Markov approximation for combinatorial network optimization
INFOCOM'10 Proceedings of the 29th conference on Information communications
Proceedings of the eleventh ACM international symposium on Mobile ad hoc networking and computing
Insensitivity and stability of random-access networks
Performance Evaluation
On the performance of TCP over throughput-optimal CSMA
Proceedings of the Nineteenth International Workshop on Quality of Service
TCP performance optimization in multi-cell WLANs
Performance Evaluation
The effect of contention in CSMA networks: Model and fairness protocol
Performance Evaluation
Extra back-off flow control in multi-hop wireless networks
Performance Evaluation
Capacity of large-scale CSMA wireless networks
IEEE/ACM Transactions on Networking (TON)
Backlog-based random access in wireless networks: fluid limits and delay issues
Proceedings of the 23rd International Teletraffic Congress
IEEE 802.11 saturation throughput analysis in the presence of hidden terminals
IEEE/ACM Transactions on Networking (TON)
IEEE/ACM Transactions on Networking (TON)
Applications of belief propagation in CSMA wireless networks
IEEE/ACM Transactions on Networking (TON)
Delays and mixing times in random-access networks
Proceedings of the ACM SIGMETRICS/international conference on Measurement and modeling of computer systems
IEEE/ACM Transactions on Networking (TON)
Delay performance in random-access grid networks
Performance Evaluation
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This work started out with our discovery of a pattern of throughput distributions among links in IEEE 802.11 networks from experimental results. This pattern gives rise to an easy computation method, which we term back-of-the-envelop (BoE) computation. For many network configurations, very accurate results can be obtained by BoE within minutes, if not seconds, by simple hand computation. This allows us to make shortcuts in performance evaluation, bypassing complicated stochastic analysis. To explain BoE, we construct a theory based on the model of an “ideal CSMA network” (ICN). The BoE computation method emerges from ICN when we take the limit c \to 0, where c is the ratio of the mean backoff countdown time to the mean transmission time in the CSMA protocol. Importantly, we derive a new mathematical result: the link throughputs of ICN are insensitive to the distributions of the backoff countdown time and transmission time (packet duration) given the ratio of their means c. This insensitivity result explains why BoE works so well for practical 802.11 networks, in which the backoff countdown process is one that has memory, and in which the packet size can be arbitrarily distributed. Our results indicate that BoE is a good approximation technique for modest-size networks such as those typically seen in 802.11 deployments. Beyond explaining BoE, the theoretical framework of ICN is also a foundation for fundamental understanding of very-large-scale CSMA networks. In particular, ICN is similar to the Ising model in statistical physics used to explain phenomena arising out of the interactions of a large number of entities. Many new research directions arise out of the ICN model.