Results 21 to 30 of about 20,635 (205)

DeepScaler: Holistic Autoscaling for Microservices Based on Spatiotemporal GNN with Adaptive Graph Learning [PDF]

open access: yesInternational Conference on Automated Software Engineering, 2023
Autoscaling functions provide the foundation for achieving elasticity in the modern cloud computing paradigm. It enables dynamic provisioning or de-provisioning resources for cloud software services and applications without human intervention to adapt to
Chunyang Meng   +4 more
semanticscholar   +1 more source

Data analysis using microservices to solve forecasting problem

open access: yesAdaptivni Sistemi Avtomatičnogo Upravlinnâ, 2021
This article discusses the solution to the issue of increasing the efficiency and reliability of data analysis systems with the involvement of microservices for solving forecasting problems.
O. Бондар   +1 more
doaj   +1 more source

Placement of Microservices-based IoT Applications in Fog Computing: A Taxonomy and Future Directions [PDF]

open access: yesACM Computing Surveys, 2022
The Fog computing paradigm utilises distributed, heterogeneous and resource-constrained devices at the edge of the network for efficient deployment of latency-critical and bandwidth-hungry IoT application services.
Samodha Pallewatta   +2 more
semanticscholar   +1 more source

Nightcore: efficient and scalable serverless computing for latency-sensitive, interactive microservices

open access: yesInternational Conference on Architectural Support for Programming Languages and Operating Systems, 2021
The microservice architecture is a popular software engineering approach for building flexible, large-scale online services. Serverless functions, or function as a service (FaaS), provide a simple programming model of stateless functions which are a ...
Zhipeng Jia, Emmett Witchel
semanticscholar   +1 more source

Dependable workflow management system for smart farms

open access: yesConnection Science, 2022
Smart Farming is a new and emerging domain representing the application of modern technologies into agriculture, leading to a revolution of this classic domain.
Catalin Negru   +7 more
doaj   +1 more source

Practice of Alibaba cloud on elastic resource provisioning for large‐scale microservices cluster [PDF]

open access: yesSoftware: Practice and Experience, 2023
Cloud‐native architecture is becoming increasingly crucial for today's cloud computing environments due to the need for speed and flexibility in developing applications.
Minxian Xu   +8 more
semanticscholar   +1 more source

An Attention Mechanism-Based Microservice Placement Scheme for On-Star Edge Computing Nodes

open access: yesIEEE Access, 2023
In the context of high-speed networks with 5G and 6G, the influx of user requests under variable usage scenarios puts great pressure on the monolithic architecture, and quality of service (QoS) is gradually not guaranteed.
Xiangyu Su   +5 more
doaj   +1 more source

MicroFog: A Framework for Scalable Placement of Microservices-based IoT Applications in Federated Fog Environments [PDF]

open access: yesJournal of Systems and Software, 2023
MicroService Architecture (MSA) is gaining rapid popularity for developing large-scale IoT applications for deployment within distributed and resource-constrained Fog computing environments.
Samodha Pallewatta   +2 more
semanticscholar   +1 more source

An Open-Source Benchmark Suite for Microservices and Their Hardware-Software Implications for Cloud & Edge Systems

open access: yesInternational Conference on Architectural Support for Programming Languages and Operating Systems, 2019
Cloud services have recently started undergoing a major shift from monolithic applications, to graphs of hundreds or thousands of loosely-coupled microservices.
Yu Gan   +23 more
semanticscholar   +1 more source

BARO: Robust Root Cause Analysis for Microservices via Multivariate Bayesian Online Change Point Detection [PDF]

open access: yesProc. ACM Softw. Eng.
Detecting failures and identifying their root causes promptly and accurately is crucial for ensuring the availability of microservice systems. A typical failure troubleshooting pipeline for microservices consists of two phases: anomaly detection and root
Luan Pham, Huong Ha, Hongyu Zhang
semanticscholar   +1 more source

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