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 Gabriel Antoniu

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Average citations per article3.63
Citation Count290
Publication count80
Publication years1999-2017
Available for download23
Average downloads per article214.78
Downloads (cumulative)4,940
Downloads (12 Months)350
Downloads (6 Weeks)42
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80 results found Export Results: bibtexendnoteacmrefcsv

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1
May 2017 CCGrid '17: Proceedings of the 17th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing
Publisher: IEEE Press
Bibliometrics:
Citation Count: 1
Downloads (6 Weeks): 3,   Downloads (12 Months): 31,   Downloads (Overall): 43

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We are now witnessing an unprecedented growth of data that needs to be processed at always increasing rates in order to extract valuable insights. Big Data streaming analytics tools have been developed to cope with the online dimension of data processing: they enable real-time handling of live data sources by ...
Keywords: memory deduplication, streaming analytics, sliding-window aggregations, Apache Flink, Big Data

2
May 2017 CCGrid '17: Proceedings of the 17th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing
Publisher: IEEE Press
Bibliometrics:
Citation Count: 0
Downloads (6 Weeks): 2,   Downloads (12 Months): 11,   Downloads (Overall): 19

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In-memory storage systems emerged as a de-facto building block for today's large scale Web architectures and Big Data processing frameworks. Many research and engineering efforts have been dedicated to improve their performance and memory efficiency. More recently, such systems can leverage high-performance networks, e.g., Infiniband. To be able to leverage ...
Keywords: Energy efficiency, In-memory storage, Performance evaluation, RAMCloud

3
November 2016 SC '16: Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis
Publisher: IEEE Press
Bibliometrics:
Citation Count: 0
Downloads (6 Weeks): 4,   Downloads (12 Months): 40,   Downloads (Overall): 95

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Concurrent Big Data applications often require high-performance storage, as well as ACID (Atomicity, Consistency, Isolation, Durability) transaction support. Although blobs (binary large objects) are an increasingly popular storage model for such applications, state-of-the-art blob storage systems offer no transaction semantics. This demands users to coordinate data access carefully in order ...

4 published by ACM
October 2016 ACM Transactions on Parallel Computing (TOPC): Volume 3 Issue 3, December 2016
Publisher: ACM
Bibliometrics:
Citation Count: 2
Downloads (6 Weeks): 3,   Downloads (12 Months): 31,   Downloads (Overall): 117

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With exascale computing on the horizon, reducing performance variability in data management tasks (storage, visualization, analysis, etc.) is becoming a key challenge in sustaining high performance. This variability significantly impacts the overall application performance at scale and its predictability over time. In this article, we present Damaris, a system that ...
Keywords: dedicated cores, dedicated nodes, Damaris, in situ visualization, Exascale computing, I/O

5
September 2016 Future Generation Computer Systems: Volume 62 Issue C, September 2016
Publisher: Elsevier Science Publishers B. V.
Bibliometrics:
Citation Count: 0

The advent of unprecedentedly scalable yet energy hungry Exascale supercomputers poses a major challenge in sustaining a high performance-per-watt ratio. With I/O management acquiring a crucial role in supporting scientific simulations, various I/O management approaches have been proposed to achieve high performance and scalability. However, the details of how these ...
Keywords: Damaris, Dedicated cores, Exascale computing, Dedicated nodes, Energy, I/O

6 published by ACM
June 2016 ScienceCloud '16: Proceedings of the ACM 7th Workshop on Scientific Cloud Computing
Publisher: ACM
Bibliometrics:
Citation Count: 1
Downloads (6 Weeks): 2,   Downloads (12 Months): 22,   Downloads (Overall): 88

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Large-scale scientific experiments increasingly rely on geo-distributed clouds to serve relevant data to scientists worldwide with minimal latency. State-of-the-art caching systems often require the client to access the data through a caching proxy, or to contact a metadata server to locate the closest available copy of the desired data. Also, ...
Keywords: availability, cloud, content distribution network, data consistency, data warehousing, geo-replication, metadata, storage networks, wide-area replication

7
April 2016 Scientific Programming: Volume 2016, April 2016
Publisher: Hindawi Limited
Bibliometrics:
Citation Count: 0

Containers are considered an optimized fine-grain alternative to virtual machines in cloud-based systems. Some of the approaches which have adopted the use of containers are the MapReduce frameworks. This paper makes an analysis of the use of containers in MapReduce-based systems, concluding that the resource utilization of these systems in ...

8
March 2016 Concurrency and Computation: Practice & Experience: Volume 28 Issue 4, March 2016
Publisher: John Wiley and Sons Ltd.
Bibliometrics:
Citation Count: 2

The emergence of cloud computing has brought the opportunity to use large-scale compute infrastructures for a broader and broader spectrum of applications and users. As the cloud paradigm gets attractive for the 'elasticity' in resource usage and associated costs the users only pay for resources actually used, cloud applications still ...
Keywords: big data, Azure, MapReduce, cloud storage, data-intensive processing, scientific applications, cloud computing

9
March 2016 Concurrency and Computation: Practice & Experience: Volume 28 Issue 4, March 2016
Publisher: John Wiley and Sons Ltd.
Bibliometrics:
Citation Count: 0


10
January 2016 Future Generation Computer Systems: Volume 54 Issue C, January 2016
Publisher: Elsevier Science Publishers B. V.
Bibliometrics:
Citation Count: 5

With increasingly inexpensive storage and growing processing power, the cloud has rapidly become the environment of choice to store and analyze data for a variety of applications. Most large-scale data computations in the cloud heavily rely on the MapReduce paradigm and on its Hadoop implementation. Nevertheless, this exponential growth in ...
Keywords: DVFS, MapReduce, Governors, Power management, Hadoop

11
January 2016 IEEE Transactions on Cloud Computing: Volume 4 Issue 1, January 2016
Publisher: IEEE Computer Society Press
Bibliometrics:
Citation Count: 1

The global deployment of cloud datacenters is enabling large scale scientific workflows to improve performance and deliver fast responses. This unprecedented geographical distribution of the computation is doubled by an increase in the scale of the data handled by such applications, bringing new challenges related to the efficient data management ...

12
January 2016 Future Generation Computer Systems: Volume 54 Issue C, January 2016
Publisher: Elsevier Science Publishers B. V.
Bibliometrics:
Citation Count: 2

Scientific and commercial applications operate nowadays on tens of cloud datacenters around the globe, following similar patterns: they aggregate monitoring or sensor data, assess the QoS or run global data mining queries based on inter-site event stream processing. Enabling fast data transfers across geographically distributed sites allows such applications to ...
Keywords: Big Data, Stream processing, Multi-site, Cloud computing

13
December 2015 DSDIS '15: Proceedings of the 2015 IEEE International Conference on Data Science and Data Intensive Systems (DSDIS)
Publisher: IEEE Computer Society
Bibliometrics:
Citation Count: 0

Hadoop emerged as an important system for large-scale data analysis. Speculative execution is a key feature in Hadoop that is extensively leveraged in clouds: it is used to mask slow tasks (i.e., stragglers) -- resulted from resource contention and heterogeneity in clouds -- by launching speculative task copies on other ...

14 published by ACM
November 2015 ISAV2015: Proceedings of the First Workshop on In Situ Infrastructures for Enabling Extreme-Scale Analysis and Visualization
Publisher: ACM
Bibliometrics:
Citation Count: 6
Downloads (6 Weeks): 3,   Downloads (12 Months): 40,   Downloads (Overall): 119

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Over the past few years, the increasing amounts of data produced by large-scale simulations have motivated a shift from traditional offline data analysis to in situ analysis and visualization. In situ processing began as the coupling of a parallel simulation with an analysis or visualization library, motivated primarily by avoiding ...
Keywords: Exascale, Simulation, Coupling, FlowVR, In Situ Visualization, Damaris, Decaf, Swift

15
November 2015 World Wide Web: Volume 18 Issue 6, November 2015
Publisher: Kluwer Academic Publishers
Bibliometrics:
Citation Count: 2

The usage of Cloud Serviced has increased rapidly in the last years. Data management systems, behind any Cloud Service, are a major concern when it comes to scalability, flexibility and reliability due to being implemented in a distributed way. A Distributed Data Aggregation Service relying on a storage system meets ...
Keywords: Distributed services, Data management, Intelligent cloud services, Cloud storage, Data aggregation, Formal methods, Rule markup language

16
October 2015 BIG DATA '15: Proceedings of the 2015 IEEE International Conference on Big Data (Big Data)
Publisher: IEEE Computer Society
Bibliometrics:
Citation Count: 1

Hadoop emerged as the de facto state-of-the-art system for MapReduce-based data analytics. The reliability of Hadoop systems depends in part on how well they handle failures. Currently, Hadoop handles machine failures by re-executing all the tasks of the failed machines (i.e., executing recovery tasks). Unfortunately, this elegant solution is entirely ...

17
October 2015 SBAC-PAD '15: Proceedings of the 2015 27th International Symposium on Computer Architecture and High Performance Computing (SBAC-PAD)
Publisher: IEEE Computer Society
Bibliometrics:
Citation Count: 0

Apache Cassandra is an open-source cloud storage system that offers multiple types of operation-level consistency including eventual consistency with multiple levels of guarantees and strong consistency. It is being used by many data-center applications (e.g., Facebook and App Scale). Most existing research efforts have been dedicated to exploring trade-offs such ...

18
September 2015 CLUSTER '15: Proceedings of the 2015 IEEE International Conference on Cluster Computing
Publisher: IEEE Computer Society
Bibliometrics:
Citation Count: 1

With their globally distributed datacenters, clouds now provide an opportunity to run complex large-scale applications on dynamically provisioned, networked and federated infrastructures. However, there is a lack of tools supporting data intensive applications across geographically distributed sites. For instance, scientific workflows which handle many small files can easily saturate state-of-the-art ...
Keywords: metadata management, multi-site clouds, scientific workflows

19
September 2015 Procedia Computer Science: Volume 51 Issue C, September 2015
Publisher: Elsevier Science Publishers B. V.
Bibliometrics:
Citation Count: 0

The MapReduce community is progressively replacing the classic Hadoop with Yarn, the second-generation Hadoop (MapReduce 2.0). This transition is being made due to many reasons, but primarily because of some scalability drawbacks of the classic Hadoop. The new framework has appropriately addressed this issue and is being praised for its ...
Keywords: Hadoop, Yarn, fault tolerance, MapReduce

20
November 2014 DataCloud '14: Proceedings of the 5th International Workshop on Data-Intensive Computing in the Clouds
Publisher: IEEE Press
Bibliometrics:
Citation Count: 0
Downloads (6 Weeks): 0,   Downloads (12 Months): 5,   Downloads (Overall): 62

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Research on cloud-based Big Data analytics has focused so far on optimizing the performance and cost-effectiveness of the computations, while largely neglecting an important aspect: users need to upload massive datasets on clouds for their computations. This paper studies the problem of running MapReduce applications when considering the simultaneous optimization ...
Keywords: data management, incremental processing, MapReduce



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