The IEEE has standardized the 802.11 protocol for wireless local area networks. The primary medium access control (MAC) technique of 802.11 is called the distributed coordination function (DCF). The DCF is a carrier sense multiple access with collision avoidance (CSMA/CA) scheme with binary slotted exponential backoff. This paper provides a simple, but nevertheless extremely accurate, analytical model to compute the 802.11 DCF throughput, in the assumption of finite number of terminals and ideal channel conditions. The proposed analysis applies to both the packet transmission schemes employed by DCF, namely, the basic access and the RTS/CTS access mechanisms. In addition, it also applies to a combination of the two schemes, in which packets longer than a given threshold are transmitted according to the RTS/CTS mechanism. By means of the proposed model, we provide an extensive throughput performance evaluation of both access mechanisms of the 802.11 protocol.

To satisfy the emerging need of wireless data communications, the IEEE is currently standardizing the 802.11 protocol for wireless local area networks. This standard adopts a CSMA/CA medium access control protocol with exponential backoff. We present a simple analytical model to compute the saturation throughput performance in the presence of a finite number of terminals and in the assumption of ideal channel conditions. The model applies to both basic and request-to-send/clear-to-send (RTS/CTS) access mechanisms. Comparison with simulation results shows that the model is extremely accurate in predicting the system throughput.

The IEEE 802.11 protocol for wireless local area networks adopts a CSMA/CA protocol with exponential backoff as medium access control technique. As the throughput performance of such a scheme becomes critical when the number of mobile stations increases, in this paper we propose an adaptive contention window mechanism, which dynamically selects the optimal backoff window according to the estimate of the number of contending stations. We show that this technique leads to stable behavior, and it outperforms the standard protocol when the network load and the number of mobile stations are high. We also investigate the CSMA/CA with the optional RTS/CTS technique, and we show that our adaptive technique reaches better performance only when the packet size is short. Finally, the performance of a system environment with hidden terminals show that the RTS/CTS mechanism, which can also be used in conjunction with the adaptive contention window mechanism, provides significant improvements.

Software Defined Networking envisions smart centralized controllers governing the forwarding behavior of dumb low-cost switches. But are "dumb" switches an actual strategic choice, or (at least to some extent) are they a consequence of the lack of viable alternatives to OpenFlow as programmatic data plane forwarding interface? Indeed, some level of (programmable) control logic in the switches might be beneficial to offload logically centralized controllers (de facto complex distributed systems) from decisions just based on local states (versus network-wide knowledge), which could be handled at wire speed inside the device itself. Also, it would reduce the amount of flow processing tasks currently delegated to specialized middleboxes. The underlying challenge is: can we devise a stateful data plane programming abstraction (versus the stateless OpenFlow match/action table) which still entails high performance and remains consistent with the vendors' preference for closed platforms? We posit that a promising answer revolves around the usage of extended finite state machines, as an extension (super-set) of the OpenFlow match/action abstraction. We concretely turn our proposed abstraction into an actual table-based API, and, perhaps surprisingly, we show how it can be supported by (mostly) reusing core primitives already implemented in OpenFlow devices.

This letter presents a new approach to evaluate the throughput/delay performance of the 802.11 distributed coordination function (DCF). Our approach relies on elementary conditional probability arguments rather than bidimensional Markov chains (as proposed in previous models) and can be easily extended to account for backoff operation more general than DCF's one.