Performance of Communication Systems: A Model-Based Evaluation with Matrix-Geometric Methods
Performance of Communication Systems: A Model-Based Evaluation with Matrix-Geometric Methods
Non-saturation and saturation analysis of IEEE 802.11e EDCA with starvation prediction
MSWiM '05 Proceedings of the 8th ACM international symposium on Modeling, analysis and simulation of wireless and mobile systems
A versatile infinite-state Markov reward model to study bottlenecks in 2-hop ad hoc networks
QEST '06 Proceedings of the 3rd international conference on the Quantitative Evaluation of Systems
A performance study on service integration in IEEE 802.11E wireless LANs
Computer Communications
Performance modeling of a bottleneck node in an IEEE 802.11 ad-hoc network
ADHOC-NOW'06 Proceedings of the 5th international conference on Ad-Hoc, Mobile, and Wireless Networks
Performance analysis of the IEEE 802.11 distributed coordination function
IEEE Journal on Selected Areas in Communications
An adaptive resource control mechanism in multi-hop ad-hoc networks
WWIC'11 Proceedings of the 9th IFIP TC 6 international conference on Wired/wireless internet communications
Setting the parameters right for two-hop IEEE 802.11e ad hoc networks
MMB&DFT'10 Proceedings of the 15th international GI/ITG conference on Measurement, Modelling, and Evaluation of Computing Systems and Dependability and Fault Tolerance
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Recently, a quality-of-service (QoS) extension of the IEEE 802.11 standard (known as IEEE 802.11e) for wireless LANs has been proposed. We present a versatile and accurate performance model to study how these new QoS enhancements can be used to improve the performance of wireless nodes competing for bandwidth in a multi-hop ad hoc network. The paper presents the QoS enhancements, and shows how they can be modeled using a simple, yet effective, parameterized quasi-birth-death model. The model is developed hierarchically, in that results at packet level (e.g., as developed by Bianchi and others) are used in our flow-level model, in which a single bottleneck station interacts with a time-varying number of traffic sources. Thus, we are able to study the impact of the QoS enhancements on the flow-level performance. This has not been done before. The results of our analyses are compared with extensive simulations (using Opnet), and show excellent agreement for throughput, mean number of active sources and mean buffer occupancy at the bottleneck station. An important asset of our model is that it allows for very quick evaluations: where simulations require up to an hour per scenario, our model is solved in seconds.