Algorithms and Architectures for Parallel Processing
ICA3PP 2016 Collocated Workshops: SCDT, TAPEMS, BigTrust, UCER, DLMCS, Granada, Spain, December 14-16, 2016, Proceedings
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Chapter and Conference Paper
Appraising SPARK on Large-Scale Social Media Analysis
Software systems for social media analysis provide algorithms and tools for extracting useful knowledge from user-generated social media data. ParSoDA (Parallel Social Data Analytics) is a Java library for dev...
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Article
Analyzing polarization of social media users and news sites during political campaigns
Social media analysis is a fast growing research area aimed at extracting useful information from social networks. Recent years have seen a great interest from academic and business world in using social media...
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Chapter
Implementing MapReduce Applications in Dynamic Cloud Environments
MapReduce is one of the most popular programming models for parallel data processing in Cloud environments. Standard MapReduce implementations are based on centralized master-slave architectures that do not co...
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Chapter
Big Data Analysis on Clouds
The huge amount of data generated, the speed at which it is produced, and its heterogeneity in terms of format, represent a challenge to the current storage, process and analysis capabilities. Those data volum...
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Article
Exploiting in-memory storage for improving workflow executions in cloud platforms
The Data Mining Cloud Framework (DMCF) is an environment for designing and executing data analysis workflows in cloud platforms. Currently, DMCF relies on the default storage of the public cloud provider for a...
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Book and Conference Proceedings
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Chapter and Conference Paper
Geocon: A Middleware for Location-Aware Ubiquitous Applications
A core functionality of any location-aware ubiquitous system is storing, indexing, and retrieving information about entities that are commonly involved in these scenarios, such as users, places, events and oth...
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Article
ServiceSs: An Interoperable Programming Framework for the Cloud
The rise of virtualized and distributed infrastructures has led to new challenges to accomplish the effective use of compute resources through the design and orchestration of distributed applications. As legac...
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Chapter and Conference Paper
Using Clouds for Scalable Knowledge Discovery Applications
Cloud platforms provide scalable processing and data storage and access services that can be exploited for implementing high-performance knowledge discovery systems and applications. This paper discusses the u...
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Chapter and Conference Paper
Enabling Cloud Interoperability with COMPSs
The advent of Cloud computing has given to researchers the ability to access resources that satisfy their growing needs, which could not be satisfied by traditional computing resources such as PCs and locally ...
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Chapter
A Peer-to-Peer Framework for Supporting MapReduce Applications in Dynamic Cloud Environments
MapReduce is a programming model widely used in Cloud computing environments for processing large data sets in a highly parallel way. MapReduce implementations are based on a master-slave model. The failure of...
