M2 R: Enabling Stronger Privacy in MapReduce Computation Tien Tuan Anh Dinh, Prateek Saxena, Ee-Chien Chang, Beng Chin Ooi, Chunwang Zhang School of Computing, National University of Singapore , prateeks

Source URL: www.comp.nus.edu.sg

Microsoft Word - HotPower_camera_ready_ACM_format

Source URL: seelab.ucsd.edu

• Computing
• Concurrent computing
• Energy economics
• Software
• Parallel computing
• Energy policy
• Distributed computing architecture
• MapReduce
• Apache Hadoop
• Scheduling
• Sustainable energy
• Energy industry

Facebook’s Data Center Network Architecture Nathan Farrington and Alexey Andreyev Facebook, Inc., 1601 Willow Road, Menlo Park, CA 94025, USA Author e-mail address: Abstract: We review Facebook’s c

Source URL: nathanfarrington.com

• Computing
• Concurrent computing
• Data
• Ethernet
• Apache Hadoop
• Apache Software Foundation
• Cloud infrastructure
• Network switch
• MapReduce
• Data center network architectures
• Big data

Longitudinal Analytics of Web Archive data European Commission Seventh Framework Programme Call: FP7-ICT, Activity: ICTContract No: 258105

Source URL: www.lawa-project.eu

• Computing
• Cloud infrastructure
• Apache Hadoop
• Amazon Elastic Compute Cloud
• MapReduce
• Computer cluster
• MapR

HiMach A Parallel Framework for Analyzing Molecular Dynamics Trajectories HiMach Version 1.0/Document Version 0.1 June 2009

Source URL: www.deshawresearch.com

• Concurrent computing
• Computing
• Parallel computing
• MapReduce
• Data-intensive computing
• Apache Hadoop
• Molecular dynamics
• Map
• Automatic parallelization
• Parallelization contract
• Aster Data Systems

Hyracks: A Flexible and Extensible Foundation for Data-Intensive Computing Vinayak Borkar, Michael Carey, Raman Grover, Nicola Onose, Rares Vernica Computer Science Department, University of California, Irvine Irvine, CA

Source URL: asterixdb.ics.uci.edu

• Computing
• Concurrent computing
• Software
• Hadoop
• Parallel computing
• Apache Software Foundation
• Distributed computing architecture
• Query languages
• Apache Hadoop
• Data-intensive computing
• MapReduce
• Pig

Cluster Fault-Tolerance: An Experimental Evaluation of Checkpointing and MapReduce through Simulation Thomas C. Bressoud #1 , Michael A. Kozuch ∗2 #

Source URL: personal.denison.edu

• Computing
• Engineering
• Parallel computing
• Fault-tolerant computer systems
• Software quality
• Application checkpointing
• Classes of computers
• MapReduce
• Computer cluster
• Reliability engineering
• Fault tolerance
• Distributed computing

Dedoop: Efficient Deduplication with Hadoop Lars Kolb Andreas Thor Erhard Rahm

Source URL: dbs.uni-leipzig.de

• Computing
• Concurrent computing
• Parallel computing
• Workflow technology
• Distributed computing architecture
• Apache Software Foundation
• Cloud infrastructure
• MapReduce
• Apache Hadoop
• Record linkage
• Workflow
• Data cleansing

Prajna: Cloud Service and Interactive Big Data Analytics (Distributed Platform Building Leverage Functional Programming) Jin Li, Sanjeev Mehrotra and Weirong Zhu Microsoft One Microsoft Way, Bld. 99, Redmond, WA, USA {ji

Source URL: msrccs.github.io

• Computing
• Software engineering
• Computer programming
• Higher-order functions
• Programming language comparisons
• Parallel computing
• Apache Software Foundation
• Fold
• Recursion
• Apache Spark
• MapReduce
• Map

Parallel and Distributed Approach for Processing Large-Scale XML Datasets Zacharia Fadika 1 , Michael R. Head 2 , Madhusudhan Govindaraju 3 Computer Science Department, Binghamton University P.O. Box 6000, Binghamton, NY

Source URL: www.cs.binghamton.edu

• Computing
• Concurrent computing
• Parallel computing
• Data-intensive computing
• MapReduce
• Speedup
• Apache Hadoop
• VTD-XML
• Computer cluster
• Scalability
• Concurrent data structure
• Multi-core processor