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Manik Sharma, Smriti Smriti
The objective of this study is to analyzethe performance of static (HLFET) and dynamic (DLS) BNPparallel scheduling algorithm for allocating the tasks ofdistributed database over number of processors.  ...  Parallel processing is usedto solve the complex problems that require vast amount ofprocessing time. Task scheduling is one of the major problemsof parallel processing.  ...  and parallel processing (HLFET & DLS), when tasks in distributed environment are scheduled over three processors.  ... 
doi:10.24297/ijct.v1i1.2601 fatcat:d2ubgnmc5jdl3ofyxrr3xo7t3e

Big Data Management in the Cloud: Evolution or Crossroad? [chapter]

Abdelkader Hameurlain, Franck Morvan
2016 Communications in Computer and Information Science  
In this perspective, data management based on parallel and cloud (e.g.  ...  MapReduce) systems are overviewed, and compared by relying on meeting software requirements (e.g. data independence, software reuse), high performance, scalability, elasticity, and data availability.  ...  Parallel database systems have been developed for applications processing a large volume of data. Their main objectives are to obtain high performance and resource availability.  ... 
doi:10.1007/978-3-319-34099-9_2 fatcat:nj57rxfi5bhlxfwr7risc3tpcq

Superposition Enhanced Nested Sampling

Stefano Martiniani, Jacob D. Stevenson, David J. Wales, Daan Frenkel
2014 Physical Review X  
We also introduce a novel parallelization algorithm for nested sampling.  ...  The theoretical analysis of many problems in physics, astronomy and applied mathematics requires an efficient numerical exploration of multimodal parameter spaces that exhibit broken ergodicity.  ...  The key insight of nested sampling is that the volumes, Ω E≤ER , normalised by the total phase space volume, are distributed according to the Beta distribution, Beta(K − R + 1, R) [46] .  ... 
doi:10.1103/physrevx.4.031034 fatcat:b6a6caz355ahdint6b2raymssu

Main Memory Database Systems

Frans Faerber, Alfons Kemper, Per-Åke Larson, Justin Levandoski, Tjomas Neumann, Andrew Pavlo
2017 Foundations and Trends in Databases  
Editorial Scope Topics Foundations and Trends R in Databases covers a breadth of topics relating to the management of large volumes of data.  ...  Kersten, and Hans Oerlemans. PRISMA Database Machine: A Distributed, Main-Memory Approach.  ... 
doi:10.1561/1900000058 fatcat:j7dpcbszkbdqdarwrxdt3dv5ja

A Combined Horizontal Parallel Apriori Algorithm and Adaptive Frequent Pattern Growth Algorithm for Big Data Mining

With the rapid increase in the database size, parallel and distributed computing systems can yield better benefits in the data mining applications.  ...  In this paper, a combined Horizontal Parallel-Apriori (HP-Apriori) and Adaptive Frequent Pattern (FP) Growth algorithm is proposed to divide the database both horizontally and vertically into four sub-processes  ...  The Data Distribution algorithm divides the entire database and assigns the candidate itemsets to various processors.  ... 
doi:10.35940/ijitee.b1133.1292s219 fatcat:eicabawvgrbvfgmhaxpjbwu2ni

Implementation and Evaluation of mpiBLAST-PIO on HPC Cluster

Nisha Dhankher, O P Gupta
2014 International Journal of Computer Applications  
In mpiBLAST, the master process distributes the database fragments among worker nodes to compute the sequence search in parallel.  ...  As merging and writing of the results is done sequentially by the master process, it would create performance bottleneck with increasing number of processors and varying database sizes.  ...  As BLAST is both computationally intensive and parallelizes well, many parallel and distributed approaches of parallelizing BLAST have been proposed.  ... 
doi:10.5120/17131-7735 fatcat:trriihl3erainbw7ssxhcwdcyy

Parallel and Distributed Data Mining: An Introduction [chapter]

Mohammed J. Zaki
2000 Lecture Notes in Computer Science  
This chapter presents a survey on large-scale parallel and distributed data mining algorithms and systems, serving as an introduction to the rest of this volume.  ...  The explosive growth in data collection in business and scientific fields has literally forced upon us the need to analyze and mine useful knowledge from it.  ...  We hope that this volume, representing the state-of-the-art in parallel and distributed mining methods, will be successful in bringing to surface the requirement and challenges in large-scale parallel  ... 
doi:10.1007/3-540-46502-2_1 fatcat:3mmcofbadbas7f7r5y5opxxwdy

Distributed Database Kriging for Adaptive Sampling (D2KAS)

Dominic Roehm, Robert S. Pavel, Kipton Barros, Bertrand Rouet-Leduc, Allen L. McPherson, Timothy C. Germann, Christoph Junghans
2015 Computer Physics Communications  
We present an adaptive sampling method supplemented by a distributed database and a prediction method for multiscale simulations using the Heterogeneous Multiscale Method.  ...  The cloud database Redis provides the plain table lookup, and with locality aware hashing we gather input data for our prediction scheme.  ...  Rivera and E. Cieren for fruitful discussions at the beginning of this project as well as J. Mohd-Yusof for support with the CoMD code.  ... 
doi:10.1016/j.cpc.2015.03.006 fatcat:c46psndt4vc45akgxq6odjnory

Interactive Big Data Analytics Platform for Healthcare and Clinical Services

Dillon Chrimes
2018 Global Journal of Engineering Sciences  
The next step of the testing of the BDA platform will be to distribute and index the data to ten billion patient data rows across the database nodes, and then test the performance using the established  ...  Afterwards, the study plan is to distribute the data across 100 nodes; Hadoop's HDFS and HBase are theoretically supposed to scale and function better with more nodes [14, 15] .  ...  nodes across the computing cluster, and (2) high-throughput data processing via a batch processing framework and the Hadoop Distributed File System (HDFS) [38, [40] [41] [42] [43] .  ... 
doi:10.33552/gjes.2018.01.000502 fatcat:biiz2qnx4vckrcrmv4gcn5ydru

Scalability and Fuzzy Systems: What Parallelization Can Do [chapter]

Malaquias Q. Flores, Federico Del Razo, Anne Laurent, Nicolas Sicard
2013 Studies in Computational Intelligence  
In this paper, we discuss how the parallelization of fuzzy algorithms is crucial to tackle the problem of scalability and optimal performance in the context of database mining.  ...  Fuzzy) Database management systems aim at providing tools for data storage and querying.  ...  model (FRDBM) and into of the objectoriented database model (FOODBM) [33] [38] .  ... 
doi:10.1007/978-3-319-00954-4_13 fatcat:okkfilr5njdmrbijkdeyryuqca


Renu Chaudhary, Gagangeet Singh
2014 International journal of research - granthaalayah  
Results:Large-scale data processing (parallel processing over distributed systems); Embedded IR (basic machine-to-machine information look-up & retrieval); Exploratory analytics on semi-structured data  ...  Conclusions:This study report motivation to provide an independent understanding of the strengths and weaknesses of various NoSQL database approaches to supporting applications that process huge volumes  ...  The exponential growth of the volume of data generated by users, systems and sensors, further accelerated by the concentration of large part of this volume on big distributed systems like Amazon, Google  ... 
doi:10.29121/granthaalayah.v1.i1.2014.3086 fatcat:drzvgh6tcvflda52scih2dpqbi


Hyogi Sim, Youngjae Kim, Sudharshan S. Vazhkudai, Geoffroy R. Vallée, Seung-Hwan Lim, Ali R. Butt
2017 Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis on - SC '17  
Data services such as search, discovery, and management in scalable distributed environments have traditionally been decoupled from the underlying file systems, and are often deployed using external databases  ...  CCS CONCEPTS • Software and its engineering → File systems management; • Information systems → Distributed storage;  ...  [38] .  ... 
doi:10.1145/3126908.3126929 dblp:conf/sc/SimKVVLB17 fatcat:db3r5tzh6veexgbr52qagli3le

Review of Apriori Based Algorithms on MapReduce Framework [article]

Sudhakar Singh, Rakhi Garg, P. K. Mishra
2017 arXiv   pre-print
The problems with most of the distributed framework are overheads of managing distributed system and lack of high level parallel programming language.  ...  Now days many algorithms have been proposed on parallel and distributed platforms to enhance the performance of Apriori algorithm.  ...  CD and DD algorithms are categorized under data parallelism and task parallelism while candidate distribution algorithm is hybrid of data parallelism and task parallelism [38] .  ... 
arXiv:1702.06284v1 fatcat:khpoq35xcfhzfc4v7mm362bbyq

A Survey of Data Mining Activities in Distributed Systems

Waleed A. Mohammad, Hajar Maseeh Yasin, Azar Abid Salih, Adel AL-Zebari, Naaman Omar, Karwan Jameel Merceedi, Abdulraheem Jamil Ahmed, Nareen O. M. Salim, Sheren Sadiq Hasan, Shakir Fattah Kak, Ibrahim Mahmood Ibrahim
2021 Asian Journal of Research in Computer Science  
Managing massive amounts of data and processing them with limited resources is difficult. Large volumes of data, for instance, are swiftly generated and stored in many locations.  ...  distributed data mining methods, such as distributed common item-set mining, distributed frequent sequence mining, technical difficulties with distributed systems, distributed clustering, as well as privacy-protection  ...  A large volume of data was given through the widespread usage of computers and advances in database technology [49] .  ... 
doi:10.9734/ajrcos/2021/v11i430267 fatcat:t4wcvxu2czd45imagjenzsvcqi

Turning points in systems architecture

A. G. Ganek, E. H. Sussenguth
1999 IBM Systems Journal  
processing services, databases, and networking.  ...  An alternative approach for implementing a multiple processor complex is utilized in the S/390 Parallel Sysplex Cluster, which is the topic for the entire issue of Volume 36, Number 2, 1997 of the IBM  ...  He was the recipient of IBM Outstanding Innovation Awards for his work on Enterprise Systems Architecture/370 and System/390 Parallel Sysplex Design.  ... 
doi:10.1147/sj.382.0335 fatcat:ldcu6dmos5ak3krkw4o5wtphgm
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