Results 51 to 60 of about 2,055 (161)

MapReduce: within, outside, or on the side-by-side with parallel DBMSs?

Труды Института системного программирования РАН, 2018
The approaches of use of MapReduce technology together with analytical DBMSs are discussed. The paper considers approaches where one implements MapReduce within a kernel of a parallel DBMS, where MapReduce serves as a communication infrastructure of a ...
Sergey D. Kuznetsov.
doaj  

FCNB: Fuzzy Correlative Naive Bayes Classifier with MapReduce Framework for Big Data Classification

Journal of Intelligent Systems, 2018
The term “big data” means a large amount of data, and big data management refers to the efficient handling, organization, or use of large volumes of structured and unstructured data belonging to an organization.
Banchhor Chitrakant, Srinivasu N.
doaj   +1 more source

Applicability Assessment of Technologies for Predictive and Prescriptive Analytics of Nephrology Big Data

PROTEOMICS, Volume 25, Issue 11-12, June 2025.
ABSTRACT The integration of big data into nephrology research will open new avenues for analyzing and understanding complex biological datasets, driving advances in personalized management of kidney diseases. This paper describes the multifaceted challenges and opportunities by incorporating big data in nephrology, emphasizing the importance of data ...
Riste Stojanov, Milos Jovanovik, Sasho Gramatikov, Igor Mishkovski, Eftim Zdravevski, Darko Sasanski, Zorica Karapancheva, Goce Spasovski, Ivona Vasileska, Tome Eftimov, Wu Zhuojun, Joachim Jankowski, Dimitar Trajanov   +12 more
wiley   +1 more source

CloudSim 7G: An Integrated Toolkit for Modeling and Simulation of Future Generation Cloud Computing Environments

Software: Practice and Experience, Volume 55, Issue 6, Page 1041-1058, June 2025.
ABSTRACT Background Cloud Computing has established itself as an efficient and cost‐effective paradigm for the execution of web‐based applications, and scientific workloads, that need elasticity and on‐demand scalability capabilities. However, the evaluation of novel resource provisioning and management techniques is a major challenge due to the ...
Remo Andreoli, Jie Zhao, Tommaso Cucinotta, Rajkumar Buyya   +3 more
wiley   +1 more source

Research of kNN algorithm based on MapReduce and double levels of inverted grid index(基于MapReduce和双层倒排网格索引的kNN算法)

Zhejiang Daxue xuebao. Lixue ban, 2014
随着卫星定位技术和移动互联网技术的飞速发展，地理空间数据来源变得更加多源异构.面对海量地理空间数据，如何快速有效地找到目标周围的兴趣点变得异常重要.依据空间k近邻(kNN)查询算法，提高效率的关键在数据索引和数据块存储结构设计，通过引入云计算的MapReduce编程模型，设计了一种面向MapReduce的地理空间数据双层倒排网格索引，利用CircularTrip算法实现了目标点近邻查询计算，最终获得距离目标点最邻近的数据点集.实验结果表明，该索引方法较单层倒排网格索引下的kNN查询效率有明显提高 ...
ZHAOMinchao(赵敏超), DUZhenhong(杜震洪), ZHANGFeng(张丰), LIURenyi(刘仁义), LIRongya(李荣亚)   +4 more
doaj   +1 more source

Clustering‐based recommendation method with enhanced grasshopper optimisation algorithm

CAAI Transactions on Intelligence Technology, Volume 10, Issue 2, Page 494-509, April 2025.
Abstract In the era of big data, personalised recommendation systems are essential for enhancing user engagement and driving business growth. However, traditional recommendation algorithms, such as collaborative filtering, face significant challenges due to data sparsity, algorithm scalability, and the difficulty of adapting to dynamic user preferences.
Zihao Zhao, Yingchun Xia, Wenjun Xu, Hui Yu, Shuai Yang, Cheng Chen, Xiaohui Yuan, Xiaobo Zhou, Qingyong Wang, Lichuan Gu   +9 more
wiley   +1 more source

Interpretable decision-tree induction in a big data parallel framework

International Journal of Applied Mathematics and Computer Science, 2017
When running data-mining algorithms on big data platforms, a parallel, distributed framework, such asMAPREDUCE, may be used. However, in a parallel framework, each individual model fits the data allocated to its own computing node without necessarily ...
Weinberg Abraham Itzhak, Last Mark
doaj   +1 more source

Autonomous Intelligent Monitoring of Photovoltaic Systems: An In‐Depth Multidisciplinary Review

Progress in Photovoltaics: Research and Applications, Volume 33, Issue 3, Page 381-409, March 2025.
This article examines the autonomous monitoring and analysis of PV plants, highlighting key barriers and research directions for smart monitoring of PV systems. The discussed topics cover UAV choice and related standards, camera varieties, AI applications in monitoring, datasets, and data enhancement methods, as well as data exchange between UAVs and ...
M. Aghaei, M. Kolahi, A. Nedaei, N. S. Venkatesh, S. M. Esmailifar, A. M. Moradi Sizkouhi, A. Aghamohammadi, A. K. V. Oliveira, A. Eskandari, P. Parvin, J. Milimonfared, V. Sugumaran, R. Rüther   +12 more
wiley   +1 more source

Processing of raw astronomical data of large volume by MapReduce model

Труды Института системного программирования РАН, 2018
Exponential grow of volume, increased quality of data in current and incoming sky surveys open new horizons for astrophysics but require new approaches to data processing especially big data technologies and cloud computing.
S. . Gerasimov, A. . Mesheryakov, I. . Kolosov, E. . Glotov, I. . Popov   +4 more
doaj   +1 more source

SparkGrid: Blockchain Assisted Secure Query Scheduling and Dynamic Risk Assessment for Live Migration of Services in Apache Spark‐Based Grid Environment

IET Blockchain, Volume 5, Issue 1, January/December 2025.
Grid computing is an emerging technology that enabled the heterogeneous collection of data and provisioning of services to the users. Due to the high amount of incoming heterogeneous request, grid computing needs an efficient scheduling to reduce execution time and satisfy service level agreement (SLA) and quality of service (QoS) requirements.
Gangasandra Mahadevaiah Kiran, Narasimaiah Nalini   +1 more
wiley   +1 more source