A histogram-based model for video traffic behavior in an ATM multiplexer
IEEE/ACM Transactions on Networking (TON)
The Markov-modulated Poisson process (MMPP) cookbook
Performance Evaluation
An EM algorithm for estimation in Markov-modulated Poisson processes
Computational Statistics & Data Analysis
Self-similarity and heavy tails: structural modeling of network traffic
A practical guide to heavy tails
ACM SIGCOMM Computer Communication Review
Wide-area Internet traffic patterns and characteristics
IEEE Network: The Magazine of Global Internetworking
A unified approach for improving QoS and provider revenue in 3G mobile networks
Mobile Networks and Applications
A vacation queue with setup and close-down times and batch Markovian arrival processes
Performance Evaluation
Analysis and generation of random vectors with copulas
Proceedings of the 39th conference on Winter simulation: 40 years! The best is yet to come
Tools for dependent simulation input with copulas
Proceedings of the 2nd International Conference on Simulation Tools and Techniques
M-MIP: extended mobile IP to maintain multiple connections to overlapping wireless access networks
ICN'05 Proceedings of the 4th international conference on Networking - Volume Part I
Expanding weak PRF with small key size
ICISC'05 Proceedings of the 8th international conference on Information Security and Cryptology
Phase-type models for cellular networks supporting voice, video and data traffic
Mathematical and Computer Modelling: An International Journal
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In this paper, we identify the batch Markovian arrival process (BMAP) as an analytically tractable model of choice for aggregated traffic modeling of IP networks. The key idea of this aggregated traffic model lies in customizing the batch Markovian arrival process such that the different lengths of IP packets are represented by rewards (i.e., batch sizes of arrivals) of the BMAP. The utilization of the BMAP is encouraged by the observation that IP packet lengths follow to a large extent a discrete distribution. A comparative study with the MMPP and the Poisson process illustrates the effectiveness of the customized BMAP for IP traffic modeling by visual inspection of sample paths over four different time-scales, by presenting important statistical properties, and by analysis of traffic burstiness using R/S statistics. Additionally, we show that the BMAP model outperforms MMPP and Poisson traffic models by comparison of queuing performance.