Application of the Diffusion Approximation to Queueing Networks I: Equilibrium Queue Distributions
Journal of the ACM (JACM)
On Approximate Computer System Models
Journal of the ACM (JACM)
Theory, Volume 1, Queueing Systems
Theory, Volume 1, Queueing Systems
Modeling the 802.11 distributed coordination function in nonsaturated heterogeneous conditions
IEEE/ACM Transactions on Networking (TON)
Diffusion Approximation Model of Multiserver Stations with Losses
Electronic Notes in Theoretical Computer Science (ENTCS)
Transient States of Priority Queues - A Diffusion Approximation Study
AICT '09 Proceedings of the 2009 Fifth Advanced International Conference on Telecommunications
Performance analysis under finite load and improvements for multirate 802.11
Computer Communications
CSMA/CA performance under high traffic conditions: throughput and delay analysis
Computer Communications
Performance analysis of the IEEE 802.11 distributed coordination function
IEEE Journal on Selected Areas in Communications
Applications and challenges of the 802.11e EDCA mechanism: an experimental study
IEEE Network: The Magazine of Global Internetworking
Diffusion approximation as a modelling tool
Network performance engineering
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The article presents an analytical model of wireless networks using the IEEE 802.11 protocol to access the transport medium. The model allows to determine such key factors of the quality of service as transmission delays and losses. The model is based on diffusion approximation approach which was proposed three decades ago to model wired networks. We show that it can be adapted to take into consideration the input streams with general interarrival time distributions and servers with general service time distributions. The diffusion approximation has been chosen because of fairly general assumptions of models based on it, hard to be represented in Markov models. A queueing network model can have an arbitrary topology, the intensity of transmitted flows can be represented by non-Poisson (even self-similar) streams, the service times at nodes can be defined by general distributions. These assumptions are important: because of the CSMA/CA algorithm, the overall times needed to sent a packet are far from being exponentially distributed and therefore the flows between nodes are non-Poisson. Diffusion approximation allows us also to analyse the of transient behaviour of a network when traffic intensity is changing with time.