Queueing Systems: Theory and Applications
Waiting Time Distributions for Processor-Sharing Systems
Journal of the ACM (JACM)
Insensitivity in processor-sharing networks
Performance Evaluation
Models of Network Access Using Feedback Fluid Queues
Queueing Systems: Theory and Applications
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 fluid system with coupled input and output, and its application to bottlenecks in ad hoc networks
Queueing Systems: Theory and Applications
Fluid-flow modeling of a relay node in an IEEE 802.11 wireless ad-hoc network
ITC20'07 Proceedings of the 20th international teletraffic conference on Managing traffic performance in converged networks
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
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In this paper we model and analyze a relay node in a wireless ad-hoc network; the capacity available at this node is used to both transmit traffic from the source nodes (towards the relay node), and to serve traffic at the relay node (so that it can be forwarded to successor nodes). Clearly, a network node that is used more heavily than others is prone to becoming a performance bottleneck. Therefore we consider the situation that the relay node obtains a share of the capacity that is m times as large as the share that each source node receives. The main performance metrics considered are the workload at the relay node and the average overall flow transfer time, i.e., the average time required to transmit a flow from a source node via the relay node to the destination. Our aim is to find expressions for these performance metrics for a general resource-sharing ratio m, as well as a general flow-size distribution. The analysis consists of the following steps. First, for the special case of exponential flow sizes we analyze the source-node dynamics, as well as the workload at the relay node by a fluid-flow queueing model. Then we observe from extensive numerical experimentation over a broad set of parameter values that the distribution of the number of active source nodes is actually insensitive to the flow-size distribution. Using this remarkable (empirical) result as an approximation assumption, we obtain explicit expressions for both the mean workload at the relay node and the overall flow transfer time, both for general flow-size distributions.