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Scalable Data Placement of Data-intensive Services in Geo-distributed Clouds

Ankita Atrey, Gregory Van Seghbroeck, Bruno Volckaert, Filip De Turck
2018 Proceedings of the 8th International Conference on Cloud Computing and Services Science  
The advent of big data analytics and cloud computing technologies has resulted in wide-spread research in finding solutions to the data placement problem, which aims at properly placing the data items  ...  In this paper, we propose a scalable method for performing data placement of data-intensive services into geographically distributed clouds.  ...  The advancements in big data and cloud computing technologies have definitely enriched the field of scalable data management with state-of-theart distributed data processing systems like Hadoop and more  ... 
doi:10.5220/0006767504970508 dblp:conf/closer/AtreySVT18 fatcat:vanetevax5hftkty65xmx7vd4u

Cloud-Based Infrastructure for Data-Intensive e-Science Applications: Requirements and Architecture [chapter]

Yuri Demchenko, Canh Ngo, Paola Grosso, Cees de Laat, Peter Membrey
2015 Cloud Computing with e-Science Applications  
The chapter introduces the Scientific Data Lifecycle Management (SDLM) model that includes all the major stages and reflects specifics in data management in modern e-Science.  ...  The chapter discusses how the proposed models SDLM and SDI can be naturally implemented using modern cloud based infrastructure services, analyses security and trust issues in cloud based infrastructure  ...  [51] and recently established the NIST Big Data WG (NBD-WG) [52] .  ... 
doi:10.1201/b18021-3 fatcat:g36sf7g6nneahmad2crfwy4fyq

Unifying Data and Replica Placement for Data-intensive Services in Geographically Distributed Clouds

Ankita Atrey, Gregory Van Seghbroeck, Higinio Mora, Filip De Turck, Bruno Volckaert
2019 Proceedings of the 9th International Conference on Cloud Computing and Services Science  
In this paper, we propose a unified paradigm of data placement, called CPR, which combines data placement and replication of data-intensive services into geographically distributed clouds as a joint optimization  ...  The increased reliance of data management applications on cloud computing technologies has rendered research in identifying solutions to the data placement problem to be of paramount importance.  ...  MOTIVATION With the emergence of Cloud computing, Big Data, and Internet of Things (IoT), the rate at which data is being generated is increasing exponentially (ins, 2017; gro, 2018) .  ... 
doi:10.5220/0007613400250036 dblp:conf/closer/AtreySMTV19 fatcat:idsh2wuezbbofkco47aprnuv6a

Location, Location, Location: Data-Intensive Distributed Computing in the Cloud

Michael Luckeneder, Adam Barker
2013 2013 IEEE 5th International Conference on Cloud Computing Technology and Science  
We evaluate our approach by executing randomly generated data-intensive workflows deployed on the PlanetLab platform in order to rank Amazon EC2 Cloud regions.  ...  In this paper we present CloudForecast: a Web service framework and analysis tool which given a workflow specification, computes the optimal Amazon EC2 Cloud region to automatically deploy the orchestration  ...  Our proposed approach addresses the bottlenecks associated with executing highly distributed and data-intensive applications in the Cloud.  ... 
doi:10.1109/cloudcom.2013.91 dblp:conf/cloudcom/LuckenederB13 fatcat:2c4qi52ivnet7e2ybpiokjqmu4

Cloud Storage and Bioinformatics in a Private Cloud Deployment: Lessons for Data Intensive Research [chapter]

Victor Chang, Robert John Walters, Gary Wills
2013 Communications in Computer and Information Science  
Experiments for data services (backup automation, data recovery and data migration) are performed and results confirm backup automation is completed swiftly and is reliable for data-intensive research.  ...  This paper describes service portability for a private cloud deployment, including a detailed case study about Cloud Storage and bioinformatics services developed as part of the Cloud Computing Adoption  ...  Plug and Play Features in Cloud Storage for Data Intensive Research There are papers explaining the importance and relevance of data intensive research, and why it is essential for Cloud development and  ... 
doi:10.1007/978-3-319-04519-1_16 fatcat:hxgig2gxzffllpjfwvyztgcpju

Dynamic Data Partitioning and Virtual Machine Mapping: Efficient Data Intensive Computation

Kenn Slagter, Ching-Hsien Hsu, Yeh-Ching Chung
2013 2013 IEEE 5th International Conference on Cloud Computing Technology and Science  
MapReduce achieves this by distributing the storage and processing of data amongst a large number of computers (nodes).  ...  Big data can be awkward to work and the storage, processing and analysis of big data can be problematic. MapReduce is a recent programming model that can handle big data.  ...  Alternatively, MapReduce may be deployed on a hybrid cloud environment, where computing resources tend to be heterogeneous [7] .  ... 
doi:10.1109/cloudcom.2013.134 dblp:conf/cloudcom/SlagterHC13 fatcat:54ool2qmcndazaxqqlimwib54e

Multi-dimensional Resource Allocation for Data-intensive Large-scale Cloud Applications
english

Foued Jrad, Jie Tao, Ivona Brandic, Achim Streit
2014 Proceedings of the 4th International Conference on Cloud Computing and Services Science  
Today, the economic and technical benefits offered by the Cloud computing technology encouraged many users to migrate their applications to Cloud.  ...  Using an implemented Multi-Cloud simulation environment, we evaluated our approach with a real data-intensive workflow application in different scenarios.  ...  performance of data-intensive workflows.  ... 
doi:10.5220/0004971906910702 dblp:conf/closer/JradTBS14 fatcat:iqbr2x34nbexfma2xpqavuc6ti

A Cost-Aware Resource Selection for Data-intensive Applications in Cloud-oriented Data Centers

Wei Liu, Feiyan Shi, Wei Du, Hongfeng Li
2011 International Journal of Information Technology and Computer Science  
As a kind of large-scale user-oriented dataintensive computing, cloud computing allows users to utilize on-demand computation, storage, data and services from around the world in a pay-as-you-go model.  ...  In cloud environment, applications need access to mass datasets that may each be replicated on different resources (or data centers).  ...  As business application of data-intensive computing, cloud computing allows users to utilize on-demand computation, storage, data and services from around the world in a pay-as-you-go model [1] .  ... 
doi:10.5815/ijitcs.2011.01.02 fatcat:qstsjqrwmzhhxp3ox3bp53bqvu

Gemini: An Adaptive Performance-Fairness Scheduler for Data-Intensive Cluster Computing

Zhaojie Niu, Shanjiang Tang, Bingsheng He
2015 2015 IEEE 7th International Conference on Cloud Computing Technology and Science (CloudCom)  
In data-intensive cluster computing platforms such as Hadoop YARN, performance and fairness are two important factors for system design and optimizations.  ...  We first develop a model with the regression approach to estimate the performance improvement and the fairness loss under the sharing computation compared to the exclusive non-sharing scenario.  ...  INTRODUCTION In the current era of "big data", data-intensive cluster computing is a common paradigm in clusters and clouds.  ... 
doi:10.1109/cloudcom.2015.52 dblp:conf/cloudcom/NiuTH15 fatcat:dh7qeiut5vcxrfktw3t2vt3rke

Optimizing and dimensioning a data intensive cloud application for soccer player tracking

Gergely Dobreff, Marton Molnar, Laszlo Toka
2022 International Journal of Computer Science in Sport  
latency and cloud costs low.  ...  Cloud-based services revolutionize how applications are designed and provisioned in more and more application domains.  ...  Data analytics in sports has been gaining steam: with novel means of collecting data, applying creative data mining methods and the rise of cloud-deployed big data technologies, both the complexity and  ... 
doi:10.2478/ijcss-2022-0004 fatcat:isfn7vffffh3vgbutwrpzddulm

Real-Time Handling of Network Monitoring Data Using a Data-Intensive Framework

Aryan Taherimonfared, Tomasz Wiktor Wlodarczyk, Chunming Rong
2013 2013 IEEE 5th International Conference on Cloud Computing Technology and Science  
This mechanism takes advantage of a data-intensive framework for collecting network flow information records, as well as data points' indexes.  ...  In addition, the requirements (e.g. response time, accuracy) imposed by longterm planned queries and short-term ad-hoc queries should be satisfied for multi-tenant computing models.  ...  ACKNOWLEDGMENT The authors would like to thank Olav Kvittem and Arne Oslebo from UNINETT and Martin Gilje Jaatun from SINTEF ICT, who provided valuable comments and assistance to the undertaking of this  ... 
doi:10.1109/cloudcom.2013.41 dblp:conf/cloudcom/TaheriMonfaredWR13 fatcat:jkqi2m7gevg63jkdlmjbd7r2eu

Load Balanced and Energy Aware Cloud Resource Scheduling Design for Executing Data-intensive Application in SDVC

Shalini. S, Annapurna P Patil
2021 International Journal of Advanced Computer Science and Applications  
In SDVC, the vehicle enables virtualization technology through SDVN and provides complex data-intensive workload execution in scalable and efficient manner.  ...  Cloud computational platform provisions numerous cloud-based Vehicular Adhoc Network (VANET) applications.  ...  A vast majority of these applications require complicated computation and various methods to recognize the patterns, which can compute intensive data and thus need a processor which can provide a powerful  ... 
doi:10.14569/ijacsa.2021.0121040 fatcat:odv3z2fjgbhczaqxycxf5qvfx4

Asterism: Pegasus and Dispel4py Hybrid Workflows for Data-Intensive Science

Rosa Filgueira, Rafael Ferreira da Silva, Amrey Krause, Ewa Deelman, Malcolm Atkinson
2016 2016 Seventh International Workshop on Data-Intensive Computing in the Clouds (DataCloud)  
Keywords Data-Intensive science, scientific workflows, stream-based system, deployment and reusability of execution environments  ...  We also present the Data-Intensive workflows as a Service (DIaaS) model, which enables easy dataintensive workflow composition and deployment on clouds using containers.  ...  It was funded under the Scottish Informatics and Computer Science Alliance with the Postdoctoral and Early Career Researcher Exchanges fellowship, and by the National Science Foundation under the SI 2  ... 
doi:10.1109/datacloud.2016.004 dblp:conf/sc/FilgueiraSKDA16 fatcat:efpt66w6tnho3p7a3j6eoqejva

A Cloud Environment for Data-intensive Storage Services

Elliot K. Kolodner, Sivan Tal, Dimosthenis Kyriazis, Dalit Naor, Miriam Allalouf, Lucia Bonelli, Per Brand, Albert Eckert, Erik Elmroth, Spyridon V. Gogouvitis, Danny Harnik, Francisco Hernandez (+9 others)
2011 2011 IEEE Third International Conference on Cloud Computing Technology and Science  
In this paper we present the architecture of a scalable and flexible cloud environment addressing the challenge of providing data-intensive storage cloud services through raising the abstraction level  ...  of storage, enabling data mobility across providers, allowing computational and content-centric access to storage and deploying new data-oriented mechanisms for QoS and security guarantees.  ...  ACKNOWLEDGMENT The research leading to these results is partially supported by the European Community's Seventh Framework Programme (FP7/2001-2013) under grant agreement n° 257019 -VISION Cloud Project  ... 
doi:10.1109/cloudcom.2011.55 dblp:conf/cloudcom/KolodnerTKNABBEEGHHJLLLMSTVW11 fatcat:gani6wcumvh35asccr4g5tphma

Spatial cloud computing: how can the geospatial sciences use and help shape cloud computing?

Chaowei Yang, Michael Goodchild, Qunying Huang, Doug Nebert, Robert Raskin, Yan Xu, Myra Bambacus, Daniel Fay
2011 International Journal of Digital Earth  
2011) 'Spatial cloud computing: how can the geospatial sciences use and help shape cloud computing?'  ...  Huadong Guo and Changlin Wang for inviting us to write this definition and field review paper. Research  ...  To capture the intrinsic relationship between cloud computing and geospatial sciences, we introduce spatial cloud computing (SCC) to: (1) enable solving geospatial science problems of the four intensiveness  ... 
doi:10.1080/17538947.2011.587547 fatcat:g6jrs3avrffxddy74baqgmyhoi
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