sla oriented resource provisioning for cloud computing
Download
Skip this Video
Download Presentation
SLA-Oriented Resource Provisioning for Cloud Computing

Loading in 2 Seconds...

play fullscreen
1 / 18

SLA-Oriented Resource Provisioning for Cloud Computing - PowerPoint PPT Presentation


  • 128 Views
  • Uploaded on

SLA-Oriented Resource Provisioning for Cloud Computing. Challenges, Architecture , and Solutions. Author. Content. Abstract Introduction Challenges and Requirements SLA-Oriented Cloud Computing Vision State-of-the-art System Architecture SLA Provisioning in Aneka

loader
I am the owner, or an agent authorized to act on behalf of the owner, of the copyrighted work described.
capcha
Download Presentation

PowerPoint Slideshow about ' SLA-Oriented Resource Provisioning for Cloud Computing' - jarah


An Image/Link below is provided (as is) to download presentation

Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.


- - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - -
Presentation Transcript
sla oriented resource provisioning for cloud computing

SLA-Oriented Resource Provisioning for Cloud Computing

Challenges, Architecture, and Solutions

content
Content
  • 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
Abstract
  • 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
Introduction
    • 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

  • New Computing Paradigms
    • Cloud Computing
    • Grid Computing
    • P2P Computing
    • Utility Computing
challenges and requirements 2
Challenges and Requirements - 2
  • 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
SLA-Oriented Cloud Computing Vision

The resource provisioning will be driven by market-oriented principles for efficient resource allocation depending on user QoS targets and workload demand patterns.

  • 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;
  • Incorporation of autonomic resource management models;
  • Leverage of Virtual Machine technology to dynamically assign resource shares;
  • Implementation of the developed resource management strategies and models into a real computing server;
state of the art
State-of-the-art
  • Traditional Resource Management Systems(Condor, LoadLeveler, Load Sharing Facility, Portable Batch System)
    • adopt system-centric resource allocation approaches that focus on optimizing overall cluster performance
      • Increase processor throughput and utilization for the cluster
      • Reduce the average waiting time and response time for jobs
    • 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)
    • Main goal is to provide automatic configuration and maintenance of the centers
  • Market-based resource management
    • Not considered and incorporated customer-driven service management, computational risk management, and autonomic resource management into market-driven resource management
system architecture
System Architecture

High-level system architectural framework

performance evaluation 1
Performance Evaluation - 1
  • Static resource
    • 1 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
  • Dynamic resources
    • m1.small Linux-based instances
performance evaluation 2
Performance Evaluation - 2
  • 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
Conclusions and Future Directions
  • The need for a deeper investigation in SLA-oriented 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
ad