The changing nature of network traffic analysis and modeling

Abstract

For many decades, telephone network traffic has been characterized by Poisson call arrivals and exponentially distributed call durations (with a mean of about 3 minutes). In contrast, recent work in network traffic data analysis and modeling has demonstrated that data network traffic is best characterized in terms of burstiness and connection times that range over a wide range of time scales (from milliseconds to minutes and hours); in addition, data network traffic has been observed to undergo constant and often radical changes within short periods in time, due to a constantly changing user population, the emergence of so-called “killer applications” (e.g., the Web and other multimedia services in today’s Internet), new networking technologies, etc. Historically, the areas of network traffic data analysis and modeling have suffered from a severe “drought” of data. However, more recently, this drought has been replaced by a “flood” of traffic measurements from today’s high-speed communication networks that keeps increasing in volume and speed. As a result of these changes, network research (in particular, traffic analysis and traffic modeling) has started to adopt concepts that have a long tradition in the physical sciences but have been all but ig-nored in the social sciences and in the mainstream statistics literature. On January 10, 1997, Walter Willinger from AT&T Labs—Research illustrated some of these concepts and showed how they apply to modern network traffic analysis and modeling. He pointed out their implications on traffic engineering and performance analysis of current and future high-speed networks. Finally he outlined new areas of research in the mathematical and statistical sciences that result from these changes and are of practical importance for network research.