Analysis of the High - Speed Network Performance through a Prediction Feedback Based Model

DES-Chan is a framework for experimentally driven research on distributed channel assignment algorithms in wireless mesh networks. DES-Chan eases the development process by providing a set of common services required by distributed channel assignment algorithms. A new challenge for channel assignment algorithms are sources of external interferences. With the increasing number of wireless devices in the unlicensed radio spectrum, co-located devices that share the same radio channel may have a severe impact on the network performance. DES-Chan provides a sensing component to detect such external devices and predict their future activity. As a proof of concept, the authors present a reference implementation of a distributed greedy channel assignment algorithm. The authors evaluate its performance in the DES-Testbed, a multi-transceiver wireless mesh network with 128 nodes at the Freie Universität Berlin.