Adaptive Quality of Service Engine With Dynamic Queue Control

<p>While the current routing and congestion control algorithms in use today are often sufficient for networks with relatively static topology these algorithms may not be sufficient for military networks where a certain level of quality of service (QoS) needs to be achieved to complete a mission. Current networking technology limits a network's ability to adapt to changes and interactions in the network often resulting in sub-optimal performance. This research investigates the use of queue size predictions to create a network controller to optimize computer networks. These queue size predictions are made possible through the use of Kalman filters to detect network congestion. The premise is that intelligent agents can use such predictions to form context-aware cognitive processes for managing communication in mobile networks. The network controller designed and implement in this thesis will take in the current and predicted network conditions and make intelligent choices to optimize the network.</p><p>This work has been selected by scholars as being culturally important and is part of the knowledge base of civilization as we know it. This work was reproduced from the original artifact and remains as true to the original work as possible. Therefore you will see the original copyright references library stamps (as most of these works have been housed in our most important libraries around the world) and other notations in the work.</p><p>This work is in the public domain in the United States of America and possibly other nations. Within the United States you may freely copy and distribute this work as no entity (individual or corporate) has a copyright on the body of the work.</p><p>As a reproduction of a historical artifact this work may contain missing or blurred pages poor pictures errant marks etc. Scholars believe and we concur that this work is important enough to be preserved reproduced and made generally available to the public. We appreciate your support of the preservation process and thank you for being an important part of keeping this knowledge alive and relevant.</p>