End-to-end versus explicit feedback measurement in 802.11 networks

Higher layer protocols in wireless networks need to dynamically adapt to observed network response. The common approach is that each session employs end-to-end monitoring to estimate quantities of interest, like delay, delay jitter and available bandwidth. A less conventional approach is to employ lower layer explicit feedback mechanisms in place or in aid of end-to-end efforts. Available bandwidth measurements are known to follow multi-modal distributions and therefore are especially difficult to measure and filter, even in wired networks. In 802.11-based multi-hop networks obtaining usable end-to-end measurements is questionable. They are affected by a combination of a large number of transient variables due to the virtual carrier sense, head of line problems on each link and mobility. Motivated by this, we are developing a network explicit feedback mechanism. Our study of this accurate network feedback architecture aids in the cost/benefit analysis of an important trade-off: deployment of network support mechanisms for transports and QoS, versus the simple, scalable and easily deployable end-to-end solution. We test our solution in: (i) multimedia adaptation and (ii) measurement based call admission. Loss rates of end-to-end adaptive video and audio connections have been more than 4 times higher than in the network feedback case. A simple call admission strategy has also proved very effective using the feedback. In our experiments it led the network to a maximal performance and stable operating point.