the link error monitoring procedures in the SS7 protocol were performed by the authors. This paper summarizes the results obtained thus far and include the following: (a) results of an exact analysis of the performance of the error monitoring procedures under both random and bursty errors; (b) a demonstration that there exists a range of error rates within which the error monitoring procedures of SS7 may induce frequent changeovers and changebacks; (c) an analysis of the performance of the SS7 level-2 transmission protocol to determine the tolerable error rates within which the delay requirements can be met; (d) a demonstration that the tolerable error rate depends strongly on various link and traffic characteristics, thereby implying that a single set of error monitor parameters will not work well in all situations; and (e) some recommendations on a customizable/adaptable scheme of error monitoring with a discussion on their implementability. These issues may be particularly relevant in the presence of anticipated increases in SS7 traffic due to widespread deployment of advanced intelligent network (AIN) and personal communications service (PCS) as well as for developing procedures for high-speed SS7 links currently under consideration by standards bodies.>

Link quality in the common channel signaling (CCS) network is monitored and reported by the Signaling System No.7 (SS7) protocol level 2 signaling link error monitoring procedures. The procedures include two algorithms: the signal unit error rate monitor (SUERM), which provides one of the criteria for taking the link out of service, and the alignment error rate monitor (AERM), which determines whether a link should be put into service. The authors, motivated by the excessive link status changes observed in some field operations of the CCS network provide a detailed analysis of the signaling link error monitoring algorithms and show that under current SS7 specifications of the error monitoring algorithms, the probability of a link oscillating in and out of service could be high for certain sustained error rates. While the risk to the existing network may not be high due to the light loads carried at present, there is still a need to study the error monitoring issues thoroughly.>

Motivated by the excessive link status changes observed in some field operations of the common channel signaling (CCS) network, the authors provide a detailed analysis of the signaling link error monitoring algorithms in the Signaling System No. 7 (SS7) protocol. These algorithms determine when to fail a link due to excessive error rates and when to put a failed link back into service. The analysis shows that, under current SS7 specifications of the error monitoring algorithms, the probability of a signaling link oscillating in and out of service could be high, depending on the traffic load, signal unit size, and the statistical nature of errors (bursty or random). The link oscillation phenomenon could become worse as longer Transaction Capability Application Part (TCAP) messages for transaction-based services (e.g., 800 Service) are carried in the CCS networks. While the risk to the existing network may not be high due to the light loads carried at present, there is still a need to study the error monitoring issues thoroughly.>

A parametric model is proposed for the cell arrival traffic on the input lines of a switch. The cell stream alternates between active and silent periods, and general distributions are allowed for the lengths of these periods. The traffic is represented by a discrete Markov chain model obtained through a simple moment matching procedure. The cell arrivals at in input port of the switch are typically non-Poisson and exhibit periodicities. The simulation experiments illustrate that each parameter included in the model has a significant impact on the performance of the switch (as measured by cell-loss probabilities, average cell delay, and steady-state queue length distribution).>

A discrete-time queuing model for the performance of a meteor-burst packet communication system is analyzed using matrix analytic methods. Not only is the system subject to interruptions due to the intermittence of the ionization layer, but its analysis is further complicated by the necessity to retransmit packets that have error or that occur at the tail end of a period of availability of the system. The authors' model takes such complexities into account. It is also of independent methodological interest in that it provides an exact analysis of a general queuing model with service interruptions. For the application at hand, the authors demonstrate the feasibility of the algorithms by a selected set of numerical examples. The algorithm can be used to ascertain the effects of the packet size, the bit error rate, the sync acquisition time, and other variables on system performance.>