Recent measurements of local-area and wide-area traffic have shown that network traffic exhibits variability at a wide range of scales. In this paper, we examine a mechanism that gives rise to self-similar network traffic and present some of its performance implications. The mechanism we study is the transfer of files or messages whose size is drawn from a heavy-tailed distribution. First, we show that in a “realistic ” client/server network environment—i.e., one with bounded resources and coupling among traffic sources competing for resources—the degree to which file sizes are heavy-tailed can directly determine the degree of traffic self-similarity at the link level. We show that this causal relationship is robust with respect to changes in network resources (bottleneck bandwidth and

this paper, we focus on the problem of making short and medium term forecasts of CPU availability on time-shared Unix systems. We evaluate the accuracy with which availability can be measured using Unix load average, the Unix utility vmstat, and the Network Weather Service CPU sensor that uses both. We also examine the autocorrelation between successive CPU measurements to determine their degree of self-similarity. While our observations show a long-range autocorrelation dependence, we demonstrate how this dependence manifests itself in the short and medium term predictability of the CPU resources in our study.

Cumulative broadband network traffic is often thought to be well modelled by fractional Brownian motion. However, some traffic measurements do not show an agreement with the Gaussian marginal distribution assumption. We show that if connection rates are modest relative to heavy tailed connection length distribution tails, then stable L'evy motion is a sensible approximation to cumulative traffic over a time period. If connection rates are large relative to heavy tailed connection length distribution tails, then FBM is the appropriate approximation. The results are framed as limit theorems for a sequence of cumulative input processes whose connection rates are varying in such a way as to remove or induce long range dependence.

This paper studies the quality of service (QoS) provision problem in noncooperative networks where applications or users are selfish and routers implement generalized processor sharing (GPS)-based packet scheduling. First, we formulate a model of QoS provision in noncooperative networks where users are given the freedom to choose both the service classes and traffic volume allocated, and heterogenous QoS preferences are captured by individual utility functions. We present a comprehensive analysis of the noncooperative multi-class QoS provision game, giving a complete characterization of Nash equilibria and their existence criteria, and show under what conditions they are Pareto and system optimal. We show that, in general, Nash equilibria need not exist, and when they do exist, they need not be Pareto nor system optimal. However, we show that for certain "resource-plentiful" systems, the world indeed can be nice with Nash equilibria, Pareto optima, and system optima collapsing into a s...

The statistical characteristics of network traffic- in particular the observation that it can exhibit long range dependence- have received considerable attention from the research community over the past few years. In addition, the recent claims that the TCP protocol can generate traffic with long rage dependent behavior has also received much attention. Contrary to the latter claims, in this paper we show that the TCP protocol can generate traffic with correlation structures that spans only an analytically predictable finite range of time-scales. We identify and analyze separately the two mechanisms within TCP that are responsible for this scaling be-havior: timeouts and congestion avoidance. We provide analytical models for both mechanisms that, under the proper loss probabilities, accurately predict the range in time-scales and the strength of the sustained correlation structure of the traffic sending rate of a single TCP source. We also analyze an existing comprehensive model of TCP that accounts for both mechanisms and show that TCP itself exhibits a predictable finite range of time-scales under which traffic presents sustained correlations. Our claims and results are derived from Markovian models that are supported by simulations. We note that traffic generated by TCP can be misinterpreted to have long range dependence, but that long range dependence is not possible due to inherent finite time-scales of the mechanisms of TCP.

he future will bring a wide variety of multimedia applications each with different traffic characteristics at optimized performance, to be carried by both wireless and wireline networks. In wireless mobile networks the offered traffic varies both temporally and spatially, with the spatial variation significantly higher than in wired networks. Models of the traffic offered to the network or a component of the network will be critical to providing high quality of service (QoS). Traffic models are used as the input to analytical or simulation studies of resource allocation strategies. We may view traffic at the application or packet level, where an application-level view may simply describe the offered traffic as “a videoconference between three parties,” while the packet-level view is given by a stochastic model

The burstiness of Internet traffic was established in pioneering work in the early 1990s, which demonstrated that packet arrival times are not Poisson, and packet and byte counts in fixed-length intervals are long-range dependent [17, 20]. Here we demonstrate that these results are one end of a continuum of traffic characteristics. At the other end are Poisson behavior and independence. Our study focuses on packets, what devices actually see; we study the statistical properties of packet inter-arrival times and packet sizes. As the traffic load increases --- that is, as the number of simultaneous transport connections increases --- arrivals tend to Poisson and sizes tend to independence. More specifically, long-range dependence of inter-arrivals and sizes decreases to independence, and the marginal distribution of inter-arrivals tends toward exponential; this happens (1) through time on a single link as the load increases due to daily variation, or (2) at a single point in time as the load increases going from lightly loaded links at the edges of the Internet to heavily loaded links at the core. Convergence is rapid; the packet traffic gets quite close to Poisson and independent loads far less than the maximum we observe.

This paper presents an adaptive protocol for packet-level forward error correction in dynamic networks. The objective is to facilitate end-to-end transport---i.e., without special network support---of real-time traffic whose timing constraints rule out the use of retransmission-based congestion control and quality of service (QoS) provision schemes. The degree of redundancy injected into the network is adjusted as a function of network state, decreasing when the network is well-behaved and increasing when it is not. The control problem is nontrivial due to the fact that increased redundancy, beyond a certain point, can backfire resulting in self-induced congestion which impedes the timely recovery of information at the receiver. In the first part of the paper, we give a comprehensive analysis of the control problem associated with adaptive forward error correction, concentrating on the dynamics of a particular protocol called Adaptive Forward Error Correction (AFEC). We show that insta...

Thispaperpresentsadiscussionofsimulation-related issuesarisinginthestudyofself-similarnetwork tra#cwithrespecttoitse#ectandcontrol.Selfsimilartra #chasbeenshowntobeanubiquitous phenomenonarisingindiversenetworkingcontexts withpotentiallyadversee#ectsonnetworkperformance. Inmanyinstances,anexperimentalorempirical approachneedstobetakentoe#ectivelyevaluate theperformanceimpactofsophisticatedcontrolalgorithmsactingatvariouslayersintheprotocolstack underself-similartra#cconditions.Simulatingorexperimentallyimplementingsuchenvironmentsisnon - trivialduetothefactthat,ingeneral,thecharacteristicsoftheobservedtra #cisitselfinfluencedbythe actionsofthecontrolalgorithmsunderstudy.To whatdegreeself-similaritymanifestsitselfinnetwork tra#cmaydependonthepropertiesoftheprotocols employed,andtrace-basedsimulationsthatrelyon tra#cmeasurementstodrivesimulationsfailtocapturethisdynamicaspect. Wediscussanapproachtoevaluatingcontrolprotocolsunderself -similartra#cconditionsbasedon asimple,robustapplication-levelcausalmechanism oftra#cself-similaritywhichisgroundedinboth empiricalUNIXfilesystemresearchandanalytic tra#cmodelsinvolvingcertainrenewalprocesses. Wepresentahigh-leveldiscussionconcentratingon simulation-relatedissues,withspecificresearchresultssummarizedorpointedtointhereferences. 1

As the active connection load (ACL) on an Internet link increases, the statistical properties of packet inter-arrivals and sizes change due to increased statistical multiplexing of packets from different connections. Chief among these results is that the long-range dependence of the inter-arrivals and sizes goes locally to independence. The results are based on (1) the mathematical theory of superposition of marked point processes, and (2) empirical study of 3026 packet traces, each 5 minutes or 90 seconds in duration, from 6 monitors on Internet links ranging from 100 mbps to 622 mbps. An understanding of packet inter-arrivals and sizes is important because it is packets that devices must send and receive, and the burstiness of traffic as seen by the devices is determined by the statistical characteristics of these two variables. The results for inter-arrivals and sizes do not conflict with previous well known results about the statistical properties of packet and byte counts in fixed time intervals, but the counts do have a different change in statistical properties with the ACL. 1.