Proceedings ArticleDOI
Automated control of multiple virtualized resources
Pradeep Padala,Kai-Yuan Hou,Kang G. Shin,Xiaoyun Zhu,Mustafa Uysal,Zhikui Wang,Sharad Singhal,Arif Merchant +7 more
- pp 13-26
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TLDR
Experimental evaluation with RUBiS and TPC-W benchmarks along with production-trace-driven workloads indicates that AutoControl can detect and mitigate CPU and disk I/O bottlenecks that occur over time and across multiple nodes by allocating each resource accordingly.Abstract:
Virtualized data centers enable sharing of resources among hosted applications. However, it is difficult to satisfy service-level objectives(SLOs) of applications on shared infrastructure, as application workloads and resource consumption patterns change over time. In this paper, we present AutoControl, a resource control system that automatically adapts to dynamic workload changes to achieve application SLOs. AutoControl is a combination of an online model estimator and a novel multi-input, multi-output (MIMO) resource controller. The model estimator captures the complex relationship between application performance and resource allocations, while the MIMO controller allocates the right amount of multiple virtualized resources to achieve application SLOs. Our experimental evaluation with RUBiS and TPC-W benchmarks along with production-trace-driven workloads indicates that AutoControl can detect and mitigate CPU and disk I/O bottlenecks that occur over time and across multiple nodes by allocating each resource accordingly. We also show that AutoControl can be used to provide service differentiation according to the application priorities during resource contention.read more
Citations
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Journal ArticleDOI
Cloud computing: state-of-the-art and research challenges
Qi Zhang,Lu Cheng,Raouf Boutaba +2 more
TL;DR: A survey of cloud computing is presented, highlighting its key concepts, architectural principles, state-of-the-art implementation as well as research challenges to provide a better understanding of the design challenges of cloud Computing and identify important research directions in this increasingly important area.
Journal ArticleDOI
Dynamic Resource Allocation Using Virtual Machines for Cloud Computing Environment
Zhen Xiao,Weijia Song,Qi Chen +2 more
TL;DR: This paper presents a system that uses virtualization technology to allocate data center resources dynamically based on application demands and support green computing by optimizing the number of servers in use and develops a set of heuristics that prevent overload in the system effectively while saving energy used.
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.
Proceedings ArticleDOI
CloudScale: elastic resource scaling for multi-tenant cloud systems
TL;DR: CloudScale is a system that automates fine-grained elastic resource scaling for multi-tenant cloud computing infrastructures that can achieve significantly higher SLO conformance than other alternatives with low resource and energy cost.
Proceedings ArticleDOI
Q-clouds: managing performance interference effects for QoS-aware clouds
TL;DR: Q-Clouds, a QoS-aware control framework that tunes resource allocations to mitigate performance interference effects, is developed, which uses online feedback to build a multi-input multi-output (MIMO) model that captures performance interference interactions, and uses it to perform closed loop resource management.
References
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Journal ArticleDOI
Xen and the art of virtualization
Paul Barham,Boris Dragovic,Keir Fraser,Steven Hand,Tim Harris,Alex Ho,Rolf Neugebauer,Ian Pratt,Andrew Warfield +8 more
TL;DR: Xen, an x86 virtual machine monitor which allows multiple commodity operating systems to share conventional hardware in a safe and resource managed fashion, but without sacrificing either performance or functionality, considerably outperform competing commercial and freely available solutions.
Book
Adaptive Control
TL;DR: Benefiting from the feedback of users who are familiar with the first edition, the material has been reorganized and rewritten, giving a more balanced and teachable presentation of fundamentals and applications.
Proceedings ArticleDOI
Live migration of virtual machines
Christopher Clark,Keir Fraser,Steven Hand,Jacob Gorm Hansen,Eric Jul,Christian Limpach,Ian Pratt,Andrew Warfield +7 more
TL;DR: The design options for migrating OSes running services with liveness constraints are considered, the concept of writable working set is introduced, and the design, implementation and evaluation of high-performance OS migration built on top of the Xen VMM are presented.
Journal ArticleDOI
Memory resource management in VMware ESX server
TL;DR: Several novel ESX Server mechanisms and policies for managing memory are introduced, including a ballooning technique that reclaims the pages considered least valuable by the operating system running in a virtual machine, and an idle memory tax that achieves efficient memory utilization.
Proceedings ArticleDOI
Managing energy and server resources in hosting centers
TL;DR: Experimental results from a prototype confirm that the system adapts to offered load and resource availability, and can reduce server energy usage by 29% or more for a typical Web workload.