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SLA-Oriented Resource Provisioning
for Cloud Computing
Challenges, Architecture, and Solutions
Author
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Content
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Abstract
Introduction
Challenges and Requirements
SLA-Oriented Cloud Computing Vision
State-of-the-art
System Architecture
SLA Provisioning in Aneka
Performance Evaluation
Future Directions
Abstract
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Need to offer differentiated services to users and meet
their quality expectations.
Existing resource management systems are yet to support
SLA-oriented resource allocation.
No work has been done to collectively incorporate
customer-driven service management, computational risk
management, and autonomic resource management into a
market-based resource management system to target the
rapidly changing enterprise requirements of Cloud
computing.
This paper presents vision, challenges, and architectural
elements of SLA-oriented resource management.
Introduction
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There are dramatic differences between developing
software for millions to use as a service versus
distributing software for millions to run their PCs
-- Professor David Patterson
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New Computing Paradigms
Cloud Computing
 Grid Computing
 P2P Computing
 Utility Computing
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Challenges and Requirements - 1
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Challenges and Requirements - 2
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Customer-driven Service Management
Computational Risk Management
Autonomic Resource Management
SLA-oriented Resource Allocation Through
Virtualization
Service Benchmarking and Measurement
System Modeling and Repeatable Evaluation
SLA-Oriented Cloud Computing Vision
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The resource provisioning will be driven by market-oriented
principles for efficient resource allocation depending on user QoS
targets and workload demand patterns.
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Support for customer-driven service management based on customer profiles and
QoS requirements;
Definition of computational risk management tactics to identify, assess, and manage
risks involved in the execution of applications;
Derivation of appropriate market-based resource management strategies that
encompass both customer-driven service management and computational risk
management to sustain SLA-oriented resource allocation;
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Incorporation of autonomic resource management models;
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Leverage of Virtual Machine technology to dynamically assign resource shares;
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Implementation of the developed resource management strategies and models into
a real computing server;
State-of-the-art
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Traditional Resource Management Systems(Condor,
LoadLeveler, Load Sharing Facility, Portable Batch System)
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adopt system-centric resource allocation approaches that focus on
optimizing overall cluster performance
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Assume that all job requests are of equal user importance and neglect
actual levels of service required by different users.
Virtual Machine management platform solutions(Eucalyptus,
OpenStack, Apache VCL, Citrix Essentials)
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Increase processor throughput and utilization for the cluster
Reduce the average waiting time and response time for jobs
Main goal is to provide automatic configuration and maintenance of the
centers
Market-based resource management
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Not considered and incorporated customer-driven service management,
System Architecture
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High-level system architectural framework
SLA Provisioning in Aneka -1
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Aneka architecture
SLA Provisioning in Aneka - 2
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SLA Provisioning in Aneka - 3
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SLA Provisioning in Aneka - 4
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Performance Evaluation - 1
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Static resource
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Aneka master - m1.large(7.5GB memory, 4 EC2
compute units, 850GB instance storage, 64bit platform,
US0.48 per instance per hour) Windows-based VM
 4 Aneka workers – m1.small(1.7GB memory, 1 EC2
compute unit, 160GB instance storage, 32bit platform,
US0.085 per instance per hour) Linux-based VM
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Dynamic resources
 m1.small
Linux-based instances
Performance Evaluation - 2
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CPU-intensive application
SLA is defined in terms of user-defined deadline
execution time of each task was set to 2 minutes
Each job consists of 120 tasks
Conclusions and Future Directions
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The need for a deeper investigation in SLAoriented resource allocation strategies that
encompass:
 Customer-driven
service management
 Computational risk management
 Autonomic management of Clouds
In order to:
 Improve
the system efficiency
 Minimize violation of SLAs
 Improve profitability of service providers
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Thanks !