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Big Data Migration between Data Centers in Online Cloud Environment

Prasad Teli, Manoj V. Thomas, K. Chandrasekaran
2016 Procedia Technology - Elsevier  
This proposed approach gives an optimal cost solution for the data aggregation from different geographically distributed data centers which can be efficiently processed at a single site using distributed  ...  One of the solutions for reducing the cost of processing such geographically distributed big data is data aggregation.  ...  Pandora [16] , gives an optimal cost solution for transferring large amount of data from one data center to the other geographically distant data center.  ... 
doi:10.1016/j.protcy.2016.05.135 fatcat:ddixrxxpgnghlatvjm23nw443e

A Coflow-Based Co-Optimization Framework for High-Performance Data Analytics

Long Cheng, Ying Wang, Yulong Pei, Dick Epema
2017 2017 46th International Conference on Parallel Processing (ICPP)  
Efficient execution of distributed database operators such as joining and aggregating is critical for the performance of big data analytics.  ...  We present the detailed design and implementation of CCF, and conduct an experimental evaluation of CCF using large-scale simulations on large data joins.  ...  to optimize the data communications for the Hash and Mini approach.  ... 
doi:10.1109/icpp.2017.48 dblp:conf/icpp/ChengWPE17 fatcat:aykqgmy5x5fxvma5tz5nggagby

Author index

2013 2013 IEEE International Conference on Cluster Computing (CLUSTER)  
: A Cost-Efficient, High-Performance Hybrid Storage Cache Liu, Zhou A Case of System-Wide Power Management for Scientific Applications Lix, Philipp Automotive Big Data Lofstead, Jay A Case of  ...  MOLAR: A Cost-Efficient, High-Performance Hybrid Storage Cache Duato, José Influence of InfiniBand FDR on the Performance of Remote GPU Virtualization Duffy, Edward JUMMP: Job Uninterrupted Maneuverable  ... 
doi:10.1109/cluster.2013.6702604 fatcat:cxctjrwnfjahhosdn7afzf6dla

RHEEM: enabling cross-platform data processing

Divy Agrawal, Mourad Ouzzani, Paolo Papotti, Jorge-Arnulfo Quiané-Ruiz, Nan Tang, Saravanan Thirumuruganathan, Anis Troudi, Sanjay Chawla, Bertty Contreras-Rojas, Ahmed Elmagarmid, Yasser Idris, Zoi Kaoudi (+3 others)
2018 Proceedings of the VLDB Endowment  
It features (i) a robust interface to easily compose data analytic tasks; (ii) a novel cost-based optimizer able to find the most efficient platform in almost all cases; and (iii) an executor to efficiently  ...  Addressing this pain and achieving automatic cross-platform data processing is quite challenging: finding the most efficient platform for a given task requires quite good expertise for all the available  ...  THE DARK SIDE OF BIG DATA The pursuit of comprehensive, efficient, and scalable data analytics as well as the one-size-does-not-fit-all dictum have given rise to a plethora of data processing platforms  ... 
doi:10.14778/3236187.3236195 fatcat:xt4qxbumhjfptfb3g2xkkkjlay

Agrios: A hybrid approach to big array analytics

Patrick Leyshock, David Maier, Kristin Tufte
2013 2013 IEEE International Conference on Big Data  
Hybrid systems for analyzing big data integrate an analytic tool and a dedicated data-management platform.  ...  Agrios minimizes data movement between the two components of the hybrid, using techniques repurposed from relational database query optimization.  ...  ACKNOWLEDGMENT This material is based upon work supported by National Science Foundation Grant Number 1110917, and the support of Intel's Science and Technology Center for Big Data.  ... 
doi:10.1109/bigdata.2013.6691558 dblp:conf/bigdataconf/LeyshockMT13 fatcat:rdtp6lgyx5gxnopfekxmkjehvy

Energy Efficient Tapered Data Networks for Big Data processing in IP/WDM networks

Ali M. Al-Salim, Ahmed Q. Lawey, Taisir El-Gorashi, Jaafar M. H. Elmirghani
2015 2015 17th International Conference on Transparent Optical Networks (ICTON)  
Ali Al-Salim would like to acknowledge The Higher Committee for Education Development in Iraq (HCED/IRAQ) for funding his scholarship.  ...  ACKNOWLEDGEMENT The authors would like to acknowledge funding from the Engineering and Physical Sciences Research Council (EPSRC), INTERNET (EP/H040536/1) and STAR (EP/K016873/1). Mr.  ...  In [5] the authors study the minimization of overall cost for Big Data placement, processing, and movement across geodistributed data centers.  ... 
doi:10.1109/icton.2015.7193536 fatcat:57ufy5xmbjadbkv63k34veesr4

The role of sensors, big data and machine learning in modern animal farming

Suresh Neethirajan
2020 Sensing and Bio-Sensing Research  
More specifically, this paper explores the role of sensors, big data, artificial intelligence and machine learning in helping animal farmers to lower production costs, increase efficiencies, enhance animal  ...  Together the growing demand for food and the advancement in sensing technology have the potential to make animal farming more centralized, large scale and efficient.  ...  The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.  ... 
doi:10.1016/j.sbsr.2020.100367 fatcat:gu33jpez6vbvvexay373b6s7ti

Data Movement Options in Accelerated Clusters [chapter]

Holger Fröning
2014 Lecture Notes in Computer Science  
An Optimized Data Movement Method for GPU Clusters As it is unfeasible to explore all communication options for heterogeneous systems in a single work, we focus here on data movement optimizations for  ...  This is followed by an introduction to the Global GPU Address Spaces (GGAS) project, which we use to explore data movement optimizations in heterogeneous environments.  ...  Acknowledgements The author would like to thank Sudhakar Yalamanchili and Mark Hummel for the various insightful discussions.  ... 
doi:10.1007/978-3-642-54420-0_41 fatcat:uv4srhx4tvgj5kccf4cvbbim7q

High value of ecological information for river connectivity restoration

Suresh Andrew Sethi, Jesse R. O'Hanley, Jonathon Gerken, Joshua Ashline, Catherine Bradley
2017 Landscape Ecology  
Objectives We developed an optimization approach for barrier mitigation planning which directly incorporates the ecology of managed taxa, and applied it to an urbanizing salmonbearing watershed in Alaska  ...  The value of ecological information on managed taxa was estimated by comparing costs to achieve restoration targets across alternative barrier prioritization approaches.  ...  (b) Value of ecological information calculated as the added cost required for the DCI maximization approach to achieve a given level of LCCI in M USD (black line, left axis) and added cost for the DCI  ... 
doi:10.1007/s10980-017-0571-2 fatcat:e2kv73vj6zb5tclirfyrj7vgpm

A Big Data Placement Strategy in Geographically Distributed Datacenters

Laila Bouhouch, Mostapha Zbakh, Claude Tadonki
2020 2020 5th International Conference on Cloud Computing and Artificial Intelligence: Technologies and Applications (CloudTech)  
The obtained results show that our proposed strategy produces an efficient placement and actually reduces the overheads of the data movement compared to both a random assignment and a selected placement  ...  Second, we apply a greedy algorithm in order to assign each dataset to the optimal datacenter w.r.t the overall cost of data migrations.  ...  The results of the proposed approach gives better nearly-optimal solutions for the data placement and data scheduling among datacenters.  ... 
doi:10.1109/cloudtech49835.2020.9365881 fatcat:mhimnj2ffzdsxa6incbzlntqly

Energy-Efficient Big Data Analytics in Datacenters [chapter]

Farhad Mehdipour, Hamid Noori, Bahman Javadi
2016 Advances in Computers  
We later discuss the techniques for improving energy efficiency in the cloud-based datacenters for big data analytics.  ...  The volume of generated data increases by the rapid growth of Internet of Things (IoT), leading to the big data proliferation and more opportunities for data centers.  ...  Storage An efficient storage mechanism for big data is an essential part of the modern datacenters.  ... 
doi:10.1016/bs.adcom.2015.10.002 fatcat:xpecmdmje5avvphkdrdnyv4fqi

Cost Minimization for Big Data Processing in Geo-Distributed Data Centres

T. Sai Raaga Sowmya
2016 Asia-pacific Journal of Convergent Research Interchange  
So, cost minimization became an issue for the upcoming big data. One of the main feature of big data is coupling of data and computation as computation task.  ...  In this paper we study how to minimize cost through joint optimization of these above three factors for big data service in geo distributes data centres.  ...  about cost minimization for big data processing in geo-distributed data centers [7] [8] [9] .  ... 
doi:10.21742/apjcri.2016.12.05 fatcat:bm55z37syzarnemct5hu63no4a

On the Impact of High Performance Computing in Big Data Analytics for Medicine

2020 Applied Medical Informatics  
There are important differences in the approaches of these two domains: those that are working in BDA focus on the 5Vs of big data which are: volume, velocity, variety, veracity, and value, while HPC scientists  ...  The big data analytics domain (BDA) has been rapidly developed over the last years to process huge amounts of data now being generated in various domains.  ...  List of abbreviations HPC -High-Performance Computing BDA -Big Data Analytics HPDA -High-Performance Data Analytics AI -Artificial Intelligence GPU -Graphics Processing Unit  ... 
doaj:93e7a1b33ede41308d99e4db9f992fa7 fatcat:mpabfa7smrh57ix4x3uncfy6bu

A Survey on Trajectory Big Data Processing

Amina Belhassena
2018 International Journal of Performability Engineering  
Furthermore, this paper reviews an extensive collection of existing applications of movement objects, including trajectory data mining and frequent trajectory.  ...  As the massive trajectory data processing exceeds the power of centralized approaches used previously, in this paper, we survey various existing tools used to process large-scale trajectory data in a distributed  ...  Acknowledgements This paper was partially supported by NSFC grant U1509216,61472099, National Sci-Tech Support Plan 2015BAH10F01, the Scientific Research Foundation for the Returned Overseas Chinese Scholars  ... 
doi:10.23940/ijpe.18.02.p13.320333 fatcat:m74w3cfajrbzpamzpghfyrm6am

Near-Data Processing: Insights from a MICRO-46 Workshop

Rajeev Balasubramonian, Jichuan Chang, Troy Manning, Jaime H. Moreno, Richard Murphy, Ravi Nair, Steven Swanson
2014 IEEE Micro  
The trend toward big data is leading to changes in the computing paradigm, and in particular to the notion of moving computation to data, in what we call the near-data processing (NDP) approach.  ...  Data movement impacts performance, power efficiency, and reliability, three fundamental attributes of a system.  ...  Acknowledgments Some of this work was performed while Jichuan Chang was at HP Labs.  ... 
doi:10.1109/mm.2014.55 fatcat:sm7nqssporhd3bfa2srmklou64
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