C e n t r u m v o o r W i s k u n d e e n I n f o r m a t i c a PNA Probability, Networks and AlgorithmsProbability, Networks and Algorithms

In this paper we present an integrated packet/flow level modelling approach for analysing flow throughputs and transfer times in 802.11 s. The packet level model captures the statistical characteristics of the transmission of individual packets at the layer, while the flow level model takes into account the system dynamics due to the initiation and completion of data flow transfers. The latter model is a processor sharing type of queueing model reflecting the 802.11 design principle of distributing the transmission capacity fairly among the active flows. The resulting integrated packet/flow level model is analytically tractable and yields a simple approximation for the throughput and flow transfer time. Extensive simulations show that the approximation is very accurate for a wide range of parameter settings. In addition, the simulation study confirms the attractive property following from our approximation that the expected flow transfer delay is insensitive to the flow size distribution (apart from its mean).

C e n t r u m v o o r W i s k u n d e e n I n f o r m a t i c a PNA Probability, Networks and Algorithms Probability, Networks and AlgorithmsPerformance modeling of a bottleneck node in an IEEE 802.11 ad-hoc network J.L. van Performance modeling of a bottleneck node in an IEEE 802.11 ad-hoc network ABSTRACT This paper presents a performance analysis of wireless ad-hoc networks, with IEEE 802.11 as the underlying Wireless LAN technology. WLAN has, due to the fair radio resource sharing at the MAC-layer, the tendency to share the capacity equally amongst the active nodes, irrespective of their loads. An inherent drawback of this sharing policy is that a node that serves as a relay-node for multiple flows is likely to become a bottleneck. This paper proposes to model such a bottleneck by a fluid-flow model. Importantly, this is a model at the flow-level: flows arrive at the bottleneck node, and are served according to the sharing policy mentioned above. Assuming Poisson initiations of new flow transfers, we obtain insightful, robust, and explicit expressions for characteristics related to the overall flow transfer time, the buffer occupancy, and the packet delay at the bottleneck node. The analysis is enabled by a translation of the buffer dynamics at the bottleneck node in terms of an M/G/1 queueing model. We conclude the paper by an assessment of the impact of alternative sharing policies (which can be obtained by the IEEE 802.11E version), in order to improve the performance of the bottleneck. Abstract This paper presents a performance analysis of wireless ad-hoc networks, with ieee 802.11 as the underlying wireless lan technology. wlan has, due to the fair radio resource sharing at the mac-layer, the tendency to share the capacity equally amongst the active nodes, irrespective of their loads. An inherent drawback of this sharing policy is that a node that serves as a relay-node for multiple flows is likely to become a bottleneck. This paper proposes to model such a bottleneck by a fluid-flow model. Importantly, this is a model at the flow-level: flows arrive at the bottleneck node, and are served according to the sharing policy mentioned above. Assuming Poisson initiations of new flow transfers, we obtain insightful, robust, and explicit expressions for characteristics related to the overall flow transfer time, the buffer occupancy, and the packet delay at the bottleneck node. The analysis is enabled by a translation of the buffer dynamics at the bottleneck node in terms of an m/g/1 queueing model. We conclude the paper by an assessment of the impact of alternative sharing policies (which can be obtained by the ieee 802.11e version), in order to improve the performance of the bottleneck.

This paper studies a fluid queue with coupled input and output. Flows arrive according to a Poisson process, and when n flows are present, each of them transmits traffic into the queue at a rate C/(n + 1), where the remaining C/(n + 1) is used to serve the queue. We assume exponentially distributed flow sizes, so that the queue under consideration can be regarded as a system with Markov fluid input. The rationale behind studying this queue lies in ad hoc networks: bottleneck links have roughly this type of sharing policy. We consider four performance metrics: (i) the stationary workload of the queue, (ii) the queueing delay, i.e., the delay of a 'packet' (a fluid particle) that arrives at the queue at an arbitrary point in time, (iii) the flow transfer delay, i.e., the time elapsed between arrival of a flow and the M. Mandjes' work has been carried out partly in the Dutch BSIK/BRICKS project. epoch that all its traffic has been put into the queue, and (iv) the sojourn time, i.e., the flow transfer time increased by the time it takes before the last fluid particle of the flow is served. For each of these random variables we compute the Laplace transform. The corresponding tail probabilities decay exponentially, as is shown by a large-deviations analysis.