Imagen de Portada

A Reinforced Evolution-Based Approach to Multi-Resource Load Balancing

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autor principal:	Sliwko, Leszek
Formato:	Preprint
Publicado:	2025
Materias:	Neural and Evolutionary Computing Artificial Intelligence Distributed, Parallel, and Cluster Computing
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

A Meta-Heuristic Load Balancer for Cloud Computing Systems
por: Sliwko, Leszek, et al.
Publicado: (2025)

Intelligent Load Balancing in Cloud Computer Systems
por: Sliwko, Leszek
Publicado: (2025)

EvoGit: Decentralized Code Evolution via Git-Based Multi-Agent Collaboration
por: Huang, Beichen, et al.
Publicado: (2025)

GAP2WSS: A Genetic Algorithm based on the Pareto Principle for Web Service Selection
por: Khatoonabadi, SayedHassan, et al.
Publicado: (2021)

HiAER-Spike: Hardware-Software Co-Design for Large-Scale Reconfigurable Event-Driven Neuromorphic Computing
por: Frank, Gwenevere, et al.
Publicado: (2025)

Distributed genetic algorithm for application placement in the compute continuum leveraging infrastructure nodes for optimization
por: Guerrero, Carlos, et al.
Publicado: (2024)

Trackable Agent-based Evolution Models at Wafer Scale
por: Moreno, Matthew Andres, et al.
Publicado: (2024)

Adaptive Domain Models: Bayesian Evolution, Warm Rotation, and Principled Training for Geometric and Neuromorphic AI
por: Haynes, Houston
Publicado: (2026)

Workload Schedulers -- Genesis, Algorithms and Differences
por: Sliwko, Leszek, et al.
Publicado: (2025)

A Fresh Approach to Evaluate Performance in Distributed Parallel Genetic Algorithms
por: Harada, Tomohiro, et al.
Publicado: (2021)

Cluster Workload Allocation: A Predictive Approach Leveraging Machine Learning Efficiency
por: Sliwko, Leszek
Publicado: (2025)

A Frequency-based Parent Selection for Reducing the Effect of Evaluation Time Bias in Asynchronous Parallel Multi-objective Evolutionary Algorithms
por: Harada, Tomohiro
Publicado: (2021)

AGOCS -- Accurate Google Cloud Simulator Framework
por: Sliwko, Leszek, et al.
Publicado: (2025)

Hopfield Networks Meet Big Data: A Brain-Inspired Deep Learning Framework for Semantic Data Linking
por: Kannan, Ashwin Viswanathan, et al.
Publicado: (2025)

Online Continual Learning on Intel Loihi 2 via a Co-designed Spiking Neural Network
por: Hajizada, Elvin, et al.
Publicado: (2025)

Edge Intelligence with Spiking Neural Networks
por: Deng, Shuiguang, et al.
Publicado: (2025)

STEMS: Spatial-Temporal Mapping For Spiking Neural Networks
por: Eissa, Sherif, et al.
Publicado: (2025)

Split Federated Learning Over Heterogeneous Edge Devices: Algorithm and Optimization
por: Sun, Yunrui, et al.
Publicado: (2024)

Comparison of Microservice Call Rate Predictions for Replication in the Cloud
por: Mehran, Narges, et al.
Publicado: (2023)

Cyclic Data Parallelism for Efficient Parallelism of Deep Neural Networks
por: Fournier, Louis, et al.
Publicado: (2024)

Neural Cellular Automata Can Respond to Signals
por: Stovold, James
Publicado: (2023)

Neuromorphic Simulation of Drosophila Melanogaster Brain Connectome on Loihi 2
por: Wang, Felix, et al.
Publicado: (2025)

Evaluation and Efficiency Comparison of Evolutionary Algorithms for Service Placement Optimization in Fog Architectures
por: Guerrero, Carlos, et al.
Publicado: (2025)

D-CODE: Data Colony Optimization for Dynamic Network Efficiency
por: Pandey, Tannu, et al.
Publicado: (2024)

Code generation and runtime techniques for enabling data-efficient deep learning training on GPUs
por: Wu, Kun
Publicado: (2024)

SSDTrain: An Activation Offloading Framework to SSDs for Faster Large Language Model Training
por: Wu, Kun, et al.
Publicado: (2024)

Reducing Data Bottlenecks in Distributed, Heterogeneous Neural Networks
por: Lin, Ruhai, et al.
Publicado: (2024)

Trackable Island-model Genetic Algorithms at Wafer Scale
por: Moreno, Matthew Andres, et al.
Publicado: (2024)

Sparse Spiking Neural-like Membrane Systems on Graphics Processing Units
por: Hernández-Tello, Javier, et al.
Publicado: (2024)

A Taxonomy of Schedulers -- Operating Systems, Clusters and Big Data Frameworks
por: Sliwko, Leszek
Publicado: (2025)

Hybrid Approach to Parallel Stochastic Gradient Descent
por: Vora, Aakash Sudhirbhai, et al.
Publicado: (2024)

HydroFusion-LMF: Semi-Supervised Multi-Network Fusion with Large-Model Adaptation for Long-Term Daily Runoff Forecasting
por: Fan, Qianfei, et al.
Publicado: (2025)

Differentiable Quantum Architecture Search in Asynchronous Quantum Reinforcement Learning
por: Chen, Samuel Yen-Chi
Publicado: (2024)

Asynchronous Evolution of Deep Neural Network Architectures
por: Liang, Jason, et al.
Publicado: (2023)

Enhancing Cluster Scheduling in HPC: A Continuous Transfer Learning for Real-Time Optimization
por: Sliwko, Leszek, et al.
Publicado: (2025)

Breaking the MoE LLM Trilemma: Dynamic Expert Clustering with Structured Compression
por: Zhu, Peijun, et al.
Publicado: (2025)

NeuroRing: Scaling Spiking Neural Networks via Multi-FPGA Bidirectional Ring Topologies and Stream-Dataflow Architectures
por: Hafiz, Muhammad Ihsan Al, et al.
Publicado: (2026)

A novel strategy for multi-resource load balancing in agent-based systems
por: Sliwko, Leszek, et al.
Publicado: (2025)

Bio-inspired Agentic Self-healing Framework for Resilient Distributed Computing Continuum Systems
por: Saleh, Alaa, et al.
Publicado: (2026)

Neuromorphic Programming: Emerging Directions for Brain-Inspired Hardware
por: Abreu, Steven, et al.
Publicado: (2024)