Results 11 to 20 of about 8,251,079 (331)
Predictive auto-scaling with OpenStack Monasca [PDF]
Proceedings of the 14th IEEE/ACM International Conference on Utility and Cloud Computing, 2021 Cloud auto-scaling mechanisms are typically based on reactive automation rules that scale a cluster whenever some metric, e.g., the average CPU usage among instances, exceeds a predefined threshold. Tuning these rules becomes particularly cumbersome when
Cucinotta T. +4 more
core +8 more sources
2018 26th Euromicro International Conference on Parallel, Distributed and Network-based Processing (PDP), 2018 Today, auto-scaling solutions are still largely reactive and are based on the load measured on existing nodes nearing a threshold or traffic forecast information provided in advance of a scheduled event.
Caton, Simon +5 more
core +3 more sources
Towards Yo-Yo attack mitigation in cloud auto-scaling mechanism
Digital Communications and Networks, 2020 Cloud platforms could automatically scale underlying network resources up and down in response to changes in the traffic load. Such an auto-scaling mechanism can largely enhance the elasticity and scalability of cloud platforms. However, it may introduce
Xiaoqiong Xu, Hongfang Yu, Long Luo
exaly +3 more sources
Improved Q Network Auto-Scaling in Microservice Architecture
Applied Sciences, 2022 Microservice architecture has emerged as a powerful paradigm for cloud computing due to its high efficiency in infrastructure management as well as its capability of largescale user service.
Yeonggwang Kim +3 more
doaj +2 more sources
Auto-scaling LLM-based multi-agent systems through dynamic integration of agents [PDF]
Frontiers in Artificial IntelligenceIntroductionLarge Language Model-based Multi-Agent Systems (LLM-based MASs) represent a groundbreaking paradigm where diverse LLM-based agents collaborate, leveraging their unique capabilities to achieve shared objectives.
Ravindu Perera +3 more
doaj +2 more sources
Prediction-based auto-scaling of scientific workflows [PDF]
Proceedings of the 9th International Workshop on Middleware for Grids, Clouds and e-Science, 2011 In this paper we propose a novel method for auto-scaling data-centric workflow tasks. Scaling is achieved through a prediction mechanism where the input data load on each task within a workflow is used to compute the estimated task execution time ...
Reginald Cushing +7 more
core +4 more sources
SCAling: SLA-driven cloud auto-scaling
Proceedings of the 28th Annual ACM Symposium on Applied Computing, 2013 International audienceThis paper presents an implementation -driven by Service Level Agreement (SLA)- of Cloud auto-scaling based on demand. Simulation experiments indicate that our model successfully keeps the best trade-off between SaaS provider profit
Thomas Ledoux +3 more
core +3 more sources
Auto-Scaling Containerized Microservice Applications
, 2021 The microservices architecture is being increasingly used to build complex applications. Many such applications are customer-facing. Hence, they face workload fluctuations and need to respond to end user requests quickly in spite of such fluctuations ...
MirzaEbrahim Mostofi, Vahid
core +3 more sources
An adaptive auto-scaling framework for cloud resource provisioning
Future Generation Computer Systems, 2023 Spyridon Chouliaras +1 more
exaly +2 more sources
Chamulteon: Coordinated Auto-Scaling of Micro-Services
2019 IEEE 39th International Conference on Distributed Computing Systems (ICDCS), 2019 Nowadays, in order to keep track of the fast-changing requirements of Internet applications, auto-scaling is used as an essential mechanism for adapting the number of provisioned resources to the resource demand. The straightforward approach is to deploy
Samuel Kounev +20 more
core +5 more sources