On the self-similar nature of Ethernet traffic (extended version)
IEEE/ACM Transactions on Networking (TON)
Analysis, modeling and generation of self-similar VBR video traffic
SIGCOMM '94 Proceedings of the conference on Communications architectures, protocols and applications
Wide area traffic: the failure of Poisson modeling
IEEE/ACM Transactions on Networking (TON)
Self-similarity in World Wide Web traffic: evidence and possible causes
IEEE/ACM Transactions on Networking (TON)
Modelling the self-similar behaviour of network traffic
Computer Networks: The International Journal of Computer and Telecommunications Networking - Special Issue: performance modeling and evaluation of ATM networks
Performance Guarantees in Communication Networks
Performance Guarantees in Communication Networks
Heavy traffic limits associated with M/G/∞ input processes
Queueing Systems: Theory and Applications
M|G|Infinity Input Processes: A Versatile Class of Models for Network Traffic
INFOCOM '97 Proceedings of the INFOCOM '97. Sixteenth Annual Joint Conference of the IEEE Computer and Communications Societies. Driving the Information Revolution
Supporting real time VBR video using dynamic reservation based on linear prediction
INFOCOM'96 Proceedings of the Fifteenth annual joint conference of the IEEE computer and communications societies conference on The conference on computer communications - Volume 3
Modeling video traffic using M/G/∞ input processes: a compromise between Markovian and LRD models
IEEE Journal on Selected Areas in Communications
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In this paper, we propose a new method to allocate bandwidth adaptively according to the amount of input traffic volume for a long range dependent traffic requiring Quality of Service (QoS). In the proposed method, we divide the input process, which is modelled by an M/G/∞ input process, into two sub-processes, called a long time scale process and a short time scale process. For the long time scale process we estimate the required bandwidth using the linear prediction. Since the long time scale process varies (relatively) slowly, the required bandwidth doesn't need to be estimated frequently. On the other hand, for the short time scale process, we use the large deviation theory to estimate the effective bandwidth of the short time scale process based on the required QoS of the input traffic. By doing this we can capture the short time scale fluctuation by a buffer and the long time scale fluctuation by increasing or decreasing the bandwidth adaptively. Through simulations we verify that our proposed method performs well to satisfy the required QoS.