PERFORMANCE ANALYSIS OF TCP AND TCP-FRIENDLY RATE CONTROL FLOWS IN WIRED AND WIRELESS NETWORKS SUDHARSANAN S R (M.S (By Research), Information Technology) A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE (COMPUTER SCIENCE) DEPARTMENT OF COMPUTER SCIENCE SCHOOL OF COMPUTING NATIONAL UNIVERSITY OF SINGAPORE 2003 Acknowledgements I would like to express my deepest gratitude to my supervisor, Dr Lillykutty Jacob, who guided me in all aspects until the completion of this thesis Her constant support, patience and sincere evaluations made me understand many aspects pertaining to research I am highly grateful to my co-supervisor, Prof A L Ananda, for his encouragement, support and for providing the best work atmosphere His critical advice and suggestions helped me to focus more on work when there were problems I would like to acknowledge Prof Konstantin Avrachenkov, for his insightful discussions, critical comments, and words of encouragement I am thankful to Frank Akujobi, Rupinder Makkar, and Nabil Seddigh for their help regarding the BECN implementation in ns simulator Sincere appreciations should go to my colleagues Aurbind Sharma, Rahul Chaudhary, Sridhar K N, Venkatesh S O and M K Saravanan Special mention to Sridhar K N for his help in the BECN implementation I have not only enjoyed being with you guys but will remember forever the days we spent together I am forever indebted to my parents and my brothers for their constant understanding, endless patience and encouragement This thesis would be incomplete and impossible without the support given by them in every imaginable way i Dedicated To My parents – Smt Vasantha Ranganathan & Sri Ranganathan My Brothers – Sridhar & Sriram For their sacrifices and endless encouragement … ii Table of Contents Acknowledgements i Dedication ii Table of Contents iii List of Figures vi List of Tables viii Abstract ix Chapter 1: Introduction 1.1 Motivation 1.2 Research Objectives 1.3 Contributions of the thesis 1.4 Thesis Organization Chapter 2: Background and Related Work 2.1 Background 2.1.1 Congestion Control in TCP 2.1.2 TCP Friendliness 2.1.3 TCP-Friendly Rate Control 2.1.4 TFRC Protocol 10 2.1.5 Self-Similarity in Network Traffic 12 2.1.5.1 Definition 12 2.1.5.2 Long-range Dependency (LRD) 12 2.1.5.3 Heavy-tailed Distributions 13 2.1.5.4 Hurst Parameter – The Measure of Self-Similarity 14 iii 2.1.5.5 Causes of Self-Similarity 15 2.1.6 Random Early Detection (RED) 16 2.1.7 Explicit Congestion Notification (ECN) 17 2.1.8 Backward Explicit Congestion Notification (BECN) 19 2.2 Related Work 24 2.2.1 Related work on TCP-friendly Rate Control 24 2.2.2 Related work on Self-Similarity, Long-range Dependence and its 26 Impact on Network Performance 26 2.2.3 Related Work on ECN 30 2.2.4 Related work on BECN 31 Chapter 3: Characterization of TCP-Friendly Rate Control (TFRC) Flows 33 3.1 Introduction 33 3.2 Experiments 34 3.2.1 Packet Inter-arrival Time Measurement 34 3.2.2 Packet Delay Measurement 35 3.3 Results 35 3.3.1 Correlation of packet inter-arrival times 38 3.3.2 Correlation between delay and loss 39 3.4 Discussions 41 Chapter 4: Performance Analysis of ECN and BECN enabled TCP flows 43 4.1 Introduction 43 4.2 ECN and BECN Capable Networks 43 4.2.1 TCP Sender Behavior 43 iv 4.2.4 Router Behavior 45 4.3 Analytical Model 46 4.4 Simulation Setup 52 4.5 Results and Discussion 54 4.5.1 Varying number of flows (N) 54 4.5.2 Comparison of ECN and BECN for varying number of flows 59 4.5.3 Varying round-trip time (RTTo) 62 4.5.4 Bottleneck router queue size vs time 71 4.5.5 Experiments with reverse lossy link 72 4.5.6 Experiments with Multiple Bottlenecks 74 Chapter 5: Conclusion 77 References 79 v List of Figures Figure 1: Real-time Internet measurement setup 34 Figure 2: Estimate of the Hurst Parameter by R/S method for real-time measurement (Packet inter-arrival times) (2 – day data) 37 Figure 3: Estimate of the Hurst Parameter by R/S method for real-time measurement (Packet inter-arrival times) (4 – day data) 37 Figure 4: Estimate of the Hurst Parameter by R/S method for real-time measurement (Packet inter-arrival times) (1 – week data) 38 Figure 5: Histogram plot for packet inter-arrival times 39 Figure 6: Delay versus Loss rate 40 Figure 7: Congestion window evolution over time when indications are due to marking 50 Figure 8: Packets sent during a congestion notification period 50 Figure 9: Network Topology 53 Figure 10: Network Topology 54 Figure 11: Analytical and simulation results for ECN 56 Figure 12: Analytical and simulation results for BECN 58 Figure 13: BECN-ISQ traffic versus number of flows 58 Figure 14: Comparison of ECN and BECN for varying number of flows 61 Figure 15: Analytical and simulation results for ECN 63 Figure 16: Analytical and simulation results for BECN 65 Figure 17: BECN-ISQ traffic versus RTTo 65 Figure 18: Analytical and simulation results for ECN 67 Figure 19: Analytical and simulation results for BECN 69 vi Figure 20: BECN-ISQ traffic versus RTTo 69 Figure 21: Instantaneous and average queue sizes for BECN and ECN (No of flows = 22) 72 Figure 22: Comparison of ECN and BECN for varying loss rates 73 Figure 23: Comparison of ECN and BECN for multiple bottlenecks 75 Figure 24: BECN ISQ traffic versus number of flows 75 vii List of Tables Table 1: Estimate of H values by R/S method 36 Table 2: The BECN scaling factor γ versus number of flows 54 Table 3: The BECN scaling factor γ versus round trip delay (minimum no of flows) 66 Table 4: The BECN scaling factor γ versus round trip delay (maximum no of flows) 70 viii Abstract This thesis has two parts: analysis of TCP-Friendly Rate Control (TFRC) flows through real-time measurements, and analysis of Explicit Congestion Notification (ECN) and Backward Explicit Congestion Notification (BECN) enabled TCP flows through analytical modeling and simulation With the rapid increase of multimedia traffic and the deployment of real-time audio/video streaming applications, the current Internet has seen an exponential increase in the percentage of non-TCP traffic These multimedia streaming applications not share the available bandwidth fairly with applications built on TCP This evolution can lead to a congestion collapse and starvation for TCP traffic TCP-friendly protocols have been developed for these multimedia applications that behave fairly with respect to co-existent TCP flows The first part of this thesis analyzes and characterizes the TFRC flows through real-time measurements This study leads to some interesting observations: the aggregate traffic exhibits long-range dependence (LRD) over different levels of aggregation, packet inter-arrival times tend to be correlated, and there exists a correlation between packet loss and delay This measurement and analysis are done only for wired networks The second part of this thesis presents a comparative performance evaluation of ECN and BECN enabled TCP flows In this study, throughput expressions as functions of packet marking probability (p) and round trip time (RTT) are obtained for ECN and BECN enabled TCP flows Comparative performance of the ECN and BECN mechanisms are ix Table 4: The BECN scaling factor γ versus round trip delay (maximum no of flows) RTTo (ms) γ value 120 0.6 140 0.57 160 0.55 180 0.53 200 0.5 In the prediction for BECN, γ is chosen as given in Tables and Figures 15 and 16 show both the analytical and simulation results for ECN and BECN, respectively, for 10 flows Figures 18 and 19 show both the analytical and simulation results for ECN and BECN, respectively, for 22 flows Figures 15 (b), 16 (b), 18 (b) and 19 (b) show that the average queue size decreases with increasing RTTo for both ECN and BECN Naturally, the marking probability also decreases with increasing RTTo (Figures 15 (c), 16 (c), 18 (c) and 19 (c)) This decreasing marking probability combined with increasing RTTo cause the throughput to remain more or less the same with the increasing RTTo (Figures 15 (a), 16 (a), 18 (a) and 19 (a)) Note that with a lesser marking probability, the number of cwnd reductions will be lesser However, after each reduction, it will take longer time for the cwnd to grow to the earlier value because of larger RTTo Comparing Figures 15, 16, 18 and 19, we find that BECN yields slightly higher throughput, while the average queue size remains less for BECN Figures 17 and 20 show the measured ISQ traffic percentage in BECN simulations 70 4.5.4 Bottleneck router queue size vs time In this section we provide the results of bottleneck router queue size variations for ECN and BECN Figure 21 shows the results for RTTo of 140 ms and for 22 flows For less number of flows packets are not dropped for either BECN or ECN flows Due to earlier congestion notification BECN case have lower average and instantaneous queue sizes As the congestion level increases (22 flows), the instantaneous queue size for the ECN case occasionally goes beyond the maximum threshold Since queue variability is less for BECN enabled flows, it offers better network utilization under high congestion (a) Instantaneous and average queue size for BECN 71 (b) Instantaneous and average queue size for ECN Figure 21: Instantaneous and average queue sizes for BECN and ECN (No of flows = 22) 4.5.5 Experiments with reverse lossy link In this case, we investigate the impact of loss of reverse traffic on the behavior of ECN and BECN by controlling the loss rate on the reverse traffic path In particular, we investigate the impact of loss of ECN-Echo ACK and BECN-ISQ packets on the performance of ECN and BECN, respectively For these experiments we use Topology (Fig 9) with random losses introduced for the packets flowing from router R1 to sources S1 – S4 72 (a) Throughput versus loss rate (b) Average queue size versus loss rate Figure 22: Comparison of ECN and BECN for varying loss rates 73 The above figures summarize our observations First, throughput decreases steadily with increase in loss rate No significant difference in throughput was found between the mechanisms Second, due to the loss of ISQs the BECN flows not achieve the early congestion notification and this will cause considerable fluctuation in average queue size However, ECN flows are less affected due to the fact that even if an ECN-Echo ACK is lost, the subsequent ACKs also carry ECN-Echo message In this case, even though there is a gain of RTT it does not reflect on the performance of BECN flows as ISQs are lost This is one reason that BECN does not achieve a better throughput compared to ECN 4.5.6 Experiments with Multiple Bottlenecks (a) Throughput versus number of flows 74 (b) Loss versus number of flows Figure 23: Comparison of ECN and BECN for multiple bottlenecks Figure 24: BECN ISQ traffic versus number of flows 75 These experiments were done using Topology (Figure 10) In multiple bottlenecks scenario, BECN flows perform much better than ECN flows First, it yields higher throughput and second, the loss percentage is significantly less compared to ECN In an ideal multiple bottlenecks scenario where different TCP flows along with an ECN flow compete for bandwidth the BECN flow is bound to perform better This is because when there is congestion each router sends an ISQ to notify its respective source and this makes a BECN flow more efficient than an ECN flow under such conditions (for achieving higher throughput) Whereas in case of an ECN flow the source has to wait for an ECNEcho ACK before reducing its sending rate BECN flow gains by half-RTT Packet loss is less than 4% for a BECN flow compared to an ECN flow (7.5%) In case of a BECN flow when there is a packet loss the source is notified earlier for it to reduce the sending rate which in-turn prevents further packet losses It can also be seen that the percentage of ISQ traffic is less (just above 9.5%) for maximum number of flows and not affect the performance for a BECN flow in this case 76 Chapter Conclusion This thesis makes two contributions: analysis of TCP-Friendly Rate Control (TFRC) flows through real-time measurements, and analysis of Explicit Congestion Notification (ECN) and Backward Explicit Congestion Notification (BECN) enabled TCP flows through analytical modeling and simulation In the first part of this thesis, we characterize the TFRC flows through real-time measurements and present analysis based on packet inter-arrival times, packet delay and packet loss rate This study leads to some interesting observations: the aggregate traffic exhibits long-range dependence (LRD) over different levels of aggregation, packet interarrival times tend to be correlated, and there exists a correlation between packet loss and delay This measurement and analysis are done only for wired networks It is clear that packet delay and loss have tremendous impact on continuous media applications, as both delay and loss result from buffering within the network As packets traverse the network, they are queued in buffers, adding to their end-to-end delay and dropped accordingly due to buffer overflow The correlation between delay and loss, i.e., when the delay increases over a period we can predict that more loss is expected to occur The TFRC sender will reduce its sending rate based on the delay variation and it will decide on the sending rate to maintain a good quality of the continuous media flow However, there will not be any adverse effect to the protocol or network performance from a flow perspective 77 In the second part of this thesis, we extend the analytical model for TCP throughput for the case of ECN and BECN capable networks and validate this model through simulation experiments We evaluate and compare the performance of ECN and BECN mechanisms using homogeneous long-lived FTP flows for various scenarios There is a clear cut advantage in the case of BECN due to the gain in RTT and due to the early congestion notification, which results in significant improvement in performance for the BECN flows These include improvement in throughput and packet loss We also evaluated the performance of ECN and BECN flows with reverse lossy links, where the difference in throughput was not much, but the average queue size for BECN remains less compared to ECN Our simulation with multiple bottlenecks shows that BECN gives much better performance in the improvement of throughput and packet loss Therefore, we conclude that the use of BECN mechanism for congestion control in TCP/IP networks significantly improves performance compared to ECN BECN mechanism should be used to offer improved quality of service on high bandwidth-delay product links For future work, it would be interesting to further examine the following: analysis and characterization of TFRC flows over wireless networks, performance analysis of BECN enabled TCP flows for satellite networks, applicability of ECN and BECN mechanisms for congestion control in mobile ad hoc networks 78 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1994 84 [...]... for ECN and BECN enabled TCP flows and to evaluate the comparative performance of ECN and BECN mechanisms using analytical model and simulation 1.2 Research Objectives The main objective of this research is to evaluate the performance of ECN and BECN enabled TCP flows and TCP- friendly rate control flows for congestion control that gives optimal performance over wired and wireless networks In particular,... related to performance evaluation of TCP and TCP- friendly rate control flows for wired and wireless networks that have been referred in this thesis 2.1.1 Congestion Control in TCP The general congestion control framework of TCP depends on the following four parameters: AIMD, retransmit timer, slow start mechanism, and acknowledgement (ACK) – clocking TCP congestion control is based on additive increase... unicast TCPfriendly [70] The major advantage of TCP friendliness is that it ensures that coexisting TCP flows are given a “fair share” of bandwidth by non -TCP flows (such as UDP flows) , that is the non -TCP flow should not consume more bandwidth than the competing TCP flow This does not necessarily mean that all TCP and TCP- friendly flows on a bottleneck link receive the same throughput [70] Even competing... to this thesis and surveys previously done related work on TFRC, ECN and BECN Chapter 3 details the first contribution of this thesis, characterization of TCP- friendly rate control flows for wired networks through real-time measurements and analysis of some of the major issues The second contribution of this thesis, analysis of ECN and BECN enabled TCP flows through analytical modeling and simulation,... the impact of these factors on the long-term sending rate of GAIMD and examine which relationship between the factors results in TCP- friendliness The so-called binomial congestion control mechanisms proposed in [34] allow for even higher flexibility in the increase/decrease policy The authors show which combinations of parameters result in TCP- friendliness and give an in- depth analysis of some specific... co-existent TCP flows It is important to study and analyze the behavior of TCP- friendly flows where a significant amount of multimedia traffic needs to be handled in the near future Moreover, multimedia traffic flowing out of TCP- friendly protocols have not been studied and analyzed This draws motivation to the first part of this thesis to analyze and characterize TCP- friendly rate control flows through... Characterizing and observing the TCP- friendly rate control protocol (TFRC) flows through real-time measurements ¾ Observing the behavior through packet inter-arrival times, packet loss rates and delay ¾ Obtaining throughput expressions as a function of packet marking probability (p) and round trip time (RTT) for ECN and BECN enabled TCP flows ¾ Validating the analytical model developed for ECN and BECN... of available bandwidth, but also to maintain a relatively steady sending rate at the same time being responsive to congestion [18, 71] The following design principles of equation-based congestion control are contrasting to the behavior of TCP [71]: 9 ¾ It should not probe for available bandwidth aggressively And increase the sending rate slowly in response to a decrease in the loss event rate [71] ¾... on TCP- friendly Rate Control Huge amount of work has been contributed to the field of TCP modeling and validation [27] Especially, the important papers on TCP throughput estimation and simple model for TCP throughput [2, 28, 29] which give a thorough analysis of TCP modeling make a major contribution The TCP throughput equation in this work is considered by most of the current work on modeling for TCP. .. for TCP congestion control developed in [2] and [3] in order to analyze the TCP flow throughput and router buffer queue size in ECN and BECN capable networks We then evaluate comparative performance for varying network load, for different bandwidth-delay product networks, and for single- as well as multiple-bottleneck networks 2 1.1 Motivation The rapid increase in the amount of multimedia traffic and ... of TCP and TCP- friendly rate control flows for wired and wireless networks that have been referred in this thesis 2.1.1 Congestion Control in TCP The general congestion control framework of TCP. .. evaluate the performance of ECN and BECN enabled TCP flows and TCP- friendly rate control flows for congestion control that gives optimal performance over wired and wireless networks In particular,... where infrequent random drops are happening in the network (simulating errors in a wireless environment), and conclude that ECN can help to increase TCP s performance in hybrid wired/ wireless networks