Algorithmic Aspects of Cloud Computing: 8th International Symposium, ALGOCLOUD 2023, Amsterdam, The Netherlands, September 5, 2023, Revised Selected Papers

by Ioannis Chatzigiannakis (Editor), Ioannis Karydis (Editor)

Overview

This book constitutes revised selected papers from the 8th International Symposium on Algorithmic Aspects of Cloud Computing, ALGOCLOUD 2023, held in Amsterdam, The Netherlands, on September 5, 2023.

The 13 full papers included in this book were carefully reviewed and selected from 24 submissions. They focus on algorithmic aspects of computing and data management in modern cloud-based systems interpreted broadly so as to include edge- and fog-based systems, cloudlets, cloud micro-services, virtualization environments, decentralized systems, as well as dynamic networks.

Product Details

ISBN-13:	9783031493607
Publisher:	Springer Nature Switzerland
Publication date:	12/13/2023
Series:	Lecture Notes in Computer Science , #14053
Edition description:	1st ed. 2024
Pages:	231
Product dimensions:	6.10(w) x 9.25(h) x (d)

Table of Contents

Planning workflow executions over the Edge-to-Cloud Continuum.- On-Field Leaf Infection Detection using the Cloud-Edge Continuum.- Application of Federated Learning techniques for arrhythmia classification using 12- lead ECG signals.- An Adaptive, Energy-Efficient DRL-based and MCMC-based Caching Strategy for IoT Systems.- Real-Time Leakage Zone Detection in Water Distribution Networks: A Machine Learning-based Stream Processing Algorithm.- Multi-agent reinforcement learning-based energy orchestrator for cyber-physical systems.- Clustering-based Numerosity Reduction for Cloud Workload Forecasting.- Algorithmic Aspects of Distributed Hash Tables on Cloud, Fog, and Edge Computing Applications: A Survey.- i-Deliver P&D Engine: A Decentralized Middleware for a Delivery-as-a-Service System.- Intent-based Allocation of Cloud Computing Resources Using Q-Learning.- A Double-decision Reinforcement Learning based Algorithm for Online Scheduling in Edge and Fog Computing.- Decentralized Algorithms for Efficient Energy Management over Cloud-Edge Infrastructures.