@proceedings {161,
	title = {Costs of a Federated and Hybrid Cloud Environment Aimed at MapReduce Video Transcoding},
	journal = {2015 IEEE Symposium on Computers and Communication (ISCC), Larnaca Cyprus},
	year = {2015},
	month = {2015},
	pages = {258-263},
	publisher = {IEEE Computer Society},
	address = {Larnaca, Cyprus},
	abstract = {<pre>
In this paper we investigate the applicability of the federation among several Cloud platform, demonstrating that a federated environment provides evident benefits despite the costs for the <u>setup</u> and <u>maintainance</u> of the federation itself. Also, we propose a new solution able to manage resource allocation in federated Clouds where resource requests occur in a dynamic way. We adopt such a solution to <u>setup</u> distributed <u>Hadoop</u> nodes of virtual clusters for the parallel <u>MapReduce</u> processing of large data sets. To increase their capabilities, Cloud Providers establish a federation relationship, making the <u>Hadoop</u>-based Cloud platforms much more performing than in the isolate case, adding a further level of <u>parallelization</u> in service provisioning. The results <u>analyzed</u> in the <u>referece</u> use case, that is a video transcoding using the <u>MapReduce</u> paradigm in a federated fashion, show how the federation costs in terms of delays and overhead are low in comparison with the service provisioning costs, and also highlight how federation makes the offered Cloud service more streamlined and fast. </pre>
},
	keywords = {Apache Hadoop, Big Data, CLEVER, cloud computing, HDFS, Horizontal Federation, IEEE P2302, MapReduce},
	doi = {10.1109/ISCC.2015.7405525},
	url = {http://ieeexplore.ieee.org/xpl/login.jsp?tp=\&arnumber=7405525\&url=http\%3A\%2F\%2Fieeexplore.ieee.org\%2Fxpls\%2Fabs_all.jsp\%3Farnumber\%3D7405525},
	author = {Alfonso Panarello and Maria Fazio and Antonio Celesti and Massimo Villari and Antonio Puliafito}
}
@proceedings {221,
	title = {A Federated MapReduce-based Video Transcoding System to Face the Future Massive Video-Selfie Sharing Trend},
	journal = {Fourth European Conference on Service-Oriented and Cloud Computing (ESOCC 2015) -  3rd International Workshop on Cloud for IoT},
	year = {2015},
	publisher = {Springer International Publishing},
	edition = {Communications in Computer and Information Science (CCSI)},
	abstract = {<pre>
The massive use of mobile devices and social networks is causing the birth of a new compulsive users{\textquoteright} behaviour. The activity photo <u>selfie</u> sharing is gradually turning into video <u>selfie</u>. These videos will be transcoded into multiple formats to support different visualization mode. We think there will be the need to have systems that can support, in a fast, efficient and scalable way, the millions of requests for video sharing and viewing. We think that a single Cloud Computing services provider cannot alone cope with this huge amount of incoming data (Big Data), so in this paper we propose a Cloud Federation-based system that exploiting the <u>Hadoop</u> <u>MapReduce</u> paradigm performs the video transcoding in multiple format and its distribution in a fastest and most efficient possible way. Experimental results highlight the major factors involved for job deployment in a federated Cloud environment and the efficiency of the proposed system.</pre>
},
	keywords = {Adaptive Streaming, Apache Hadoop, Big Data, CLEVER, cloud computing, HDFS, Horizontal Federation, IEEE P2302, MapReduce},
	author = {Alfonso Panarello and Antonio Celesti and Maria Fazio and Massimo Villari and Antonio Puliafito}
}
@proceedings {7092964,
	title = {How to Enhance Cloud Architectures to Enable Cross-Federation: Towards Interoperable Storage Providers},
	journal = { IEEE International Conference on Cloud Engineering (IC2E), Tempe, AZ, USA},
	year = {2015},
	month = {March},
	pages = {480-486},
	publisher = {IEEE Computer Society},
	address = {Washington D.C.},
	keywords = {Big Data, Big Data storage, CLEVER, CLEVER message oriented middleware, cloud architectures, cloud computing, cloud storage market, cross-federation, Ecosystems, federated cloud ecosystem, federation, Hadoop, Hadoop distribute file system, HDFS, inter-domain communication management, interoperable storage providers, Message systems, middleware, MOM, Protocols, public domain software, Resource management, Servers, small-medium cloud storage providers, Storage, storage management, XML, XMPP},
	doi = {10.1109/IC2E.2015.80},
	url = {http://conferences.computer.org/IC2E/2015/index.htm},
	author = {Maria Fazio and Antonio Celesti and Massimo Villari and Antonio Puliafito}
}
