dc.contributor.advisor | Akar, Nail | |
dc.contributor.author | Kurugöl, Sıla | |
dc.date.accessioned | 2016-07-01T11:07:49Z | |
dc.date.available | 2016-07-01T11:07:49Z | |
dc.date.issued | 2006 | |
dc.identifier.uri | http://hdl.handle.net/11693/29884 | |
dc.description | Cataloged from PDF version of article. | en_US |
dc.description.abstract | Best effort service, used to transport the Internet traffic today, does not provide
any QoS assurances. Intserv, DiffServ and recently proposed Proportional Diff-
Serv architectures have been introduced to provide QoS. In these architectures,
some applications with more stringent QoS requirement such as real time traffic
are prioritized, while elastic flows share the remaining bandwidth. As opposed
to the well studied differential treatment of delay and/or loss sensitive traffic to
satisfy QoS constraints, our aim is satisfy QoS requirements of elastic traffic at
the flow level. We intend to maintain different average rate levels for different
classes of elastic traffic. For differential treatment of elastic flows, a dynamic variant
of Deficit Round Robin Scheduler (DRR) is used as oppose to a FIFO queue.
In this scheduling algorithm, all classes are served in a round robin fashion in
proportion to their weights at each round. The main difference of our scheduler
from the original DRR scheduler is that, we update the weights, which are called
quantums of the scheduler at each round in response to the feedback from the
network, which is in terms of the rate of phantom connection sharing capacity
fairly with the other flows in the same queue. According to the rate measured in the last time interval, the controller updates the weights in proportion with the
bandwidth requirements of each class to satisfy their QoS requirements, while
the remaining bandwidth will be used by the best effort traffic. In order to find
an optimal policy for the controller a simulation-based learning algorithm is performed
using a processor sharing model of TCP, then the resultant policies are
applied to a more realistic scenario to solve Dynamic DRR scheduling problem
through ns-2 simulations. | en_US |
dc.description.statementofresponsibility | Kurugöl, Sıla | en_US |
dc.format.extent | xv, 82 leaves, illustrations | en_US |
dc.language.iso | English | en_US |
dc.rights | info:eu-repo/semantics/openAccess | en_US |
dc.subject | Dynamic Deficit Round Robin Scheduling | en_US |
dc.subject | Reinforcement Learning | en_US |
dc.subject | QoS | en_US |
dc.subject | Elastic Traffic | en_US |
dc.subject.lcc | T57.85 .K87 2006 | en_US |
dc.subject.lcsh | Network analysis (Planning) | en_US |
dc.title | A dynamic DRR scheduling algorithm for flow level QOS assurances for elastic traffic | en_US |
dc.type | Thesis | en_US |
dc.department | Department of Electrical and Electronics Engineering | en_US |
dc.publisher | Bilkent University | en_US |
dc.description.degree | M.S. | en_US |
dc.identifier.itemid | BILKUTUPB100087 | |