Results 31 to 40 of about 2,055 (161)
Three Algorithms for Parallel Graph Summarization
Expert Systems, Volume 43, Issue 1, January 2026.ABSTRACT Most graph summarization algorithms are tailored to a specific graph summary model and were designed for one‐time computations only, that is, batch‐based computations. We developed a universal approach for parallel graph summarization and three algorithms to compute graph summaries—a batch‐based algorithm for static graphs, an incremental ...
Till Blume +3 more
wiley +1 more source
Pre-Processing and Modeling Tools for Bigdata
Foundations of Computing and Decision Sciences, 2016 Modeling tools and operators help the user / developer to identify the processing field on the top of the sequence and to send into the computing module only the data related to the requested result.
Hashem Hadi, Ranc Daniel
doaj +1 more source
Comparative Study Parallel Join Algorithms for MapReduce environment
Труды Института системного программирования РАН, 2018 There are the following techniques that are used to analyze massive amounts of data: MapReduce paradigm, parallel DBMSs, column-wise store, and various combinations of these approaches. We focus in a MapReduce environment.
A. Yu. Pigul
doaj +1 more source
Behavioral simulations in MapReduce [PDF]
Proceedings of the VLDB Endowment, 2010 In many scientific domains, researchers are turning to large-scale behavioral simulations to better understand real-world phenomena. While there has been a great deal of work on simulation tools from the high-performance computing community, behavioral simulations remain challenging to program and automatically scale in parallel environments.
Wang, Guozhang +7 more
openaire +2 more sources
Lightweight Deep Learning Approach for Intelligent Intrusion Detection in IoT Networks
International Journal of Distributed Sensor Networks, Volume 2026, Issue 1, 2026.Intrusion detection system (IDS) is designed to analyze and monitor the network traffic to identify unauthorized access or attacks in an Internet of Things (IoT). IDS assists in protecting IoT devices and networks by recognizing malicious activities and preventing potential breaches.
Srikanth Mudiyanuru Sriramappa +5 more
wiley +1 more source
e-Prime: Advances in Electrical Engineering, Electronics and EnergyA successful deployment of Industry 5.0 is significantly dependent on the synergetic integration of several advanced technologies such as big data processing, Artificial Intelligence (AI) integration, and several effective digitization techniques that ...
Arnab Mitra
doaj +1 more source
Canadian Journal of Statistics, Volume 53, Issue 4, December 2025.Abstract Modern longitudinal data from wearable devices consist of biological signals at high‐frequency time points. Distributed statistical methods have emerged as a powerful tool to overcome the computational burden of estimation and inference with large data, but methodology for distributed functional regression remains limited.
Cole Manschot, Emily C. Hector
wiley +1 more source
CES Transactions on Electrical Machines and Systems, 2019 Effective storage, processing and analyzing of power device condition monitoring data faces enormous challenges. A framework is proposed that can support both MapReduce and Graph for massive monitoring data analysis at the same time based on Aliyun ...
Hongtao Shen, Peng Tao, Pei Zhao, Hao Ma
doaj +1 more source
Hadoop MapReduce scheduling paradigms [PDF]
2017 IEEE 2nd International Conference on Cloud Computing and Big Data Analysis (ICCCBDA), 2017 Apache Hadoop is one of the most prominent and early technologies for handling big data. Different scheduling algorithms within the framework of Apache Hadoop were developed in the last decade. In this paper, we attempt to provide a comprehensive overview over the different paradigms for scheduling in Apache Hadoop.
Johannessen, Roger +2 more
openaire +2 more sources
A Systematic Overview of Caching Mechanisms to Improve Hadoop Performance
Concurrency and Computation: Practice and Experience, Volume 37, Issue 25-26, 30 November 2025.ABSTRACT In today's distributed computing environments, the rapid generation of large‐scale data from diverse sources poses significant challenges in terms of storage, management, and processing, particularly for traditional relational databases. Hadoop has emerged as a widely adopted framework for handling such data through parallel processing across ...
Rana Ghazali, Douglas G. Down
wiley +1 more source