Date of Award
2004
Publication Type
Master Thesis
Degree Name
M.Sc.
Department
Computer Science
Keywords
Computer Science.
Supervisor
Aggarwal, A. K.
Rights
info:eu-repo/semantics/openAccess
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Abstract
With the growth of the Internet, the problem of congestion has attained the distinction of being a perennial problem. The Internet community has been trying several approaches for improved congestion control techniques. The end-to-end approach is considered to be the most robust one and it has served quite well until recently, when researchers started to explore the information available at the intermediate node level. This approach triggered a new field called Active Networks where intermediate nodes have a much larger role to play than that of the naive nodes. This thesis proposes an active congestion control (ACC) scheme based on Available Bandwidth-based Congestion Detection (ABCD), which regulates the traffic according to network conditions. Dynamic changes in the available bandwidth can trigger re-negotiation of flow rate. We have introduced packet size adjustment at the intermediate router in addition to rate control at sender node, scaled according to the available bandwidth, which is estimated using three packet probes. To verify the improved scheme, we have extended Ted Faber's ACC work in NS-2 simulator. With this simulator we verify ACC-ABCD's gains such as a marginal improvement in average TCP throughput at each endpoint, fewer packet drops and improved fairness index. Our tests on NS-2 prove that the ACC-ABCD technique yields better results as compared to TCP congestion control with or without the cross traffic. Source: Masters Abstracts International, Volume: 43-03, page: 0870. Adviser: A. K. Aggarwal. Thesis (M.Sc.)--University of Windsor (Canada), 2004.
Recommended Citation
Bharadwaj, Aniruddha, "Active congestion control using ABCD (available bandwidth-based congestion detection)." (2004). Electronic Theses and Dissertations. 887.
https://scholar.uwindsor.ca/etd/887