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Performance Ehancement of Congestion Control Algorithm Through Traffic Flow Istinction

Peyman, Zakariaei | 2012

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  1. Type of Document: M.Sc. Thesis
  2. Language: Farsi
  3. Document No: 43573 (19)
  4. University: Sharif University of Technology
  5. Department: Computer Engineering
  6. Advisor(s): Jahangir, Amir Hossein
  7. Abstract:
  8. Congestion is an important issue in the network environment. To keep stable the perfor-mance of the network, congestion control algorithms have been extensively studied. Queue management method employed by the routers is one of the important issues in the congestion control study. Active Queue Management (AQM) has been proposed for early detection of congestion inside the network. AQM mechanisms control the queue length in a router by dropping arriving packets. The Random Early Detection (RED) is the most popular AQM mechanism used in routers on the Intenet to allow network users to simultaneously achieve high throughput and low average delay. The RED algorithm may cause heavy oscillation of average queue length and induce network instability. So performance of RED algorithm decreases significantly under certain conditions. In this thesis an algorithm is implemented so that RED’s performance will be improved. This algorithm is based on flow distinction. First, it extracts 4 features of packets, namely, packet size, each flow’s packet count, interarrival time and flow duration. Then, certain weights are assigned to these features and according to weights’ values, the probability of packet drop is calculated. The results show that this algorithm improves the performance of RED algorithm, in different network traffic conditions, by 4 to 6 percents. Network’s performance improvement reaches more than 7 percent in some cases, though
  9. Keywords:
  10. Active Queue Management (AQM) ; Congestion Control ; Delay ; Service Quality ; Timing Jitter ; Drop Rate ; Random Early Detection (RED)Algorithm

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