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ALVEC: Auto-scaling by Lotka Volterra elastic cloud: A QoS aware non linear dynamical allocation model
- Source :
- Simulation Modelling Practice and Theory. 93:262-292
- Publication Year :
- 2019
- Publisher :
- Elsevier BV, 2019.
-
Abstract
- Measurement of the dynamic elasticity of resource allocation in cloud computing continues to be a relevant problem in the related literature. Yet, there is scant evidence on determining the dynamic scaling quotient in such operations. Elasticity is defined as the ability to adapt to the changing workloads by provisioning and de-provisioning of Cloud resources and scaling is essential for maintaining elasticity in resource allocation. We propose ALVEC, as a model of resource allocation in Cloud data centers (Sarkar et al. , 2016) [7] , [16] , to address dynamic allocation by auto-tuning the model parameters. The proposed model, governed by a coupled differential equation known as Lotka Volterra (LV), fares better for management of Service Level Agreement (SLA) and Quality of Services (QoS). We show evidence of true elasticity both in theoretical and numerical applications. Additionally, we show that ALVEC as an example of unsupervised resource allocation, is able to predict the future load and allocate virtual machines efficiently.
- Subjects :
- FOS: Computer and information sciences
0209 industrial biotechnology
Mathematical optimization
Computer science
Differential equation
Cloud computing
02 engineering and technology
computer.software_genre
Computer Science - Networking and Internet Architecture
Service-level agreement
020901 industrial engineering & automation
0202 electrical engineering, electronic engineering, information engineering
Scaling
Networking and Internet Architecture (cs.NI)
business.industry
Quality of service
020208 electrical & electronic engineering
Provisioning
Elasticity (cloud computing)
Computer Science - Distributed, Parallel, and Cluster Computing
Hardware and Architecture
Virtual machine
Modeling and Simulation
Distributed, Parallel, and Cluster Computing (cs.DC)
business
computer
Software
Subjects
Details
- ISSN :
- 1569190X
- Volume :
- 93
- Database :
- OpenAIRE
- Journal :
- Simulation Modelling Practice and Theory
- Accession number :
- edsair.doi.dedup.....7bbdf09854609d4cd1559287c612c951