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Testbed in Network Coding 学生:李腾飞 导师:舒炎泰 Background • Bob and Alice Alice Relay Require 4 transmissions Bob Background • Bob and Alice Alice Relay Bob XOR XOR XOR Require 3 transmissions Outline • • • • • MIT Testbed (COPE,MORE,MIXIT) Toronto Aalborg-Denmark Harvard(Rainbow) What can we learn from? MIT-Testbed Outline • Objective & Function • Configuration • Work & Paper on Network Coding Objective & Function • Build a two-floors Indoor Testbed • First putting network coding into practice • Mainly for test Network Coding Routing/Mac/Phyical Layer Algorithm(wireless 802.11a/b/g,zigbee, etc ) on Laptop • Large number of Nodes support(about 30) Configuration Software: • System is Linux,and using Click Routing Module[1] toolkit send 802.11a/b/g tcp and udp datagram • Implement with Srcr,EXOR and other classic Routing or Mac Layer Algorithm Configuration(2) Hardware: • 802.11a/b/g wireless card with an omni-directional antenna (MIXIT use zigbee(802.15)) • Cards based on the NETGEAR 2.4&5GHz 802.11a/g chipset(or NETGEAR WAG311 802.11chipset) • RTS/CTS disabled • Power level : Adjustable • Mode: Adjustable Testbed Work & Paper on Network Coding • COPE[2](Sigcomm 06) • MORE[3](Sigcomm 07) • MIXIT[4](Sigcomm 08) COPE (Coding Opportunistically) • Consider multiple unicast flows – Generalize Alice-Bob scenario • Exploits Shared Nature of Wireless Medium – Store Overheard Packets for Short Time – These packets are used for decoding perspective packets • First implement Wireless Network Coding in the real world MIT-MORE • Spatial reuse and thus underutilize the wireless medium. • MAC-independent opportunistic routing protocol • The first intra flow (single flow) in Network Coding • It combines random network coding with opportunistic routing to address its current limitations. MIT-MIXIT • • • • Not apply an error detection code Use Physical Layer Hint to guess bit error/right Cross-layer Most Based on More Outline • • • • • MIT Testbed (COPE,MORE,MIXIT) Toronto Aalborg-Denmark Harvard(Rainbow) What can we learn from? Toronto Testbed Hardware • NVIDIA GTX 280 Graphics Process Unit, 240 computing cores. • NVIDIA GeForce 8800 GT GPU with 112 cores, which is supported by the CUDA platform. • 8-core Intel Xeon server Software • NVIDIA’s Tesla GPU architecture • C language using the Compute Unified Device Architecture (CUDA) programming model and development tools Work & Paper on Network Coding • Parallelized Progressive Network Coding With Hardware Acceleration[5](IWQOS07) • Nuclei: Graphics accelerated Many-core Network Coding[6](Infocom 09) • Pushing the Envelope:Extreme Network Coding on the GPU[7]( ICDCS 09) • UUSEE[8](Infocom 2010) Parallelized Progressive Network Coding • hardware acceleration • Take advantage of symmetric multiprocessor (SMP) systems • packaged as a C++ class library Platform comparison of coding performance at (n = 128, k = 4 KB). Nuclei: GPU-accelerated Many-core Network Coding • Hundreds of computing cores in GPU • Not affected by competing threads and background tasks • combined CPU-GPU encoding & decoding Pushing the Envelope: Extreme Network Coding on the GPU • Super GPU set CPU free • Table-based encoding technique • parallel decoding ofmultiple segments UUSEE Objectives • Minimized server bandwidth costs. • Minimized buffering delay after a random seek • Consistently satisfactory playback quality Outline • • • • • MIT Testbed (COPE,MORE,MIXIT) Toronto Aalborg-Denmark Harvard(Rainbow) What can we learn from? Aalborg University Outline • Objective & Function • Configuration • Work & Paper on Network Coding Objective & Function • • • • Mainly Build a Mobile PhoneTestbed Easy for movement Scene Mainly for wireless Network Research Work. Nearly 150 Papers in recent 10 years(most on this Testbed) • Recently years most of Testbed work is about Network Coding Configuration-Ex Hardware: • Nokia N810 Internet Tablet Large Screen ,for Visualization • WLAN Interface • Processor - TI OMAP 2420, 400 MHz ARM11. Configuration(2) Software: • Operating System - Maemo1 OS2008 (Linux kernel 2.6.21omap1) • Cross-compilation toolkit Scratchbox • SDK:Maemo SDK Not just N810 • Nokia N95-8GB, ARM 11 332 MHz CPU, 128 MB ram,Symbian OS 9.2. support IEEE802.11b/g Lots of work on it! • Laptop:Lenovo T61p, 2.53 GHz Intel Core2Duo, 2 GB ram,Kubuntu 8.10 64bit. Work & Paper on Network Coding • Cautious View on Network Coding - From Theory to Practice“ JCN 2008 • Evolutionary Theory for Cluster Head Election in Cooperative Clusters implementing Network Coding", Europe Wireless 2009 • Implementation and Performance Evaluation of Network Coding for Cooperative Mobile Devices“ ICC2008 • Implementation of Random Linear Network Coding on OpenGL-enabled Graphics Cards Europe Wireless 2009 • Network Coding Opportunities for Wireless Grids Formed by Mobile Devices ICST 2008 • Network Coding for Mobile Devices - Systematic Binary Random Rateless Codes ICC09 • … Outline • • • • • MIT Testbed (COPE,MORE,MIXIT) Toronto Aalborg-Denmark Harvard(Rainbow) What can we learn from? Harvard-Rainbow • MAC priority scheme • Priority computed by the information collect from neighbor,decide the rate of TX • Priority based on the rank of coefficient matrix of the Buffer of node • Network Coding scheme for the outgoing data at each node. Rainbow-Testbed • 29 OLPC Beta-2[9] nodes wireless testbed • Outdoor Experiment(wireless interference (802.11)is small compare with indoor) • Broadcast Ethernet packets at the 2Mbit/s rate for all protocol implementations • The size of the file we distributed was 6.1 MBytes, which at the 1.7 Mbit/s link rate of our testbed takes about 30 seconds to transfer.We limited the experiment run time to 300 seconds. Hardware • i386 compatible systems based on the AMD Geode GX processor running at 366MHz, and equipped with 128MB RAM. • Each node has one Marvell Libertas 88W8388 802.11b/g radio, with tunable transmit power. Harvard Implementation,We can learn ? Developed implementation: • Test Application:GUI has been implemented to show the distribution of packets • Framework:A Virtual Layer between MAC and IP Layer,just call basic Berkely Function,easy for implement • Logistics Platform:It contains all the data structures and functions for the logistics of network coding. • Schemes:This level is the algorithms for encoding and decoding. One scheme for reliable broadcast, and one for network coding. Outline • • • • • MIT Testbed (COPE,MORE,MIXIT) Toronto Aalborg-Denmark Harvard(Rainbow) What can we learn from? Testbed Objective Architectural objectives • • • • • • Research Requirements Fast control connectivity and easy management Flexible wireless components Extendability Financial cost …… Research Requirements • Be able to observe findings that have been published in the past.(reproductive) • Indoor and Outdoor Experiments • New Idea Fast control connectivity and easy management • Node with more number and kinds of interfaces • NFS Mounting Strategy – All Update link to the server – Remote turn off the node? – Central Control Flexible wireless components • hardware and software should support modifications • Wifi Cards Driver should be opensource(or Partly Open) • Click Modular Router software framework is a good idea. • Linux-based wireless applications are used The Driver-chipset Architecture Example • Three open-source Linux drivers available today. Click • Refer:http://read.cs.ucla.edu/click/ • MIT and many University using Click • modular software based router approach. The components of Click are packet processing modules called elements. Extendability • Multiply Interface for future Application • Big waterproof box,for future more Device • Through NFS ,Software could be easy for Update Financial cost • Complicate Problem References • [1] http://read.cs.ucla.edu/click/ • [2] Sachin Katti, Hariharan Rahul, Wenjun Hu, Dina Katabi, Muriel Medard, and Jon Crowcroft "XORs In The Air: Practical Wireless Network Coding," ACM SIGCOMM, 2006. • [3] Szymon Chachulski, Michael Jennings, Sachin Katti, and Dina Katabi, "Trading Structure for Randomness in Wireless Opportunistic Routing," ACM SIGCOMM, 2007. • [4] Sachin Katti, Dina Katabi, Hari Balakrishnan, and Muriel Medard, "Symbol-Level Network Coding for Wireless Mesh Networks," ACM SIGCOMM, 2008. • [5] H. Shojania and B. Li, “Parallelized Network Coding With Hardware Acceleration,” in Proc. of the 15th IEEE International Workshop on Quality of Service (IWQoS), 2007. • [6] H. Shojania, B. Li, and X. Wang, “Nuclei: Graphicsaccelerated Manycore Network Coding,” in Proc. of IEEE INFOCOM 2009, August 2009. References [7] Hassan Shojania, Baochun Li. "Pushing the Envelope: Extreme Network Coding on the GPU," to appear in the Proceedings of the 29th International Conference on Distributed Computing Systems (ICDCS 2009), Montreal Canada, June 22-26, 2009. [8] Zimu Liu, Chuan Wu, Baochun Li, Shuqiao Zhao. "UUSee: Large-Scale Operational On-Demand Streaming with Random Network Coding," to appear in the Proceedings of IEEE INFOCOM 2010, San Diego, California, March 15-19, 2010. [9] http://zh.wikipedia.org/wiki/OLPC