PPT-Distributed Data Flow Language

for MultiParty Protocols Krzysztof Ostrowski Ken Birman Danny Dolev Cornell University Hebrew University krzysken cscornelledu dolevcshujiacil Introduction. Advait Dixit, . Fang . Hao. , . Sarit. . Mukherjee, . T.V. . . Lakshman. , . Ramana. . Kompella. Physical Network Infrastructure. SDN Control Plane. Distributed Control Plane. Single point of failure. Raghaven. et all. Presented by: Brian Card. CS 577 - Fall 2014 - . Kinicki. 1. Motivation. Distributed Rate Limiting. Global Token Bucket. Global Random Drop. Flow Proportional Share. Simulation and Results. : . A Fault-Tolerant Abstraction for In-Memory Cluster Computing. Matei. . Zaharia. , . Mosharaf. Chowdhury, . Tathagata. Das, . Ankur. Dave, Justin Ma, Murphy McCauley, Michael J. Franklin, Scott . Conference on Empirical Methods in Natural Language . Processing 2007. 報告者：郝柏翰. 2013/06/04. Thorsten . Brants. , Ashok . C. . Popat. , . Peng. . Xu. , Franz . J. . Och. , Jeffrey Dean. for . Big-Data Applications . Running on Data Center Networks. * . Mellanox . Technologies . LTD, . +. Technion - EE Department. Eitan Zahavi. *+. Isaac Keslassy. +. . Avinoam Kolodny. +. ANCS 2012. A Fault-Tolerant Abstraction for In-Memory Cluster Computing. Matei Zaharia, Mosharaf Chowdhury. , Tathagata Das, Ankur Dave, Justin Ma, Murphy McCauley, Michael J. Franklin, Scott Shenker, Ion Stoica. Fundamental issue: the speed gap between data plane and control plane.. Switch OS. Switch HW. 10-100 . Gbps. Switch OS. Switch HW. 10-100 0Mbps. Switch OS. Switch HW. ???. SDN controller. SDN controller scalability issue. draft-. finn. -. detnet. -problem-statement. Norm . Finn, . Pascal . Thubert. DetNet problem statement. Doc charter. This . effort will establish . the deployment . environment and deterministic network requirements. . : . A Fault-Tolerant Abstraction for In-Memory Cluster Computing. Matei. . Zaharia. , . Mosharaf. Chowdhury, . Tathagata. Das, . Ankur. Dave, Justin Ma, Murphy McCauley, Michael J. Franklin, Scott . © . 2013 . Pearson Education, Inc.  Publishing as Prentice Hall. 1. Modern Database Management. 11. th. Edition. Jeffrey A. Hoffer, V. Ramesh, . Heikki Topi. . Objectives. Define terms. Explain business conditions driving distributed databases. Derwent classification to the US classification, and, consequently, to the fulltext of patents online at the USPTO. There are many other practical examples of how distributed higher-order rules can be Design. Virani Amit. 1461356. 3.1 Top-Down Design . Process. 3.2 . Distribution Design . Issues. 3.2.1 Reasons for Fragmentation. . 3.2.2 Fragmentation Alternatives. Distributed Database . Design. The design of a distributed computer system involves making decisions on the placement of data  and programs  across the sites of a computer . 2015. Contents. Confidential. Optical fibres and packaging for the downhole environment. Optical fibre cable – downhole deployment options. Distributed sensing – how it works (summary). Silixa’s distributed sensing technology and specifications. Derek . Murray. October 2010. What we’ll cover. Techniques for handling “big. data”. Distributed storage. Distributed computation. Focus on recent papers describing real systems. Example: web search.