Analysis of Multiple Flows using Different High Speed TCP protocols on a General Network

We develop analytical tools for performance analysis of multiple TCP flows (which could be using TCP CUBIC, TCP Compound, TCP New Reno) passing through a multi-hop network. We first compute average window size for a single TCP connection (using CUBIC or Compound TCP) under random losses. We then consider two techniques to compute steady state throughput for different TCP flows in a multi-hop network. In the first technique, we approximate the queues as M/G/1 queues. In the second technique, we use an optimization program whose solution approximates the steady state throughput of the different flows. Our results match well with ns2 simulations.Comment: Submitted to Performance Evaluatio

Stochastic Models of TCP Flows over 802 11 WLANs

This technical report develops an analytical framework to model the interaction between TCP and 802:11 MAC protocol over a WLAN, when concurrent TCP downlink and uplink connections are active. Assuming a TCP advertised window equal to one, we formulate a Markov model to characterize the dynamic network contention level, de ned as the expected number of wireless stations having at least a frame to transmit. Exploiting the stochastic characterization of the dynamic contention level induced by the TCP ow control, we develop an accurate model of the MAC protocol behavior to evaluate the TCP throughput performance. Comparison with simulation results validates the model, which provides the analytical basis for the optimization of the system performance. In particular, we prove that using a TCP advertised window equal to one ensures a fair access to the TCP ows of the channel bandwidth, irrespective of the number of TCP downlink or uplink connections. Moreover, we show that the aggregate TCP throughput is almost independent of the number of wireless stations in the network

Self-similar traffic and network dynamics

Copyright © 2002 IEEEOne of the most significant findings of traffic measurement studies over the last decade has been the observed self-similarity in packet network traffic. Subsequent research has focused on the origins of this self-similarity, and the network engineering significance of this phenomenon. This paper reviews what is currently known about network traffic self-similarity and its significance. We then consider a matter of current research, namely, the manner in which network dynamics (specifically, the dynamics of transmission control protocol (TCP), the predominant transport protocol used in today's Internet) can affect the observed self-similarity. To this end, we first discuss some of the pitfalls associated with applying traditional performance evaluation techniques to highly-interacting, large-scale networks such as the Internet. We then present one promising approach based on chaotic maps to capture and model the dynamics of TCP-type feedback control in such networks. Not only can appropriately chosen chaotic map models capture a range of realistic source characteristics, but by coupling these to network state equations, one can study the effects of network dynamics on the observed scaling behavior. We consider several aspects of TCP feedback, and illustrate by examples that while TCP-type feedback can modify the self-similar scaling behavior of network traffic, it neither generates it nor eliminates it.Ashok Erramilli, Matthew Roughan, Darryl Veitch and Walter Willinge

Performance Modelling and Measurements of TCP Transfer Throughput in 802.11based WLANs

The growing popularity of the 802.11 standard for building local wireless networks has generated an extensive literature on the performance modelling of its MAC protocol. However, most of the available studies focus on the throughput analysis in saturation conditions, while very little has been done on investigating the interactions between the 802.11 MAC protocol and closed-loop transport protocols such as TCP. This paper addresses this issue by developing an analytical model to compute the stationary probability distribution of the number of backlogged nodes in a WLAN in the presence of persistent TCP-controlled download and upload data transfers. By embedding the network backlog distribution in the MAC protocol modelling, we can precisely estimate the throughput performance of TCP connections. A large set of experiments conducted in a real network validates the model correctness for a wide range of configurations. A particular emphasis is devoted to investigate and explain the TCP fairness characteristics. Our analytical model and the supporting experimental outcomes demonstrate that using default settings for the capacity of devices\u27 output queues provides a fair allocation of channel bandwidth to the TCP connections, independently of the number of downstream and upstream flows. Furthermore, we show that the TCP total throughput does not degrade by increasing the number of wireless stations

Queues with Congestion-dependent Feedback

This dissertation expands the theory of feedback queueing systems and applies a number of these models to a performance analysis of the Transmission Control Protocol, a flow control protocol commonly used in the Internet

Robust Mobile Data Transport: Modeling, Measurements, and Implementation

Advances in wireless technologies and the pervasive influence of multi-homed devices have significantly changed the way people use the Internet. These changes of user behavior and the evolution of multi-homing technologies have brought a huge impact to today\u27s network study and provided new opportunities to improve mobile data transport. In this thesis, we investigate challenges related to human mobility, with emphases on network performance at both system level and user level. More specifically, we seek to answer the following two questions: 1) How to model user mobility in the networks and use the model for network provisioning? 2) Is it possible to utilize network diversity to provide robust data transport in wireless environments? We first study user mobility in a large scale wireless network. We propose a mixed queueing model of mobility and show that this model can accurately predict both system-level and user-level performance metrics. Furthermore, we demonstrate how this model can be used for network dimensioning. Secondly, with the increasing demand of multi-homed devices that interact with heterogeneous networks such as WiFi and cellular 3G/4G, we explore how to leverage this path diversity to assist data transport. We investigate the technique of multi-path TCP (MPTCP) and evaluate how MPTCP performs in the wild through extensive measurements in various wireless environments using WiFi and cellular 3G/4G simultaneously. We study the download latencies of MPTCP when using different congestion controllers and number of paths under various traffic loads and over different cellular carriers. We further study the impact of short flows on MPTCP by modeling MPTCP\u27s delay startup mechanism of additional flows. As flow sizes increase, we observe that traffic in cellular networks exhibits large and varying packet round trip times, called bufferbloat. We analyze the phenomenon of bufferbloat, and illustrate how bufferbloat can result in numerous MPTCP performance issues. We provide an effective solution to mitigate the performance degradation. Finally, as popular content is replicated at multiple locations, we develop mechanisms that take advantage of this source diversity along with path diversity to provide robust mobile data transport. We demonstrate this in the context of online video streaming, because of its popularity and significant contribution to Internet traffic. We therefore propose MSPlayer, a client-based solution for online video streaming that adjusts network traffic distribution over each path to network dynamics. MSPlayer bypasses the deployment limitations of MPTCP while maintaining the benefits of path diversity, and exploits different content sources simultaneously. MSPlayer can significantly reduce video start-up latency and quickly refill playout buffer for high quality video streaming. We evaluate MSPlayer\u27s performance through YouTube

DYNAMICS OF RANDOM EARLY DETECTION GATEWAY UNDER A LARGE NUMBER OF TCP FLOWS

While active queue management (AQM) mechanisms such as Random Early Detection (RED) are widely deployed in the Internet, they are rarely utilized or otherwise poorly configured. The problem stems from a lack of a tractable analytical framework which captures the interaction between the TCP congestion-control and AQM mechanisms. Traditional TCP traffic modeling has focused on "micro-scale" modeling of TCP, i.e., detailed modeling of a single TCP flow. While micro-scale models of TCP are suitable for understanding the precise behavior of an individual flow, they are not well suited to the situation where a large number of TCP flows interact with each other as is the case in realistic networks. In this dissertation, an innovative approach to TCP traffic modeling is proposed by considering the regime where the number of TCP flows competing for the bandwidth in the bottleneck RED gateway is large. In the limit, the queue size and the aggregate TCP traffic can be approximated by simple recursions which are independent of the number of flows. The limiting model is therefore scalable as it does not suffer from the state space explosion. The steady-state queue length and window distribution can be evaluated from well-known TCP models. We also extend the analysis to a more realistic model which incorporates session-level dynamics and heterogeneous round-trip delays. Typically, ad-hoc assumptions are required to make the analysis for models with session-level dynamics tractable under a certain regime. In contrast, our limiting model derived here is compatible with other previously proposed models in their respective regime without having to rely on ad-hoc assumptions. The contributions from these additional layers of dynamics to the asymptotic queue are now crisply revealed through the limit theorems. Under mild assumptions, we show that the steady-state queue size depends on the file size and round-trip delay only through their mean values. We obtain more accurate description of the queue dynamics by means of a Central Limit analysis which identifies an interesting relationship between the queue fluctuations and the random packet marking mechanism in AQM. The analysis also reveals the dependency of the magnitude of the queue fluctuations on the variability of the file size and round-trip delay. Simulation results supporting conclusions drawn from the limit theorems are also presented

Traffic measurement and analysis

Measurement and analysis of real traffic is important to gain knowledge about the characteristics of the traffic. Without measurement, it is impossible to build realistic traffic models. It is recent that data traffic was found to have self-similar properties. In this thesis work traffic captured on the network at SICS and on the Supernet, is shown to have this fractal-like behaviour. The traffic is also examined with respect to which protocols and packet sizes are present and in what proportions. In the SICS trace most packets are small, TCP is shown to be the predominant transport protocol and NNTP the most common application. In contrast to this, large UDP packets sent between not well-known ports dominates the Supernet traffic. Finally, characteristics of the client side of the WWW traffic are examined more closely. In order to extract useful information from the packet trace, web browsers use of TCP and HTTP is investigated including new features in HTTP/1.1 such as persistent connections and pipelining. Empirical probability distributions are derived describing session lengths, time between user clicks and the amount of data transferred due to a single user click. These probability distributions make up a simple model of WWW-sessions