A Comparison of Mechanisms for Improving TCP Performance Over Wireless Links
Total Page:16
File Type:pdf, Size:1020Kb
Load more
Recommended publications
-
Dynamic Optimization of the Quality of Experience During Mobile Video Watching
View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by Ghent University Academic Bibliography Dynamic Optimization of the Quality of Experience during Mobile Video Watching Toon De Pessemier, Luc Martens, Wout Joseph iMinds - Ghent University, Dept. of Information Technology G. Crommenlaan 8 box 201, B-9050 Ghent, Belgium Tel: +32 9 33 14908, Fax:+32 9 33 14899 Email: {toon.depessemier, luc.martens, wout.joseph}@intec.ugent.be Abstract—Mobile video consumption through streaming is Traditionally, network operators and service providers used becoming increasingly popular. The video parameters for an to pay close attention to the Quality of Service (QoS), where optimal quality are often automatically determined based on the emphasis was on delivering a fluent service. QoS is defined device and network conditions. Current mobile video services by the ITU-T as “the collective effect of service perfor- typically decide on these parameters before starting the video mance” [3]. The QoS is generally assessed by objectively- streaming and stick to these parameters during video playback. measured video quality metrics. These quality metrics play a However in a mobile environment, conditions may change sig- nificantly during video playback. Therefore, this paper proposes crucial role in meeting the promised QoS and in improving a dynamic optimization of the quality taking into account real- the obtained video quality at the receiver side [4]. time data regarding network, device, and user movement during Although useful, these objective quality metrics only ad- video playback. The optimization method is able to change the dress the perceived quality of a video session partly, since these video quality level during playback if changing conditions require this. -
Lecture 8: Overview of Computer Networking Roadmap
Lecture 8: Overview of Computer Networking Slides adapted from those of Computer Networking: A Top Down Approach, 5th edition. Jim Kurose, Keith Ross, Addison-Wesley, April 2009. Roadmap ! what’s the Internet? ! network edge: hosts, access net ! network core: packet/circuit switching, Internet structure ! performance: loss, delay, throughput ! media distribution: UDP, TCP/IP 1 What’s the Internet: “nuts and bolts” view PC ! millions of connected Mobile network computing devices: server Global ISP hosts = end systems wireless laptop " running network apps cellular handheld Home network ! communication links Regional ISP " fiber, copper, radio, satellite access " points transmission rate = bandwidth Institutional network wired links ! routers: forward packets (chunks of router data) What’s the Internet: “nuts and bolts” view ! protocols control sending, receiving Mobile network of msgs Global ISP " e.g., TCP, IP, HTTP, Skype, Ethernet ! Internet: “network of networks” Home network " loosely hierarchical Regional ISP " public Internet versus private intranet Institutional network ! Internet standards " RFC: Request for comments " IETF: Internet Engineering Task Force 2 A closer look at network structure: ! network edge: applications and hosts ! access networks, physical media: wired, wireless communication links ! network core: " interconnected routers " network of networks The network edge: ! end systems (hosts): " run application programs " e.g. Web, email " at “edge of network” peer-peer ! client/server model " client host requests, receives -
Bit & Baud Rate
What’s The Difference Between Bit Rate And Baud Rate? Apr. 27, 2012 Lou Frenzel | Electronic Design Serial-data speed is usually stated in terms of bit rate. However, another oft- quoted measure of speed is baud rate. Though the two aren’t the same, similarities exist under some circumstances. This tutorial will make the difference clear. Table Of Contents Background Bit Rate Overhead Baud Rate Multilevel Modulation Why Multiple Bits Per Baud? Baud Rate Examples References Background Most data communications over networks occurs via serial-data transmission. Data bits transmit one at a time over some communications channel, such as a cable or a wireless path. Figure 1 typifies the digital-bit pattern from a computer or some other digital circuit. This data signal is often called the baseband signal. The data switches between two voltage levels, such as +3 V for a binary 1 and +0.2 V for a binary 0. Other binary levels are also used. In the non-return-to-zero (NRZ) format (Fig. 1, again), the signal never goes to zero as like that of return- to-zero (RZ) formatted signals. 1. Non-return to zero (NRZ) is the most common binary data format. Data rate is indicated in bits per second (bits/s). Bit Rate The speed of the data is expressed in bits per second (bits/s or bps). The data rate R is a function of the duration of the bit or bit time (TB) (Fig. 1, again): R = 1/TB Rate is also called channel capacity C. If the bit time is 10 ns, the data rate equals: R = 1/10 x 10–9 = 100 million bits/s This is usually expressed as 100 Mbits/s. -
Detecting Fair Queuing for Better Congestion Control
Detecting Fair Queuing for Better Congestion Control Maximilian Bachl, Joachim Fabini, Tanja Zseby Technische Universität Wien fi[email protected] Abstract—Low delay is an explicit requirement for applications While FQ solves many problems regarding Congestion such as cloud gaming and video conferencing. Delay-based con- Control (CC), it is still not ubiquitously deployed. Flows can gestion control can achieve the same throughput but significantly benefit from knowledge of FQ enabled bottleneck links on the smaller delay than loss-based one and is thus ideal for these applications. However, when a delay- and a loss-based flow path to dynamically adapt their CC. In the case of FQ they can compete for a bottleneck, the loss-based one can monopolize all use a delay-based CCA and otherwise revert to a loss-based the bandwidth and starve the delay-based one. Fair queuing at the one. Our contribution is the design and evaluation of such bottleneck link solves this problem by assigning an equal share of a mechanism that determines the presence of FQ during the the available bandwidth to each flow. However, so far no end host startup phase of a flow’s CCA and sets the CCA accordingly based algorithm to detect fair queuing exists. Our contribution is the development of an algorithm that detects fair queuing at flow at the end of the startup. startup and chooses delay-based congestion control if there is fair We show that this solution reliably determines the presence queuing. Otherwise, loss-based congestion control can be used as of fair queuing and that by using this approach, queuing delay a backup option. -
LTE-Advanced
Table of Contents INTRODUCTION........................................................................................................ 5 EXPLODING DEMAND ............................................................................................... 8 Smartphones and Tablets ......................................................................................... 8 Application Innovation .............................................................................................. 9 Internet of Things .................................................................................................. 10 Video Streaming .................................................................................................... 10 Cloud Computing ................................................................................................... 11 5G Data Drivers ..................................................................................................... 11 Global Mobile Adoption ........................................................................................... 11 THE PATH TO 5G ..................................................................................................... 15 Expanding Use Cases ............................................................................................. 15 1G to 5G Evolution ................................................................................................. 17 5G Concepts and Architectures ................................................................................ 20 Information-Centric -
RTM-100 Troposcatter Modem Improved Range, Stability and Throughput for Troposcatter Communications
RTM-100 Troposcatter Modem Improved range, stability and throughput for troposcatter communications The Raytheon RTM-100 troposcatter modem sets new milestones in troposcatter communications featuring 100 MB throughput. Benefits Superior Performance The use of turbo-coding An industry first, the waveform forward error correction The RTM-100 comes as n Operation up to 100 Mbps of Raytheon’s RTM-100 (FEC) and state-of-the-art a compact 2U rack with troposcatter modem offers digital processing ensures an n Unique waveform for multipath standard 70 MHz inputs/ strong resiliency to multipath, unprecedented throughput cancellation and optimized outputs. algorithms for fading immunity which negatively affects up to 100 Mbps. The modem n Quad diversity with soft decision troposcatter communications. integrates a non-linear digital algorithm Combined with an optimized pre-distortion capability. time-interleaving process and n Highly spectrum-efficient FEC The Gigabit Ethernet (GbE) signal channel diversity, the processing data port and the ability RTM- 100 delivers superior n Dual transmission path with to command and control transmission performance. independent digital pre- the operation over Simple The sophisticated algorithms, distortion Network Management including Doppler n Ethernet data and control Protocol (SNMP) simplify the compensation and maximum interface (SNMP and Web integration of the device into ratio combining between the graphical user interface) a net-centric Internet protocol four diversity inputs, ensure n Compact 2U 19-inch -
On the Goodput of TCP Newreno in Mobile Networks
On the Goodput of TCP NewReno in Mobile Networks Sushant Sharma Donald Gillies Wu-chun Feng Virginia Tech, Blacksburg, VA, USA Qualcomm, San Diego, USA Virginia Tech, Blacksburg, VA, USA Abstract—Next-generation wireless networks such as LTE and WiMax can achieve throughputs of several Mbps with TCP. These higher throughputs, however, can easily be destroyed by frequent handoffs, which occur in urban environments due to shadowing. A primary reason for the throughput drop during handoffs is the out of order arrival of packets at the receiver. As a result, in this paper, we model the precise effect of packet-reordering on the goodput of TCP NewReno. Specifically, we develop a TCP NewReno model that captures the goodput of TCP as a function of round-trip time, average time duration between packet-reorder events, average number of packets reordered during every reorder event, and the congestion window threshold of TCP NewReno. We also developed an emulator that runs on a router to implement packet reordering events from time to time. We validate our NewReno model by comparing the goodput results obtained by transferring data between two hosts connected via the emulator to the goodput results that our model predicts. I. MOTIVATION Next-generation wireless technologies such as WiMax and LTE (long term evolution) offer very high data rates (on Fig. 1. Handoff description. the order of several Mbps) to mobile users. As a result, mobile users will come to expect better peak performance a rare event in the wired Internet [12], [13], [14], [15], and from the networks than from current mobile networks. -
Webrtc Based Network Performance Measurements Miranda Mcclellan
WebRTC Based Network Performance Measurements by Miranda McClellan Submitted to the Department of Electrical Engineering and Computer Science in partial fulfillment of the requirements for the degree of Masters of Engineering in Computer Science and Engineering at the MASSACHUSETTS INSTITUTE OF TECHNOLOGY June 2019 c Massachusetts Institute of Technology 2019. All rights reserved. Author.............................................................. Department of Electrical Engineering and Computer Science May 24, 2019 Certified by. Steven Bauer Research Scientist Thesis Supervisor Accepted by . Katrina LaCurts Chair, Master of Engineering Thesis Committee 2 WebRTC Based Network Performance Measurements by Miranda McClellan Submitted to the Department of Electrical Engineering and Computer Science on May 24, 2019, in partial fulfillment of the requirements for the degree of Masters of Engineering in Computer Science and Engineering Abstract As internet connections achieve gigabit speeds, local area networks (LANs) be- come the main bottleneck for users connection. Currently, network performance tests focus on end-to-end performance over wide-area networks and provide no platform- independent way to tests LANs in isolation. To fill this gap, I developed a suite of network performance tests that run in a web application. The network tests support LAN performance measurement using WebRTC peer-to-peer technology and statis- tically evaluate performance according to the Model-Based Metrics framework. Our network testing application is browser based for easy adoption across platforms and can empower users to understand their in-home networks. Our tests hope to give a more accurate view of LAN performance that can influence regulatory policy of internet providers and consumer decisions. Thesis Supervisor: Steven Bauer Title: Research Scientist 3 4 Acknowledgments I am grateful to the Internet Policy Research Initiative for providing support and context for my technical research within a larger ecosystem of technology policy and advancements. -
Bufferbloat: Advertently Defeated a Critical TCP Con- Gestion-Detection Mechanism, with the Result Being Worsened Congestion and Increased Latency
practice Doi:10.1145/2076450.2076464 protocol the presence of congestion Article development led by queue.acm.org and thus the need for compensating adjustments. Because memory now is significant- A discussion with Vint Cerf, Van Jacobson, ly cheaper than it used to be, buffering Nick Weaver, and Jim Gettys. has been overdone in all manner of net- work devices, without consideration for the consequences. Manufacturers have reflexively acted to prevent any and all packet loss and, by doing so, have in- BufferBloat: advertently defeated a critical TCP con- gestion-detection mechanism, with the result being worsened congestion and increased latency. Now that the problem has been di- What’s Wrong agnosed, people are working feverishly to fix it. This case study considers the extent of the bufferbloat problem and its potential implications. Working to with the steer the discussion is Vint Cerf, popu- larly known as one of the “fathers of the Internet.” As the co-designer of the TCP/IP protocols, Cerf did indeed play internet? a key role in developing the Internet and related packet data and security technologies while at Stanford Univer- sity from 1972−1976 and with the U.S. Department of Defense’s Advanced Research Projects Agency (DARPA) from 1976−1982. He currently serves as Google’s chief Internet evangelist. internet DeLays nOw are as common as they are Van Jacobson, presently a research maddening. But that means they end up affecting fellow at PARC where he leads the networking research program, is also system engineers just like all the rest of us. And when central to this discussion. -
TCP Optimization Improve Qoe by Managing TCP-Caused Latency
SOLUTION BRIEF TCP Optimization Improve QoE by managing TCP-caused latency TCP OPTIMIZATION MARKET OVERVIEW The Transmission Control Protocol (TCP) is the engine of the internet and its dominant DELIVERS: role in traffic delivery has only grown as customers demand support for an ever- increasing array of personal, social, and business applications and services. However, Unique Approach TCP is not without its faults, and its well-known weaknesses have created a significant Creates a TCP “midpoint” that takes control of drag on network performance and customer quality of experience (QoE). the TCP connection while remaining end-to-end transparent Given that TCP traffic represents ~90% on fixed and 90%+ on mobile networks, many operators that have overlooked TCP’s shortcomings in the past are now considering new ways Buffer Mangement to manage TCP traffic to increase its performance, service quality, and network utilization. Manages “starving” and “bufferbloats” efficiently by adjusting the sending rate to The very characteristics of TCP that made it very popular and successful led to its performance correspond to the level of buffer data in the challenges in modern day networks. TCP is largely focused on providing fail-safe traffic delivery, access network but this reliability comes at a cost: lower performance, subpar customer experience, and Better Congestion Control underutilized network assets. Operators can delay other congestion management investments TCP is hobbled by its lack of end-to-end network visibility. Without the ability -
Real-Time Latency: Rethinking Remote Networks
Real-Time Latency: Rethinking Remote Networks You can buy your way out of “bandwidth problems. But latency is divine ” || Proprietary & Confidential 2 Executive summary ▲ Latency is the time delay over a communications link, and is primarily determined by the distance data must travel between a user and the server ▲ Low earth orbits (LEO) are 35 times closer to Earth than traditional geostationary orbit (GEO) used for satellite communications. Due to the closeness and shorter data paths, LEO-based networks have latency similar to terrestrial networks1 ▲ LEO’s low latency enables fiber quality connectivity, benefiting users and service providers by - Loading webpages as fast as Fiber and ~8 times faster than a traditional satellite system - Simplifying networks by removing need for performance accelerators - Improving management of secure and encrypted traffic - Allowing real-time applications from remote areas (e.g., VoIP, telemedicine, remote-control machines) ▲ Telesat Lightspeed not only offers low latency but also provides - High throughput and flexible capacity - Transformational economics - Highly resilient and secure global network - Plug and play, standard-based Ethernet service 30 – 50 milliseconds Round Trip Time (RTT) | Proprietary & Confidential 3 Questions answered ▲ What is Latency? ▲ How does it vary for different technologies? How does lower latency improve user experience? What business outcomes can lower latency enable? Telesat Lightspeed - what is the overall value proposition? | Proprietary & Confidential 4 What is -
The Bufferbloat Problem Over Intermittent Multi-Gbps Mmwave Links
The Bufferbloat Problem over Intermittent Multi-Gbps mmWave Links Menglei Zhang, Marco Mezzavilla, Jing Zhuy, Sundeep Rangan, Shivendra Panwar NYU WIRELESS, Brooklyn, NY, USA y Intel, Santa Clara, USA emails: fmenglei, mezzavilla, srangan, [email protected], [email protected] Abstract—Due to massive available spectrum in the millimeter transport layer mechanisms and buffering must rapidly adapt wave (mmWave) bands, cellular systems in these frequencies may to the link capacities that can dramatically change. This work provides orders of magnitude greater capacity than networks addresses one particularly important problem – bufferbloat. in conventional lower frequency bands. However, due to high susceptibility to blocking, mmWave links can be extremely inter- Bufferbloat: Bufferbloat is triggered by persistently filled mittent in quality. This combination of high peak throughputs or full buffers, and usually results in long latency and packet and intermittency can cause significant challenges in end-to-end drops. This phenomenon was first pointed out in late 2010 transport-layer mechanisms such as TCP. This paper studies [16]. Optimal buffer sizes should equal the bandwidth de- the particularly challenging problem of bufferbloat. Specifically, lay product (BDP), however, as the delay is usually hard with current buffering and congestion control mechanisms, high throughput-high variable links can lead to excessive buffers to estimate, larger buffers are deployed to prevent losses. incurring long latency. In this paper, we capture the performance Even though these oversized buffer prevent packet loss, the trends obtained while adopting two potential solutions that overall performance degrades, especially when transmitting have been proposed in the literature: Active queue manage- TCP flows,1 which is the main focus of this paper.