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Advances in cloud and big data computing
Author(s) -
Bellatreche Ladjel,
Leung Carson,
Xia Yinglong,
El Baz Didier
Publication year - 2018
Publication title -
concurrency and computation: practice and experience
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.309
H-Index - 67
eISSN - 1532-0634
pISSN - 1532-0626
DOI - 10.1002/cpe.5053
Subject(s) - cloud computing , big data , ibm , cognitive computing , data center , computer science , watson , library science , the internet , data science , world wide web , operating system , artificial intelligence , materials science , cognition , neuroscience , biology , nanotechnology
We welcome you to this special issue initially dedicated to the best papers presented at the The IEEE International Conference on Cloud and Big Data Computing (CBDCom 2016), which was held in Toulouse, France, 18-21 July, 2016. Similar to CBDCom 2015, CBDCom 2016 is once again an event in the 2016 IEEE Smart World Congress, in conjunction to five other events, ie, UIC 2016, ATC 2016, ScalCom 2016, IoP 2016, and SmartWorld 2016. CBDCom is a premier forum for researchers, practitioners, developers, and users who are interested in Cloud computing and Big Data and would like to explore new ideas, techniques, and tools, as well as to exchange experience. CBDCom 2016 has been organized into 11 tracks: Big Data Algorithms, Applications and Services (co-chaired by Boualem Benatallah, University of New South Wales, Australia, and by Yassine Ouhammou, ISAE-ENSMA, France), Big Data Mining and Analytics (co-chaired by Sanjay Madria, Missouri University of Science and Technology, USA, and Praveen Rao, University of Missouri-Kansas City, USA), Big Data Processing and Querying (chaired by Mayank Daga, AMD, USA), Cloud and Big Data for Internet of Things (IoT) (chaired by Jian Tang, Syracuse, USA), Government and Industrial Experiences for Cloud and Big Data (co-chaired by Toyotaro Suzumura, IBM Research, USA), Green Computing and Networking Technologies for Cloud and Big Data (co-chaired by Kalyana Chadalavada, Intel, USA, and Samee Khan, NDSU, USA), Software Engineering for Cloud Computing and Big Data (chaired by Annie T. T. Ying, IBM T.J. Watson Research Center, USA), Cloud Computing Solutions and Platforms (co-chaired by Manisha Gajbe, Intel, USA, and Carlos Garcia-Alvarado, Amazon, USA), Privacy and Security for Cloud and Big Data (co-chaired by Alfredo Cuzzocrea, CNR & University of Trieste, Italy, and Nuyun Zhang, Clemson University, USA), Big Data Visualization (chaired by Nan Cao, New York University Shanghai, China & New York University, USA) and Big Data Education (co-chaired by Dickson K.W. Chiu, The University of Hong Kong, China, and Wenhua Yu, Jiangsu Big Data Education Lab, China). CBDCom 2016 received 35 submissions from 28 countries or districts, covering 12 topics related to Cloud and Big Data, more particularly Big Data graph algorithms, virtualization, networking, Big data mining, privacy, parallel system technology (Spark, MapReduce, HDFS), emerging hardware trends in large-scale data processing, service composition in Cloud, and industrial experiences. All submissions were peer-reviewed by at least three reviewers from our international program committee consisting of professors and industrial researchers in relevant fields from 16 countries. Through many days of hard work and persistence, we were able to complete the review process for the papers appearing in this proceeding. Finally, we accepted 12 full papers, at the acceptance rate of 35%. To attract good papers, we manage our special issue for the journal Concurrency and Computation: Practice and Experience, Wiley, as follows. Out of the 12 full papers accepted in CDBCom 2016, five of them were invited to extend their paper by at least 50% new content. Also, an open call for papers has been organized and has attracted seven papers covering the different topics of CBDCom 2016. In total, our special issue got 12 papers. After a second round of reviews, we finally accepted six papers. Thus, the relative acceptance rate for the papers included in this special issue is competitive. We congratulate the authors who submitted articles to CBDCom 2016 and our special issue. The six selected papers are summarized as follows. The first paper titled, “Learning the way to the Cloud: Big Data Park,” by Marchiori1 proposes a multidisciplinary topic combining the learning by doing teaching/learning model with the map-reduce programming model. It comes up with an interesting idea, which can be put in practice and might represent a way to help children to get used with cloud computing. To do so, the paper shows the interest in making the new generations familiar with at least the basics of these new technologies. As in the field of technology, big data computing creates a total stir; those among the young generations must intervene a readjustment to the new trends, too. In order to reach its objective, the article puts on the first line the Big Data Park one-line educational tool, which represents an innovative idea for making kids be interested and warm-blooded of cloud computing. Also, the system comes up as a response against the classical way of teaching in schools, which limits the thinking flexibility of the kids. Instead of watching and struggling with learning problems from outside of the scenario, the system brings the user in the middle of the action, starting from a low level and trying to reach the top of the game. In addition to this aspect, challenges, impacts, and results on the young class of people have been reported after they passed through both the instructive/educational and funny/attractive techniques that the system offers. The second paper, titled “Fuzzy ACID Properties for Self-Adaptive Composite Cloud Services Execution,” by Cardinale et al2 discusses a self-adaptive model that aims at relaxing atomicity of composite service execution by introducing the notion of fuzzy atomicity. The fuzzy atomicity is built upon a set of transactional properties and is relaxed using either compensation or checkpointing. According to the user requirements, the (acceptable fuzzy atomicity), and the state of the composite service execution, the system provides an all-something-or-(almost)nothing model: users

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