Rigorous Bounds for Loss Probabilities in Multiplexers of Discrete Heterogenous Markovian Sources

Exponential upper bounds of the form P[queue ≥ b] ≤ φy^(-b) are obtained for the distribution of the queue length in a model of a multiplexer in which the input is a heterogeneous superposition of discrete Markovian on-off sources. These bounds are valid at all queue lengths, rather than just asymptotic in the limit b→∞. The decay constant y is found by numerical solution of a single transcendental equation which determines the effective bandwidths of the sources in the limit b→∞. The prefactor φ is given explicitly in terms of y. The bound provides a means to determine rigorous corrections to effective bandwidths for multiplexers with finite buffers

Predicting Internet Bandwidth in Educational Institutions using Langrage’S Interpolation

This paper addresses the solution to the problem of Internet Bandwidth optimization and prediction in the institution of higher learning in Nigeria. The operation of the link-load balancer which provides an efficient cost-effective and easy-to-use solution to maximize utilization and availability of internet access is extensively discussed. This enables enterprises to lease for two or three ISP links connecting the internal network to the internet. The paper also proposes the application of the Langrage’s method of interpolation for the predictability of internet bandwidth in the institutions. The analysis provides a unique graphical solution of effective actual bandwidth (Mbps) and the corresponding acceptable number of internet Users (‘000) in the institutions. The prediction allows us to view the actual internet bandwidth and the acceptable number of internet Users as the population of users’ increases. Keywords: Internet Bandwidth, Optimization, Link-Load Balancer, Prediction, Maximized Utilization, Availability of Internet access

Two-dimensional fluid queues with temporary assistance

We consider a two-dimensional stochastic fluid model with $N$ ON-OFF inputs and temporary assistance, which is an extension of the same model with $N = 1$ in Mahabhashyam et al. (2008). The rates of change of both buffers are piecewise constant and dependent on the underlying Markovian phase of the model, and the rates of change for Buffer 2 are also dependent on the specific level of Buffer 1. This is because both buffers share a fixed output capacity, the precise proportion of which depends on Buffer 1. The generalization of the number of ON-OFF inputs necessitates modifications in the original rules of output-capacity sharing from Mahabhashyam et al. (2008) and considerably complicates both the theoretical analysis and the numerical computation of various performance measures

On the record process of time-reversible spectrally-negative Markov additive processes

We study the record process of a spectrally-negative Markov additive process (MAP). Assuming time-reversibility, a number of key quantities can be given explicitly. It is shown how these key quantities can be used when analyzing the distribution of the all-time maximum attained by MAPs with negative drift, or, equivalently, the stationary workload distribution of the associated storage system; the focus is on Markov-modulated Brownian mo- tion, spectrally-negative and spectrally-positive MAPs. It is also argued how our results are of great help in the numerical analysis of systems in which the driving MAP is a superposition of multiple time-reversible MAPs

GPS queues with heterogeneous traffic classes

We consider a queue fed by a mixture of light-tailed and heavy-tailed traffic. The two traffic classes are served in accordance with the generalized processor sharing (GPS) discipline. GPS-based scheduling algorithms, such as weighted fair queueing (WFQ), have emerged as an important mechanism for achieving service differentiation in integrated networks. We derive the asymptotic workload behavior of the light-tailed class for the situation where its GPS weight is larger than its traffic intensity. The GPS mechanism ensures that the workload is bounded above by that in an isolated system with the light-tailed class served in isolation at a constant rate equal to its GPS weight. We show that the workload distribution is in fact asymptotically equivalent to that in the isolated system, multiplied with a certain pre-factor, which accounts for the interaction with the heavy-tailed class. Specifically, the pre-factor represents the probability that the heavy-tailed class is backlogged long enough for the light-tailed class to reach overflow. The results provide crucial qualitative insight in the typical overflow scenario

Managing QoS in multiservice data networks

Abstract: Next-generation networks require organized methods to offer Quality of Service (QoS) guaranteed IP network connectivity. This study suggests a solution for combined control of routing and flow problems, namely an algorithm based on flow deterministic network models. The algorithm solves the problem by identifying optimal routes and triggering the flow control law only for those paths. This experiment aims to assess how QoS and MPLS traffic engineering (TE) can advance Internet performance. It also aims to ascertain avenues for Internet improvement and to devise innovative mechanisms to ensure traffic engineering provision, and Class-of-Service (CoS) features in next-generation networks. The performances of the algorithm were evaluated on a fully connected six-node network, the data for which were extracted from a realistic network

Internet Data Bandwidth Optimization and Prediction in Higher Learning Institutions Using Lagrange’s Interpolation: A Case of Lagos State University of Science and Technology

This research work studies the performance of the internet services of institution of higher learning in Nigeria. Data was collated from Lagos State University of Science and Technology (LASUSTECH) as case study of this research work. The problem of Internet Bandwidth optimization in the institution of higher learning in Nigeria was extensively addressed in this paper. The operation of the Link-Load balancer which provides an efficient cost-effective and easy-to-use solution to maximize utilization and availability of Internet access is discussed. In this research work, the Lagrange’s method of interpolation was used to predict effective internet data bandwidth for significantly increasing number of internet users. The linear Lagrange’s interpolation model (LILAGRINT model) was proposed for LASUSTECH.  The predictions allow us to view the effective internet data bandwidth with respect to the corresponding acceptable number of internet users as the number of user’s increases. The integrity of the model was examined, verified and validated at the ICT department of the institution. The LILAGRINT model was integrated into the management of ICT and tested. The result showed that the proposed LILAGRINT model proved to be highly effective and innovative in the area of internet data bandwidth predictability. Keywords:Internet Data Bandwidth, Optimization, Link-load balancer, Lagrange’s interpolation, Predictions, Management of ICT DOI: 10.7176/CEIS/10-1-04 Publication date:September 30th 202