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INTERNET TRAFFIC MODELING USING THE INDEX OF VARIABILITY
| Content Provider | CiteSeerX |
|---|---|
| Author | Lazarou, Georgios Y. |
| Abstract | In this paper, we propose a novel and mathematically rigorous measure of variability, called the index of variability (Hv ()), that fully and accurately captures the degree of variability of a typical network traffic process at each time scale and is analytically tractable for many popular traffic models. Using this proposed measure, we then analyzed two traffic models: the Two-State Markov Modulated Poisson Process (MMPP) and the renewal process with hyperexponential interarrival time distributions of order two (RPH2). Two-state MMPP models are popular in modeling the superposition of packet voice streams. The results show that the traffic variability can exhibit a nonmonotonic behavior. In addition, the results suggest that renewal processes with interarrival times hyperexponentially distributed are suitable for modeling network traffic processes with high variability over a broad range of time scales. |
| File Format | |
| Access Restriction | Open |
| Subject Keyword | Time Scale Hyperexponential Interarrival Time Distribution Interarrival Time Traffic Variability Nonmonotonic Behavior Renewal Process Two-state Markov Modulated Poisson Process Packet Voice Stream Rigorous Measure Typical Network Traffic Process Many Popular Traffic Model Traffic Model High Variability Network Traffic Two-state Mmpp Model |
| Content Type | Text |
