Optimal cloud resource provisioning for auto-scaling enterprise applications

2018 ◽  
Vol 7 (2) ◽  
pp. 129
Author(s):  
Satish Narayana Srirama ◽  
Alireza Ostovar
Keyword(s):  
Resource Provisioning ◽  
Cloud Resource ◽  
Enterprise Applications ◽  
Auto Scaling

Optimizing the Performance of Containerized Cloud Software Systems Using Adaptive PID Controllers

2021 ◽  
Vol 15 (3) ◽  
pp. 1-27
Author(s):  
Mikael Sabuhi ◽  
Nima Mahmoudi ◽  
Hamzeh Khazaei
Keyword(s):  
Adaptive Controller ◽  
Service Level ◽  
Resource Provisioning ◽  
Performance Model ◽  
Software Systems ◽  
Adaptive Controllers ◽  
Efficient Resource ◽  
Reliable Performance ◽  
Auto Scaling ◽  
Compare And Contrast

Control theory has proven to be a practical approach for the design and implementation of controllers, which does not inherit the problems of non-control theoretic controllers due to its strong mathematical background. State-of-the-art auto-scaling controllers suffer from one or more of the following limitations: (1) lack of a reliable performance model, (2) using a performance model with low scalability, tractability, or fidelity, (3) being application- or architecture-specific leading to low extendability, and (4) no guarantee on their efficiency. Consequently, in this article, we strive to mitigate these problems by leveraging an adaptive controller, which is composed of a neural network as the performance model and a Proportional-Integral-Derivative (PID) controller as the scaling engine. More specifically, we design, implement, and analyze different flavours of these adaptive and non-adaptive controllers, and we compare and contrast them against each other to find the most suitable one for managing containerized cloud software systems at runtime. The controller’s objective is to maintain the response time of the controlled software system in a pre-defined range, and meeting the Service-level Agreements, while leading to efficient resource provisioning.

Online Cloud Resource Provisioning Under Cost Budget for QoS Maximization

2021 ◽  
Author(s):  
Yu Liu ◽  
Niangjun Chen ◽  
Zhenhua Liu ◽  
Yuanyuan Yang
Keyword(s):  
Resource Provisioning ◽  
Cloud Resource

Autonomic cloud resource provisioning and scheduling using meta-heuristic algorithm

2020 ◽  
Vol 32 (24) ◽  
pp. 18285-18303 ◽  
Author(s):  
Mohit Kumar ◽  
S. C. Sharma ◽  
Shalini Goel ◽  
Sambit Kumar Mishra ◽  
Akhtar Husain
Keyword(s):  
Heuristic Algorithm ◽  
Resource Provisioning ◽  
Cloud Resource
Sign in / Sign up

Export Citation Format

Share Document