The recent discovery of scaling phenomena in modern communication networks involving self-similarity or fractals and power-law or heavy-tailed distributions is yet another realization of Benoit Mandelbrot's vision of order in physical, and engineered systems characterized by scaling laws. Since the seminal paper by
Leland, Taqqu,Willinger and Wilson in 1993 which set the groundwork for considering self-similarity an ubiquitous feature of empirically observed network traffic and an important notion in the understanding of the traffic's dynamic nature for modeling analysis and control of network performance, an explosion of work has ensued investigating the multifaceted nature of this phenomenon.
Despite the fact that data networks such as the Internet are drastically different from legacy legacy public switched telephone networks, the long hekd paradigm in the communication and networking research community has been that data traffic-analogous to voice traffic-is adequately described by certain MarKovian models which are amenable to accurate analysis and efficient control. This supposition has been instrumental in shaping the optimism permeating the late 1980s and early 1990s rgarding the ability of achieving efficient traffic control for quality of
service provisioning in modern high-speed communication networks. The discovery and,more importantly, succinct formulation and recognition that actual data trafficc may, infact, be fundamentally different in nature from the hereto accustomed telephony traffic has significantly influenced the networking research landscape, necessitating a reexamination and revamping of its basic premises.
1. Self-Similar Network Traffic: An Overview
2. Wavelets for the Analysis, Estimation, and Synthesis
3. Simulations with Heavy-Tailed Workloads
4. Queueing Behavior Under fractional Brownian Traffic
5. Heavy Load Queueing Analysis with LRD On/Off Sources
6. The Single Server Queue: Heavy Tails and Heavy Traffic
7. Fluid Queues, On/Off Processes, and Teletraffic Modeling with Highly Variable and Correlated Inputs Traffic
8. Bounds on the Buffer Occupancy Probability with Self-Similar Input Traffic
9. Buffer Asymptotics for M/G Input Processes
10. Asymptotic Analysis of Queues with Subexponential
etc.