# A Software-Defined Networking Framework to Provide Dynamic QoS Management in IEEE 802.11 Networks
## 5 Related Works
In this case, all the stations update the \(CW_{min}\) parameter to the same value, which is computed at the access point. This \(CW_{min}\) parameter is computed considering the maximum collision probability among all the stations, which report an explicit feedback to the access point containing measurements of their individual collision probabilities. If the maximum collision probability exceeds an upper control threshold, the \(CW_{min}\) is doubled respect to the behavior defined by the IEEE 802.11e standard. If the probability is below a lower threshold, the \(CW_{min}\) is decreased by half. After a contention window adaptation, the algorithms waits for a period \(\tau\) before changing the \(CW_{min}\) value again. In this proposal, the network resources are not properly used. Assuming that all the stations have the same behavior is not a good statement, considering that in a wireless medium the channel conditions can only change for some stations. In general, the \(CW_{min}\) adaptation mechanisms that are executed periodically can be divided into two types: _Multiplicative Increase-Multiplicative Decrease_ (MIMD) and _Additive Increase-Additive Decrease_ (AIAD) schemes. Authors in [23; 24; 25; 26] propose MIMD solutions. The multiplication factor is defined by a function of the priority and the collision rate, or simply by using a fixed value. Authors in [21; 27; 28] use AIAD schemes. The additive changes of the contention window depend on the collision rate, the priority, or simply fix values are used. On the other hand, the modification of the \(CW_{min}\) parameter has been applied in different environments. [29; 30] try to solve the throughput unfairness problem inherent to WiFi networks where devices of _a/b/g_ and \(n\) types can coexist. Slow stations occupy the channel more time to transfer the same amount of data. This fact degrades significantly the performance of high-speed stations and decreases the overall network throughput. To solve this problem, faster stations should get a higher chance of accessing the medium (i.e., get more transmission opportunities) than slower ones. This can be achieved via scaling down their contention windows or by scaling up contention windows used by slow stations. However, this proposal only takes into account the WiFi standard of every station, that is, it does not take into account the channel conditions at all. In multihop wireless networks, packets from a source node are relayed by intermediate nodes (relay nodes) towards their destination along a multihop wireless path. Ideally, in this scenario, a node should not transmit to the relay node more packets than the relay node can forward. In [31], authors propose a fully distributed contention window adaptation mechanism that adjusts the channel access probability depending on the difference between the incoming and outgoing traffic at each node, in order to equate the traffic forwarding capabilities among all the nodes in the path. Ref. [32] considers vehicular networks based on IEEE 802.11. In this scenario, it is proposed to adjust the \(CW_{min}\) parameter depending on the local node density. For that, five different mechanisms for local density estimation are proposed and evaluated. Results show the efficiency and simplicity of such mechanisms, so they recommended as building blocks of any architecture for VANET congestion control. There are a set of works that propose to obtain the exact value of the \(CW\) in the backoff procedure instead of just modify the \(CW_{min}\) parameter. In [33], authors propose to turn off the binary exponential backoff algorithm of IEEE 802.11 and use an appropriate fixed value for \(W\), according to the node density and the instantaneous PER. To estimate the number of competing stations (\(M\)), stations should measure two variables: the number of slots in which the station does not transmit, and the number of busy slots whose energy level measured is higher than a predefined value.