Abstract
The work considers the queuing system of the G/M/1/K with the Weibull distribution. The model for self-similar traffic was created within the Matlab Simulink software environment. Restoration of the self-similar traffic was obtained with the help of the spline approximation using linear and cubic splines. In this research, it has been discovered that the obtained self-similar traffic is characterized by “bursts”, “pulsations”, and the long-term dependence between arrivals. Linear and cubic spline approximations have been suggested to restore traffic. The approximations with the linear and cubic splines were used to restore smoothly changing self-similar traffic. The obtained results of the self-similar traffic restoration allow planning buffer capacities for NGN networking devices at the stages of design and further operation in order to avoid network overloads, excessive time delays and jitter for the case of packet traffic with bursts. The wavelet approximation is recommended for the accurate restoration of the self-similar traffic
Highlights
The development of modern telecommunications is connected with the active implementation of GenerationNetworks (NGN), which are multi-service, multiprotocol and invariant to switching technologies
To simulate the process of requests arrivals, the intervals between arrivals are described by an arbitrary distribution of G, and we use the Weibull distribution with the service time distributed according to the exponential law
It would be interesting to continue the research of restoring self-similar traffic with increased steepness and the presence of “bursts” and “pulsations” with the help of wavelet approximation, in order to perform a comparative analysis of the corresponding results obtained through spline-approximations
Summary
Networks (NGN), which are multi-service, multiprotocol and invariant to switching technologies. Self-similar traffic has a special structure, which is determined by the burstness and presence of a significant number of pulsations This is because packets arrive at the switching node in groups rather than one by one. The delay time and probability of packet loss increase This often leads to possible overloads of network nodes and buffer devices and, respectively, significantly affects Quality of Service. The known methods of traffic approximation (polynomial, fractional-rational, piecewise-linear, etc.) proved to be rather limited and unacceptable for self-similar traffic [5, 6] This is due to the fact that self-similar traffic is characterized by the presence of a significant number of “peaks”, “bursts” and a long-term dependence between the instants of packets arrivals. The use of spline approximation in restoration of self-similar traffic is a relevant problem, the solution of which will allow accurate and fast approximation of simulated traffic
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
