PPT-the shared log approach to cloud-scale consistency

Mahesh Balakrishnan Microsoft Research VMware Research Collaborators Dahlia Malkhi Ted Wobber Vijayan Prabhakaran Phil Bernstein Ming Wu Michael Wei Dan Glick John D Davis Aviad. Spring 2009. L. -10 Consistency. 1. Important Lessons. Lamport. & vector clocks both give a logical timestamps. Total ordering vs. causal ordering. Other issues in coordinating node activities. Exclusive access to . Doug Terry. Microsoft Research Silicon Valley. … Explained through Baseball. Data Replication in the Cloud. Question. : What consistency choices should cloud storage systems offer applications?. Some Popular Systems. Distributed Shared Memory. Shared Memory. Shared memory programs are easier to write. Multiprocessor systems. Message passing systems:. - no physically shared memory. - need to provide an abstraction of shared memory: Distributed Shared Memory. Pay only when it matters. Tim . Kraska. , Martin . Hentschel. , Gustavo Alonso, Donald . Kossmann. 27.09.2009 Systems. Modified by . Raja . Amadala. - 08305078. Sandeep. N - 08305063. 1. 2. You own a Kiosk. Doug Terry. Microsoft Research Silicon Valley. … Explained through Baseball. Data Replication in the Cloud. Question. : What consistency choices should cloud storage systems offer applications?. Some Popular Systems. Abstract. Cloud computing economically enables customers with limited computational resources to outsource large-scale computations to the cloud. . However, how to protect customers’ confidential data involved in the computations then becomes a major security concern. In this paper, we present a secure outsourcing mechanism for solving large-scale systems of linear equations (LE) in cloud.. Ramoliya. . . dipak.ramoliya@darshan.ac.in. Computer Engineering Darshan . Institute of Engineering & . Technology. Unit: 6 . Distributed . Shared Memory. Director, Security & Virtualization. Network Utility Force. About Your Presenter. Walker and Associates. has been around for more than 40 years, handling the needs of communications carriers and the Federal Government as a Value Added Distributor (Warehousing, Networking, Design Services, Reselling). KC . Sivaramakrishnan. . . Lukasz . Ziarek. . Suresh . Jagannathan. Purdue University SUNY Buffalo Purdue University. Big Picture. 2. No cache coherence. Message passing buffers. Ken Birman, CS5412 Cloud Computing. CS5412 Spring 2014. 1. Styles of cloud computing. Think about Facebook…. We normally see it in terms of pages that are image-heavy. But the tags and comments and likes create “relationships” between objects within the system. Regions in Videos. Yihang. Bo. Hao. Jiang. Institute of Automation, CAS. Boston College. Boston College. Challenges. Previous Rectangular Part Methods. Templates with . Different scales . Templates with . Boston Azure User Group. 27-October-2011. Copyright . (c) . 2011, Bill Wilder – Use allowed under Creative . Commons license . http. ://creativecommons.org/licenses/by-nc-sa/3.0. /. Boston . Azure User Group. Resource Management II. Eva . Kalyvianaki. ek264@cam.ac.uk. Contents. Apollo: Scalable and Coordinated Scheduling . for Cloud-Scale Computing, . by Eric Boutin, . Jaliya. Ekanayake, Wei Lin, Bing Shi, and . Replication Benefits. Replication enhances tolerance to failure. Performance can be improved in different ways. Placing replicas in the proximity of the process using them. Replicating servers and subsequently dividing the work among them.