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George House 1 Guildhall Street Cambridge CB2 3NH United Kingdom antrmicrosoftcom Peter Druschel Rice University 6100 Main Street MS 132 Houston TX 770051892 USA druschelcsriceedu ABSTRACT This paper presents and evaluates the storage management and. riceedu Antony Rowstron Microsoft Research Cambridge CB2 3NH UK antrmicrosoftcom Abstract This paper sketches the design of PAST a largescale Internetbased global sto rage utility that provides scala bility high availability persistence and security George House 1 Guildhall Street Cambridge CB2 3NH UK antrmicrosoftcom Rice University MS132 6100 Main Street Houston TX 770051892 USA druschelcsriceedu Abstract This paper presents the design and evaluation of Pastry a scalable distributed object lo brPage 1br Echoi Storag i Infan Perceptio Nelso Cowan Kare Suomi an Phili A Mors Uraversity of WtsconstnModtson COWAN NELSON SUOMI KAREN an MORSE PHILI A Echoic Storag m Infara Perception CHIL D in Kentico CMS. Boris . Pocatko. Solution Architect. Kentico Software. borisp@kentico.com. Agenda. Problem. Describing different caching mechanisms. Demo for cache dependencies. API caching and additional info. EVALUATING & DEVELOPING, . STICKING WITH DIFFICULTY, . NOT SCARED OF MAKING MISTAKES. PERSISTENT. EVALUATING & DEVELOPING. STICKING WITH DIFFICULTY. NOT SCARED OF MAKING MISTAKES. A QUICK WARM UP EXERCISE. MTL TPTL MITL MTLF TPTLF MTL+Past MITL+Past interval-basedsemantics MTL TPTL MITL MTLF TPTLF MTL+Past MITL+Past pointwisesemantics Figure1:Summaryofourexpressivenessresults(dashededgesindicatefolkresu Victor Zakhary, . Divyakant. Agrawal, Amr El . Abbadi. 1. The old problem of Caching. Disk. RAM. L. 2. L. 1. Larger. Slower. Cheaper. Smaller. Faster. Expensive. 2. The old problem of Caching. Smaller. CS-3013 . Operating Systems. Hugh C. Lauer. (Slides include materials from. Slides include materials from . Modern Operating Systems. , . 3. rd. ed. ., by Andrew . Tanenbaum. and from . Operating System Concepts. A Framework for Evaluating Caching Policies in a Hierarchical Network of Caches Eman Ramadan, Pariya Babaie , Zhi -Li Zhang Presented By: Arvind Narayanan University of Minnesota, USA Caching at the Web Scale Victor Zakhary, Divyakant Agrawal, Amr El Abbadi Full slide deck: https://goo.gl/1VYGW3 1 The old problem of Caching Disk RAM L 2 L 1 Larger Slower Cheaper Smaller Faster Caching 50.5* COS 518: Advanced Computer Systems Lecture 9 Michael Freedman * Half of 101 Tradeoff Fast: Costly, small, close Slow: Cheap, large, far Based on two assumptions Temporal location: Will be accessed again soon Ron Jacobs. Sr. Technical Evangelist, Microsoft. http://blogs.msdn.com/rjacobs. Agenda. . Simple. Do the simplest thing that will possibly work. . Scalability. Able . to support the required quality of service as the system load . 2Figure 1Persistent changes to TN90p hot nights and TX90p hot days have already occurred over large parts of the Earth and climate models underestimate these persistent changes Top panels show time of &. Caching. Noah Mendelsohn. Tufts University. Email: . noah@cs.tufts.edu. Web: http://www.cs.tufts.edu/~noah. COMP 150-IDS: Internet Scale Distributed Systems . (Spring 2015). 2. Goals. Explore some general principles of performance,...