Real-Time Latency: Rethinking Remote Networks
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A Comparison of Mechanisms for Improving TCP Performance Over Wireless Links
A Comparison of Mechanisms for Improving TCP Performance over Wireless Links Hari Balakrishnan, Venkata N. Padmanabhan, Srinivasan Seshan and Randy H. Katz1 {hari,padmanab,ss,randy}@cs.berkeley.edu Computer Science Division, Department of EECS, University of California at Berkeley Abstract the estimated round-trip delay and the mean linear deviation from it. The sender identifies the loss of a packet either by Reliable transport protocols such as TCP are tuned to per- the arrival of several duplicate cumulative acknowledg- form well in traditional networks where packet losses occur ments or the absence of an acknowledgment for the packet mostly because of congestion. However, networks with within a timeout interval equal to the sum of the smoothed wireless and other lossy links also suffer from significant round-trip delay and four times its mean deviation. TCP losses due to bit errors and handoffs. TCP responds to all reacts to packet losses by dropping its transmission (conges- losses by invoking congestion control and avoidance algo- tion) window size before retransmitting packets, initiating rithms, resulting in degraded end-to-end performance in congestion control or avoidance mechanisms (e.g., slow wireless and lossy systems. In this paper, we compare sev- start [13]) and backing off its retransmission timer (Karn’s eral schemes designed to improve the performance of TCP Algorithm [16]). These measures result in a reduction in the in such networks. We classify these schemes into three load on the intermediate links, thereby controlling the con- broad categories: end-to-end protocols, where loss recovery gestion in the network. is performed by the sender; link-layer protocols, that pro- vide local reliability; and split-connection protocols, that Unfortunately, when packets are lost in networks for rea- break the end-to-end connection into two parts at the base sons other than congestion, these measures result in an station. -
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. -
Cisco 200 Series Smart Switches Administration Guide 1.4.0.X
ADMINISTRATION GUIDE Cisco Small Business 200 Series Smart Switch Administration Guide Table of Contents 1 Table of Contents Chapter 1: Table of Contents 1 Chapter 2: Getting Started 8 Starting the Web-based Configuration Utility 8 Quick Start Device Configuration 12 Interface Naming Conventions 12 Window Navigation 14 Chapter 3: Status and Statistics 18 System Summary 18 Ethernet Interfaces 18 Etherlike Statistics 19 802.1X EAP Statistics 20 Health 21 RMON 22 View Log 29 Chapter 4: Administration: System Log 30 Setting System Log Settings 30 Setting Remote Logging Settings 32 Viewing Memory Logs 33 Chapter 5: Administration: File Management 35 System Files 35 Upgrade/Backup Firmware/Language 38 Download/Backup Configuration/Log 41 Cisco Small Business 200 Series Smart Switch Administration Guide 1 Table of Contents 1 Configuration Files Properties 46 Copy/Save Configuration 46 Auto Configuration/Image Update via DHCP 48 56 Chapter 6: Administration 57 Device Models 57 System Settings 59 Management Interface 61 User Accounts 61 Defining Idle Session Timeout 61 Time Settings 62 System Log 62 File Management 62 Rebooting the Device 62 Health 64 Diagnostics 65 Discovery - Bonjour 65 Discovery - LLDP 66 Discovery - CDP 66 Ping 66 Chapter 7: Administration: Time Settings 68 System Time Options 68 SNTP Modes 70 Configuring System Time 70 Chapter 8: Administration: Diagnostics 77 Copper Ports Tests 77 Displaying Optical Module Status 79 Cisco Small Business 200 Series Smart Switch Administration Guide 2 Table of Contents 1 Configuring Port and -
Latency and Throughput Optimization in Modern Networks: a Comprehensive Survey Amir Mirzaeinnia, Mehdi Mirzaeinia, and Abdelmounaam Rezgui
READY TO SUBMIT TO IEEE COMMUNICATIONS SURVEYS & TUTORIALS JOURNAL 1 Latency and Throughput Optimization in Modern Networks: A Comprehensive Survey Amir Mirzaeinnia, Mehdi Mirzaeinia, and Abdelmounaam Rezgui Abstract—Modern applications are highly sensitive to com- On one hand every user likes to send and receive their munication delays and throughput. This paper surveys major data as quickly as possible. On the other hand the network attempts on reducing latency and increasing the throughput. infrastructure that connects users has limited capacities and These methods are surveyed on different networks and surrond- ings such as wired networks, wireless networks, application layer these are usually shared among users. There are some tech- transport control, Remote Direct Memory Access, and machine nologies that dedicate their resources to some users but they learning based transport control, are not very much commonly used. The reason is that although Index Terms—Rate and Congestion Control , Internet, Data dedicated resources are more secure they are more expensive Center, 5G, Cellular Networks, Remote Direct Memory Access, to implement. Sharing a physical channel among multiple Named Data Network, Machine Learning transmitters needs a technique to control their rate in proper time. The very first congestion network collapse was observed and reported by Van Jacobson in 1986. This caused about a I. INTRODUCTION thousand time rate reduction from 32kbps to 40bps [3] which Recent applications such as Virtual Reality (VR), au- is about a thousand times rate reduction. Since then very tonomous cars or aerial vehicles, and telehealth need high different variations of the Transport Control Protocol (TCP) throughput and low latency communication. -
Measuring Latency Variation in the Internet
Measuring Latency Variation in the Internet Toke Høiland-Jørgensen Bengt Ahlgren Per Hurtig Dept of Computer Science SICS Dept of Computer Science Karlstad University, Sweden Box 1263, 164 29 Kista Karlstad University, Sweden toke.hoiland- Sweden [email protected] [email protected] [email protected] Anna Brunstrom Dept of Computer Science Karlstad University, Sweden [email protected] ABSTRACT 1. INTRODUCTION We analyse two complementary datasets to quantify the la- As applications turn ever more interactive, network la- tency variation experienced by internet end-users: (i) a large- tency plays an increasingly important role for their perfor- scale active measurement dataset (from the Measurement mance. The end-goal is to get as close as possible to the Lab Network Diagnostic Tool) which shed light on long- physical limitations of the speed of light [25]. However, to- term trends and regional differences; and (ii) passive mea- day the latency of internet connections is often larger than it surement data from an access aggregation link which is used needs to be. In this work we set out to quantify how much. to analyse the edge links closest to the user. Having this information available is important to guide work The analysis shows that variation in latency is both com- that sets out to improve the latency behaviour of the inter- mon and of significant magnitude, with two thirds of sam- net; and for authors of latency-sensitive applications (such ples exceeding 100 ms of variation. The variation is seen as Voice over IP, or even many web applications) that seek within single connections as well as between connections to to predict the performance they can expect from the network. -
The Effects of Latency on Player Performance and Experience in A
The Effects of Latency on Player Performance and Experience in a Cloud Gaming System Robert Dabrowski, Christian Manuel, Robert Smieja May 7, 2014 An Interactive Qualifying Project Report: submitted to the Faculty of the WORCESTER POLYTECHNIC INSTITUTE in partial fulfillment of the requirements for the Degree of Bachelor of Science Approved by: Professor Mark Claypool, Advisor Professor David Finkel, Advisor This report represents the work of three WPI undergraduate students submitted to the faculty as evidence of completion of a degree requirement. WPI routinely publishes these reports on its web site without editorial or peer review. Abstract Due to the increasing popularity of thin client systems for gaming, it is important to un- derstand the effects of different network conditions on users. This paper describes our experiments to determine the effects of latency on player performance and quality of expe- rience (QoE). For our experiments, we collected player scores and subjective ratings from users as they played short game sessions with different amounts of additional latency. We found that QoE ratings and player scores decrease linearly as latency is added. For ev- ery 100 ms of added latency, players reduced their QoE ratings by 14% on average. This information may provide insight to game designers and network engineers on how latency affects the users, allowing them to optimize their systems while understanding the effects on their clients. This experiment design should also prove useful to thin client researchers looking to conduct user studies while controlling not only latency, but also other network conditions like packet loss. Contents 1 Introduction 1 2 Background Research 4 2.1 Thin Client Technology . -
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. -
Evaluating the Latency Impact of Ipv6 on a High Frequency Trading System
Evaluating the Latency Impact of IPv6 on a High Frequency Trading System Nereus Lobo, Vaibhav Malik, Chris Donnally, Seth Jahne, Harshil Jhaveri [email protected] , [email protected] , [email protected] , [email protected] , [email protected] A capstone paper submitted as partial fulfillment of the requirements for the degree of Masters in Interdisciplinary Telecommunications at the University of Colorado, Boulder, 4 May 2012. Project directed by Dr. Pieter Poll and Professor Andrew Crain. 1 Introduction Employing latency-dependent strategies, financial trading firms rely on trade execution speed to obtain a price advantage on an asset in order to earn a profit of a fraction of a cent per asset share [1]. Through successful execution of these strategies, trading firms are able to realize profits on the order of billions of dollars per year [2]. The key to success for these trading strategies are ultra-low latency processing and networking systems, henceforth called High Frequency Trading (HFT) systems, which enable trading firms to execute orders with the necessary speed to realize a profit [1]. However, competition from other trading firms magnifies the need to achieve the lowest latency possible. A 1 µs latency disadvantage can result in unrealized profits on the order of $1 million per day [3]. For this reason, trading firms spend billions of dollars on their data center infrastructure to ensure the lowest propagation delay possible [4]. Further, trading firms have expanded their focus on latency optimization to other aspects of their trading infrastructure including application performance, inter-application messaging performance, and network infrastructure modernization [5]. -
Esports: a Network Focus
Esports: A Network Focus ©2019 Extreme Networks, Inc. All rights reserved Esports: A Network Focus ESPORTS Latency/ Visibility Security ClouD/ISP Tools/Network- Performance #1 Management 2 ©2019 Extreme Networks, Inc. All rights reserved Esports: A Network Focus Latency/Jitter “Anything over 1 or 2 Mbps download speed is going to be sufficient for most online gaming. - What matters for online gamers is low latency. Latency (defined as the average time it takes a network packet to travel from you, to a server, and back) is that lag you can sometimes see online, be it in a web page download stuttering or game struggling to keep up.” IND (Interpolation Delay) is in some games Stat’s Display. IND is the small buffer of time between when your client gets information from the server, and when it's shown to you in the game. This is normally around 50-60ms for normal games. RTT (RounD Trip Time) https://www.imperva.com/learn/performance/round-trip-time-rtt/ Round-trip time (RTT) is the duration, measured in milliseconds, from when a browser sends a request to when it receives a response from a server. It’s a key performance metric for web applications and one of the main factors, along with Time to First Byte (TTFB), when measuring page load time and network latency Protocols Online gaming uses TCP for non-critical traffic such as chat, game lobbies, etc. The Game traffic uses UDP. 3 ©2019 Extreme Networks, Inc. All rights reserved Esports: A Network Focus Visibility If you can’t see it, you can’t manage it.