Analysing TCP performance when link experiencing packet loss

Examensarbete för masterexamen

Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.12380/193786
Download file(s):
File Description SizeFormat 
193786.pdfFulltext3.07 MBAdobe PDFView/Open
Type: Examensarbete för masterexamen
Master Thesis
Title: Analysing TCP performance when link experiencing packet loss
Authors: Chowdhury, Sharin
Fatema, Kaniz
Abstract: TCP is a reliable protocol which is capable of handling retransmission and packet loss. In TCP, packet loss is not expected to have a noticeable impact on bandwidth. However, performance was affected even at low packet loss rates (1%) and with an increased rate of packet loss, a drastic drop was observed. To uncover the cause of this unexpected behavior of TCP, a deep analysis of TCP has been accomplished. In this paper we have done a comparison between three different congestion control algorithms (Cubic, Reno and H_TCP) and a deeper analysis of Reno by means of several experimental tests in when the link experiences Data loss and ACK loss. Initially different TCP congestion control algorithms were used to observe their influence on bandwidth rate. Subsequently the TCP variables i.e. advanced window scaling, ECN value, window scaling, TCP no-metric-save value were changed to examine their role in obtaining adequate bandwidth rate with respect to packet drop. In addition to our experimental results, we also include some possible reasons behind the drastic drop in performance rate which was observed. Moreover, experimental results show that the congestion control algorithm H-TCP performed better than Cubic and Reno while link was experiencing packet loss. However, ACK loss didn‟t affect performance that much, and up to 50% loss of ACKs could be tolerated with almost no performance degradation. Keywords: TCP congestion control algorithms, TCP variables, Data loss, ACK loss, Packet loss, Bandwidth rate etc.
Keywords: Data- och informationsvetenskap;Computer and Information Science
Issue Date: 2014
Publisher: Chalmers tekniska högskola / Institutionen för data- och informationsteknik (Chalmers)
Chalmers University of Technology / Department of Computer Science and Engineering (Chalmers)
URI: https://hdl.handle.net/20.500.12380/193786
Collection:Examensarbeten för masterexamen // Master Theses



Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.