Proceedings ArticleDOI
Optimizing the utilization of virtual resources in Cloud environment
Sunirmal Khatua,Anirban Ghosh,Nandini Mukherjee +2 more
- pp 82-87
TLDR
The proposed architecture, named as Monitoring & Optimizing Virtual Resources (MOVR) architecture, manages and optimizes the usage of the resources required by a cloud application considering auto deployment, auto scaling and auto recovery of the provisioned resources for the application.Abstract:
One of the key factors behind successful deployment of Cloud for on demand services is the optimal utilization of its virtual resources. A poorly managed cloud application may lead to huge cost which is even more than the cost of physical deployment. The most important issues in Cloud are the scalability and availability. A highly scalable deployment may lead to poor resource utilization whereas a low scalable deployment may lead to unavailability of services. This paper proposes architecture for optimal utilization of such resources considering both scalability and availability. The proposed architecture, named as Monitoring & Optimizing Virtual Resources (MOVR) architecture, manages and optimizes the usage of the resources required by a cloud application considering auto deployment, auto scaling and auto recovery of the provisioned resources for the application.read more
Citations
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Journal ArticleDOI
A Review of Auto-scaling Techniques for Elastic Applications in Cloud Environments
TL;DR: This work proposes a classification of techniques for automating application scaling in the cloud into five main categories: static threshold-based rules, control theory, reinforcement learning, queuing theory and time series analysis, and uses this classification to carry out a literature review of proposals.
Journal ArticleDOI
Elasticity in Cloud Computing: State of the Art and Research Challenges
TL;DR: This article provides an overview of containerization, a new technological trend in lightweight virtualization, and provides a taxonomy of elasticity mechanisms according to the identified works and key properties.
Auto-scaling Techniques for Elastic Applications in Cloud Environments
TL;DR: In this article, a classification of techniques for automating application scaling in the cloud is proposed, including static threshold-based rules, control theory, reinforcement learning, queuing theory and time series analysis.
Journal ArticleDOI
Cloud Infrastructure Resource Allocation for Big Data Applications
TL;DR: This paper presents a multi-objective optimization algorithm to trade off the performance, availability, and cost of Big Data application running on Cloud, and designs and implements this approach on experimental environment.
Proceedings ArticleDOI
Cost Minimization for Provisioning Virtual Servers in Amazon Elastic Compute Cloud
TL;DR: Two virtual server provisioning algorithms are proposed to minimize the provisioning cost for long- and short-term planning using Stochastic programming, robust optimization, and sample-average approximation to obtain the optimal solutions of the algorithms.
References
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Posted Content
Modeling and Simulation of Scalable Cloud Computing Environments and the CloudSim Toolkit: Challenges and Opportunities
TL;DR: This paper proposes CloudSim: an extensible simulation toolkit that enables modelling and simulation of Cloud computing environments and allows simulation of multiple Data Centers to enable a study on federation and associated policies for migration of VMs for reliability and automatic scaling of applications.