SIGCOMM '92 Conference proceedings on Communications architectures & protocols
The impact of autocorrelation on queuing systems
Management Science
Queue response to input correlation functions: discrete spectral analysis
IEEE/ACM Transactions on Networking (TON)
Wide-area traffic: the failure of Poisson modeling
SIGCOMM '94 Proceedings of the conference on Communications architectures, protocols and applications
An Adaptive Nonlinear Least-Squares Algorithm
ACM Transactions on Mathematical Software (TOMS)
Computers and Operations Research
Pricing and capacity decisions for non-profit internet service providers
Information Technology and Management
A load control method for small data centers participating in demand response programs
Future Generation Computer Systems
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This paper presents a statistical characterization of on-line service trafJic. The trafJic is parameterized by the call holding times, the aggregate number of bytes and the number of packets transferred during the call. Particular attention is paid to modeling the stochastic rate function describing the call arrivals. The time of day and day of the week seasonal features produce long term correlations in the arrival process. In addition, short term correlations are found to exist within the hourly time scale. The arrival rates are in general nonstationary in the mean rate. This is attributed to the daily influx of new subscribers and other exogenous influences such as promotions and advertisements that trigger increased usage. A time series modeling methodology is used to identify and quantify these features. Under suitable transformations, a stationary rendition of the arrival process is derived and characterized by the short and long term correlation coeficients. The second order characterization of the arrival process is used to predict resource usage.