Applying Machine Learning on Big Data With Apache Spark by Elias Dritsas, Maria Trigka

“…Our findings indicate that Apache Spark’s in-memory processing and distributed computing capabilities provide effective scalability, allowing these models to handle large-scale data with linear increases in processing time. …”
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Leveraging Deep Learning for Fault Detection and Localization in Distributed Systems by Debolina Ghosh, Jay Prakash Singh

“…These contributions provide useful information for implementing accurate and scalable fault localization in distributed computing environments found in the real world.…”
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A Novel Orchestrator Architecture for Deploying Virtualized Services in Next-Generation IoT Computing Ecosystems by Francisco Mahedero Biot, Alejandro Fornes-Leal, Rafael Vaño, Raúl Reinosa Simón, Ignacio Lacalle, Carlos Guardiola, Carlos E. Palau

“…This paper introduces an orchestrator architecture for dynamic IoT scenarios, inspired by ETSI NFV MANO and Cloud Native principles, where distributed computing nodes often have unfixed and changing networking configurations. …”
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Reputation-Based Leader Selection Consensus Algorithm with Rewards for Blockchain Technology by Munir Hussain, Amjad Mehmood, Muhammad Altaf Khan, Rabia Khan, Jaime Lloret

“…It has several practical applications such as distributed computing, load balancing, and blockchain transaction validation. …”
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Analog and digital systems and high-performance solutions in problems of brain research and modeling by N. I. Ananyeva, A. V. Bogdanov, D. E. Gushchanskiy, A. B. Degtyarev, N. M. Zalutskaya, K. A. Lysov, N. G. Neznanov, O. O. Iakushkin

“…For each of them we survey existing options for creating cloud-based distributed computing solutions that can solve important challenges faced by researchers in their work.…”
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Dynamic scheduling strategies for cloud-based load balancing in parallel and distributed systems by Nasser S. Albalawi

“…The Harmony Search Algorithm with Linear Regression (LR-HSA) is then used to do Distributed Computing-based Load Prediction and Adjustment. …”
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An Analytical Framework for Optimizing the Renewable Energy Dimensioning of Green IoT Systems in Pipeline Monitoring by Godlove Suila Kuaban, Valery Nkemeni, Piotr Czekalski

“…We propose a hybrid approach combining solar energy harvesting with energy-saving strategies such as adaptive sensing, duty cycling, and distributed computing to extend the lifetime of IoT nodes without human intervention. …”
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Deep learning-based ensemble stacking for enhanced intrusion detection in IoT-edge platforms by P. R. Chithra Rani, K. Baalaji

“…This research contributes a scalable, efficient, and resource-aware intrusion-detection approach to extending the resilience of IoT-edge systems in distributed computing environments.…”
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Multi-gate neuron-like transistors based on ensembles of aligned nanowires on flexible substrates by João Neto, Abhishek Singh Dahiya, Ravinder Dahiya

“…The temporal and spatial summation functions, demonstrated by the v-FET presented here, could open interesting new avenues for development of neuromorphic electronic skin (v-skin) with possibility of biological-skin like distributed computing.…”
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When IEEE 802.11 and 5G Meet Time-Sensitive Networking by Mahin K. Atiq, Raheeb Muzaffar, Oscar Seijo, INaki Val, Hans-Peter Bernhard

“…Many emerging applications require a higher level of flexibility, modularity, and efficiency but are dependent on advancements in communication infrastructure and distributed computing. Time-sensitive networking (TSN) standards aim at providing vendor agnostic, reliable, and deterministic communications over the Ethernet, but lack in flexibility and modularity provisions. …”
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Federated services: smart service paradigm based on distributed data co-governance by JIA Xiaofeng, QIN Rui, WANG Shouwen, QI Hongwei, WANG Fei-Yue, LI Juanjuan, ZHANG Min, LIANG Xiaolong

“…On this basis, the paper proposes the key supporting technologies for federated services, including blockchain and decentralized autonomous organizations and operations, large language models and scenario engineering, distributed computing and edge computing, as well as encryption technology and privacy computing. …”
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A Survey on Software Defined Network-Enabled Edge Cloud Networks: Challenges and Future Research Directions by Baha Uddin Kazi, Md Kawsarul Islam, Muhammad Mahmudul Haque Siddiqui, Muhammad Jaseemuddin

“…To address these challenges, edge cloud-distributed computing networks emerge. Because of the distributed nature of edge cloud networks, many research works considering software defined networks (SDNs) and network–function–virtualization (NFV) could be key enablers for managing, orchestrating, and load balancing resources. …”
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Federated Learning-Driven IoT Request Scheduling for Fault Tolerance in Cloud Data Centers by Sheeja Rani S, Raafat Aburukba

“…Cloud computing is a virtualized and distributed computing model that provides resources and services based on demand and self-service. …”
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A demand-centered scheduling framework for shared supercomputing resources: modeling, metrics, and case insights by Hyungwook Shim

“…In response, many nations are exploring joint utilization systems to maximize resource efficiency by enabling the flexible allocation of distributed computing assets. This study proposes a novel dynamic scheduling framework designed to enhance demand-side management in such environments. …”
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Monitoring and Forecasting the Dynamics of the Incidence of COVID-19 in Moscow: 2020–2021 by A. V. Sokolov, L. A. Sokolova

“…The basis of the study is the balanced identification method and the information technology of the same name, created at the Center for Distributed Computing of the Institute for Information Transmission Problems of the Russian Academy of Sciences. …”
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PERFORMANCE REFINEMENT OF CONVOLUTIONAL NEURAL NETWORK ARCHITECTURES FOR SOLVING BIG DATA PROBLEMS by Saud Aljaloud

“…As the project description implied, this study would not present a standard comparison because of this; instead, it would present a comparison of these networks' performance in a Big Data environment using distributed computing. The FMNIST or Fashion MNIST database and CIFAR10 were also tested (using the same neural network design), extending the scope of the comparison beyond MNIST. …”
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Resource Adaptive Automated Task Scheduling Using Deep Deterministic Policy Gradient in Fog Computing by Prashanth Choppara, S. Sudheer Mangalampalli

“…This research demonstrates the transformative impact of deep reinforcement learning in improving task scheduling in distributed computing environments, laying a strong foundation for further research aimed at harnessing the full capabilities of fog computing for the ongoing demands of IoT applications.…”
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Is it possible to perform a comprehensive analysis of the diagnostic data of mental diseases in the early stages? by N. M. Zalutskaya, A. Eran, Sh. Freilikhman, R. Balicer, N. A. Gomzyakova, V. V. Korkhov, N. G. Neznanov, A. V. Bogdanov, A. B. Degtyarev

“…It is planned to use the new approach associated with the use of newSQL database as an API, and then use the distributed computing tools for working with heterogeneous data, which will lead to features in the analysis of correlations in multidimensional data arrays. …”
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Resource Management Techniques for the Internet of Things, Edge, and Fog Computing Environments by Koushik Chakraborty, Manmohan Sharma, Krishnaveni Kommuri, Voore Subrahmanyam, Pratap Patil, Manmohan Singh Yadav

“…A speculative exhibit for distributed computing organizations is implied as a haze of mists joining different parceled mists into a solitary fluid mass for on-request tasks. …”
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Population of computational rabbit-specific ventricular action potential models for investigating sources of variability in cellular repolarisation. by Philip Gemmell, Kevin Burrage, Blanca Rodriguez, T Alexander Quinn

“…This was accomplished with distributed computing software specialised for multi-dimensional parameter sweeps and grid execution. …”
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