Algorithmic Aspects of Cloud Computing

✍ Scribed by Timos Sellis and Konstantinos Oikonomou

Publisher: Springer
Year: 2017
Tongue: English
Leaves: 190
Series: Lecture Notes in Computer Science 10230
Category: Library

No coin nor oath required. For personal study only.

✦ Synopsis

This book constitutes the thoroughly refereed post-conference proceedings of the Second International Workshop on Algorithmic Aspects of Cloud Computing, ALGOCLOUD 2016, held in Aarhus, Denmark, in August 2016.

The 11 revised full papers presented together with one tutorial paper were carefully reviewed and selected from 30 initial submissions. They deal with the following topics: algorithmic aspects of elasticity and scalability for distributed, large-scale data stores (e.g. NoSQL and columnar databases) search and retrieval algorithms for cloud infrastructures monitoring and analysis of elasticity for virtualized environments NoSQL, schemaless data modeling, integration caching and load-balancing storage structures and indexing for cloud databases new algorithmic aspects of parallel and distributed computing for cloud applications scalable machine learning, analytics and data science high availability, reliability, failover transactional models and algorithms for cloud databases query languages and processing programming models consistency, replication and partitioning CAP, data structures and algorithms for eventually consistent stores.

✦ Table of Contents

Front Matter....Pages I-XII
Front Matter....Pages 1-1
NSM-Tree: Efficient Indexing on Top of NoSQL Databases....Pages 3-14
An Apache Spark Implementation for Sentiment Analysis on Twitter Data....Pages 15-25
(A)kNN Query Processing on the Cloud: A Survey....Pages 26-40
A Cloud-Based Time-Dependent Routing Service....Pages 41-64
A Big Data Architecture for Traffic Forecasting Using Multi-Source Information....Pages 65-83
Front Matter....Pages 85-85
Mining Uncertain Graphs: An Overview....Pages 87-116
Recovering from Cloud Application Deployment Failures Through Re-execution....Pages 117-130
Fair, Fast and Frugal Large-Scale Matchmaking for VM Placement....Pages 131-145
Survey of Machine Learning Algorithms on Spark Over DHT-based Structures....Pages 146-156
Scaling Out to Become Doctrinal....Pages 157-168
A Survey on Big Data and Collective Intelligence....Pages 169-181
Back Matter....Pages 183-183

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