Study on the Performance of TCP over 10Gbps High Speed Networks

Internet traffic is expected to grow phenomenally over the next five to ten years. To cope with such large traffic volumes, high-speed networks are expected to scale to capacities of terabits-per-second and beyond. Increasing the role of optics for packet forwarding and transmission inside the high-speed networks seems to be the most promising way to accomplish this capacity scaling. Unfortunately, unlike electronic memory, it remains a formidable challenge to build even a few dozen packets of integrated all-optical buffers. On the other hand, many high-speed networks depend on the TCP/IP protocol for reliability which is typically implemented in software and is sensitive to buffer size. For example, TCP requires a buffer size of bandwidth delay product in switches/routers to maintain nearly 100\% link utilization. Otherwise, the performance will be much downgraded. But such large buffer will challenge hardware design and power consumption, and will generate queuing delay and jitter which again cause problems. Therefore, improve TCP performance over tiny buffered high-speed networks is a top priority. This dissertation studies the TCP performance in 10Gbps high-speed networks. First, a 10Gbps reconfigurable optical networking testbed is developed as a research environment. Second, a 10Gbps traffic sniffing tool is developed for measuring and analyzing TCP performance. New expressions for evaluating TCP loss synchronization are presented by carefully examining the congestion events of TCP. Based on observation, two basic reasons that cause performance problems are studied. We find that minimize TCP loss synchronization and reduce flow burstiness impact are critical keys to improve TCP performance in tiny buffered networks. Finally, we present a new TCP protocol called Multi-Channel TCP and a new congestion control algorithm called Desynchronized Multi-Channel TCP (DMCTCP). Our algorithm implementation takes advantage of a potential parallelism from the Multi-Path TCP in Linux. Over an emulated 10Gbps network ruled by routers with only a few dozen packets of buffers, our experimental results confirm that bottleneck link utilization can be much better improved by DMCTCP than by many other TCP variants. Our study is a new step towards the deployment of optical packet switching/routing networks

On the performance of machine-type communications networks under Markovian arrival sources

Abstract. This thesis evaluates the performance of reliability and latency in machine type communication networks, which composed of single transmitter and receiver in the presence of Rayleigh fading channel. The source’s traffic arrivals are modeled as Markovian processes namely Discrete-Time Markov process, Fluid Markov process, Discrete-Time Markov Modulated Poisson process and Continuous-Time Markov Modulated Poisson process, and delay/buffer overflow constraints are imposed. Our approach is based on the reliability and latency outage probability, where transmitter not knowing the channel condition, therefore the transmitter would be transmitting information over the fixed rate. The fixed rate transmission is modeled as a two-state Discrete-time Markov process, which identifies the reliability level of wireless transmission. Using effective bandwidth and effective capacity theories, we evaluate the trade-off between reliability-latency and identify QoS requirement. The impact of different source traffic originated from MTC devices under QoS constraints on the effective transmission rate are investigated

A critical look at power law modelling of the Internet

This paper takes a critical look at the usefulness of power law models of the Internet. The twin focuses of the paper are Internet traffic and topology generation. The aim of the paper is twofold. Firstly it summarises the state of the art in power law modelling particularly giving attention to existing open research questions. Secondly it provides insight into the failings of such models and where progress needs to be made for power law research to feed through to actual improvements in network performance.Comment: To appear Computer Communication

Dynamic routing optimization using traffic prediction

In this dissertation, a new efficient routing maintenance algorithm, called Predicting of Future Load-based Routing (PFLR), is introduced for optimizing the routing performance in IP-based networks. The main idea of PFLR algorithm is combing the predicted link load with the current link load with an effective method to optimize the link weights and so reduce the network congestions. Another research objective is introducing a new efficient Traffic Engineering (TE) algorithm, called Prediction-based Decentralized Routing (PDR) algorithm, which is fully decentralized and self-organized approach

Managing the Bursty Nature of Packet Traffic using the BPTraSha Algorithm

The rapid development of network technologies has widened the scope of Internet applications and, in turn, increased both Internet traffic and the need for its accurate measurement, modelling and control. Various researchers have reported that traffic measurements demonstrate considerable burstiness on several time scales, with properties of self-similarity. The self-similar nature of this data traffic may exhibit spikiness and burstiness on large scales with such behaviour being caused by strong dependence characteristics in data: that is, large values tend to come in clusters and clusters of clusters and so on. Several studies have shown that TCP, the dominant network (Internet) transport protocol, contributes to the propagation of self-similarity. Bursty traffic can affect the Quality of Service of all traffic on the network by introducing inconsistent latency. It is easier to manage the workloads under less bursty (i.e. smoother) conditions. In this paper, we examine the use of a novel algorithm, the Bursty Packet Traffic Shaper (BPTraSha), for traffic shaping, which can smooth out the traffic burstiness. Experimental results show that this approach allows significant traffic control by smoothing the incoming traffic. BPTraSha can be implemented on the distribution router buffer so that the traffic’s bursty nature can be modified before it is transmitted over the core 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

Investigating self-similarity and heavy tailed distributions on a large scale experimental facility

After seminal work by Taqqu et al. relating self-similarity to heavy tail distributions, a number of research articles verified that aggregated Internet traffic time series show self-similarity and that Internet attributes, like WEB file sizes and flow lengths, were heavy tailed. However, the validation of the theoretical prediction relating self-similarity and heavy tails remains unsatisfactorily addressed, being investigated either using numerical or network simulations, or from uncontrolled web traffic data. Notably, this prediction has never been conclusively verified on real networks using controlled and stationary scenarii, prescribing specific heavy-tail distributions, and estimating confidence intervals. In the present work, we use the potential and facilities offered by the large-scale, deeply reconfigurable and fully controllable experimental Grid5000 instrument, to investigate the prediction observability on real networks. To this end we organize a large number of controlled traffic circulation sessions on a nation-wide real network involving two hundred independent hosts. We use a FPGA-based measurement system, to collect the corresponding traffic at packet level. We then estimate both the self-similarity exponent of the aggregated time series and the heavy-tail index of flow size distributions, independently. Comparison of these two estimated parameters, enables us to discuss the practical applicability conditions of the theoretical prediction

Performance modeling of congestion control and resource allocation under heterogeneous network traffic. Modeling and analysis of active queue management mechanism in the presence of poisson and bursty traffic arrival processes.

Along with playing an ever-increasing role in the integration of other communication networks and expanding in application diversities, the current Internet suffers from serious overuse and congestion bottlenecks. Efficient congestion control is fundamental to ensure the Internet reliability, satisfy the specified Quality-of-Service (QoS) constraints and achieve desirable performance in response to varying application scenarios. Active Queue Management (AQM) is a promising scheme to support end-to-end Transmission Control Protocol (TCP) congestion control because it enables the sender to react appropriately to the real network situation. Analytical performance models are powerful tools which can be adopted to investigate optimal setting of AQM parameters. Among the existing research efforts in this field, however, there is a current lack of analytical models that can be viewed as a cost-effective performance evaluation tool for AQM in the presence of heterogeneous traffic, generated by various network applications. This thesis aims to provide a generic and extensible analytical framework for analyzing AQM congestion control for various traffic types, such as non-bursty Poisson and bursty Markov-Modulated Poisson Process (MMPP) traffic. Specifically, the Markov analytical models are developed for AQM congestion control scheme coupled with queue thresholds and then are adopted to derive expressions for important QoS metrics. The main contributions of this thesis are listed as follows: iii ¿ Study the queueing systems for modeling AQM scheme subject to single-class and multiple-classes Poisson traffic, respectively. Analyze the effects of the varying threshold, mean traffic arrival rate, service rate and buffer capacity on the key performance metrics. ¿ Propose an analytical model for AQM scheme with single class bursty traffic and investigate how burstiness and correlations affect the performance metrics. The analytical results reveal that high burstiness and correlation can result in significant degradation of AQM performance, such as increased queueing delay and packet loss probability, and reduced throughput and utlization. ¿ Develop an analytical model for a single server queueing system with AQM in the presence of heterogeneous traffic and evaluate the aggregate and marginal performance subject to different threshold values, burstiness degree and correlation. ¿ Conduct stochastic analysis of a single-server system with single-queue and multiple-queues, respectively, for AQM scheme in the presence of multiple priority traffic classes scheduled by the Priority Resume (PR) policy. ¿ Carry out the performance comparison of AQM with PR and First-In First-Out (FIFO) scheme and compare the performance of AQM with single PR priority queue and multiple priority queues, respectively