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Cloud Computing: The Next Revolution in Information Technology

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Title: Cloud Computing: The Next Revolution in Information Technology


1
Cloud Computing The Next Revolution in
Information Technology
2
Cloud Computing The Next Revolution in
Information Technology
  • Dr. Suraj Pandey and Dr. Christian Vecchiola

Cloud Computing and Distributed Systems (CLOUDS)
Lab Dept. of Computer Science and Software
Engineering The University of Melbourne,
Australia www.cloudbus.org www.buyya.com www.manjr
asoft.com
Major Sponsors/Supporters
3
The CLOUDS Lab _at_ Melbourne
Education
R D
  • Part of a World-class Melbourne University
  • Rated as 1 in Australia (Times Higher Education)
  • Often rated amongst the top 20 or 30 in the
    world.
  • Youngest and one of the rapidly growing research
    labs in the University
  • Founded in 2002 (formerly, GRIDS Lab)
  • Houses 20 researchers consisting of
  • Research Fellows/PostDocs
  • Software Engineers
  • PhD candidates
  • Funding
  • Australian Research Council DIISR
  • Many industries (Sun, IBM, Microsoft, CA)
  • Many national and international collaborations.
  • Academics - Science, Engineering, Medicine
  • Industries
  • Software
  • Used in over 40 countries by academic and
    industrial users.
  • Publication
  • Produces over 20 of our Depts output.

Community Services e.g., IEEE TC for Scalable
Computing
4
www.manjrasoft.com
5
Books at Glance Co-authored/edited
6
Cloud Compting
7
Overall Agenda
Introduction to Recent Advances in Parallel and Distributed Computing
Introduction to Cloud computing
Cloud Computing with Manjrasoft Aneka
Building Enterprise Cloud, Applications and Teaching Cloud/Grid/Distributed Computing
Discussion and QA
8
Drivers for New Advances in Parallel/Distributed
Computing Resource Hungry Applications
  • Solving grand challenge applications using
    modeling, simulation and analysis

Aerospace
Internet Ecommerce
Life Sciences
CAD/CAM
Digital Biology
Military Applications
Military Applications
Military Applications
9
How to Run Applications Faster ?
  • There are 3 ways to improve performance
  • Work Harder
  • Work Smarter
  • Get Help
  • Computer Analogy
  • Build faster hardware
  • Develop Optimized algorithms and techniques used
    to solve computational tasks
  • Utilise multiple computers to solve a particular
    task

10
Computational Power Improvement (Horizontal
integration)
Multiprocessor
Uniprocessor
C.P.I
1 2 . . . .
No. of Processors
11
Computing is Scaling Towards
Inter-Planetary Level
S E R V I C E S PERFORMANCE
Administrative Barriers
  • Individual
  • Group
  • Department
  • Campus
  • State
  • National
  • Globe
  • Inter Planet
  • Universe

Personal Device
SMPs or SuperComputers
Local Cluster
Global Grid/InterCloud
Inter Planet Grid
Compute Cloud
12
New IT Trends
  • Ownership -gt Leasing Model
  • Infrastructure, platform, applications
  • PC -gt Internet Data Center
  • Building applications for a single user ? large
    number of concurrent consumers
  • Web 2.0 Virtualisation
  • Building 3rd party IT services by composing
    multiple independent services

13
Cloud Computing The Next Revolution in
Information Technology
14
The Next Revolution in IT The Big Switch in IT
  • Classical Computing
  • Buy Own
  • Hardware, System Software, Applications often to
    meet peak needs.
  • Install, Configure, Test, Verify, Evaluate
  • Manage
  • ..
  • Finally, use it
  • ....(High CapEx)
  • Cloud Computing
  • Subscribe
  • Use
  • - pay for what you use, based on QoS

15
Outline
  • Computer Utilities
  • Vision and Promising IT Paradigms/Platforms
  • Cloud Computing and Related Paradigms
  • Trends, Definition, Cloud Benefits and Challenges
  • Market-Oriented Cloud Architecture
  • SLA-oriented Resource Allocation
  • Global Cloud Exchange
  • Emerging Cloud Platforms
  • Cloudbus Melbourne Cloud Computing Initiative
  • Summary and Thoughts for Future

16
4 Essential Utilities and Delivery Networks
17
Computing Paradigms and Attributes Realizing the
Computer Utilities Vision
?
  • Web
  • Data Centres
  • Utility Computing
  • Service Computing
  • Grid Computing
  • P2P Computing
  • Market-Oriented Computing
  • Cloud Computing

  • -Ubiquitous -Reliable
  • Scalable
  • Autonomic
  • Dynamic discovery
  • Composable
  • -QoS
  • -SLA
  • -
  • Trillion business

Paradigms
Attributes/Capabilities
18
Outline
  • Computer Utilities
  • Vision and Promising IT Paradigms/Platforms
  • Cloud Computing and Related Paradigms
  • Trends, Definition, Cloud Benefits and Challenges
  • Market-Oriented Cloud Architecture
  • SLA-oriented Resource Allocation
  • Global Cloud Exchange
  • Emerging Cloud Platforms
  • Cloudbus Melbourne Cloud Computing Initiative
  • Summary and Thoughts for Future

19
Defining Clouds There are many views for what is
cloud computing?
  • Over 20 definitions
  • http//cloudcomputing.sys-con.com/read/612375_p.ht
    m
  • Renting remote storage ? backup
  • Renting remote server ? hosting Web server
  • Renting remote more servers ? to manage large
    workload
  • Buyyas Scientific definition of Cloud Computing
    ?
  • Cloud is a market-oriented distributed computing
    system consisting of a collection of
    inter-connected and virtualised computers that
    are dynamically provisioned and presented as one
    or more unified computing resources based on
    service-level agreements (SLA) established
    through negotiation between the service provider
    and consumers.
  • SLA negotiated and agreed QoS parameters
    rewards penalties for violation of
    agreement....

20
Subscription Oriented Cloud Services Xcompute,
apps, data, .. as a Service (..aaS)
Clients
Other Cloud Services
Govt. Cloud Services
21
Cloud Services
  • Infrastructure as a Service (IaaS)
  • CPU, Storage Amazon.com, Nirvanix, GoGrid.
  • Platform as a Service (PaaS)
  • Google App Engine, Microsoft Azure, Manjrasoft
    Aneka..
  • Software as a Service (SaaS)
  • SalesForce.Com

Software as a Service (SaaS)
Platform as a Service (PaaS)
Infrastructure as a Service (IaaS)
....
22
Cloud Deployment Models
23
Cloud Applications
  • Scientific/Tech Applications
  • Business Applications
  • Consumer/Social Applications

Science and Technical Applications
Business Applications
Consumer/Social Applications
24
(Promised) Benefits of (Public) Clouds
  • No upfront infrastructure investment
  • No procuring hardware, setup, hosting, power,
    etc..
  • On demand access
  • Lease what you need and when you need..
  • Efficient Resource Allocation
  • Globally shared infrastructure, can always be
    kept busy by serving users from different time
    zones/regions...
  • Nice Pricing
  • Based on Usage, QoS, Supply and Demand, Loyalty,
  • Application Acceleration
  • Parallelism for large-scale data analysis,
    what-if scenarios studies
  • Highly Availability, Scalable, and Energy
    Efficient
  • Supports Creation of 3rd Party Services
    Seamless offering
  • Builds on infrastructure and follows similar
    Business model as Cloud

25
Outline
  • Computer Utilities
  • Vision and Promising IT Paradigms/Platforms
  • Cloud Computing and Related Paradigms
  • Trends, Definition, Cloud Benefits and Challenges
  • Market-Oriented Cloud Architecture
  • SLA-oriented Resource Allocation
  • Global Cloud Exchange
  • Emerging Cloud Platforms
  • Cloudbus Melbourne Cloud Computing Initiative
  • Summary and Thoughts for Future

26
Cloud to expand/shrink leasing of resources with
QoS/demand variation
27
Cloud to expand (lease more resources) with
increase in demand
28
Cloud to shrink (unlease resources) with decrease
in demand
29
A (Layered) Cloud Architecture
Cloud applications Social computing, Enterprise,
ISV, Scientific, CDNs, ...
User level
Cloud programming environments and tools Web 2.0
Interfaces, Mashups, Concurrent and Distributed
Programming, Workflows, Libraries, Scripting
User-Level Middleware
Apps Hosting Platforms
QoS Negotiation, Admission Control, Pricing, SLA
Management, Monitoring, Execution Management,
Metering, Accounting, Billing
Autonomic / Cloud Economy
Adaptive Management
Core Middleware
Virtual Machine (VM), VM Management and
Deployment
Cloud resources
System level
30
Outline
  • 21st Century Vision of Computing
  • Promising Computing Paradigms
  • Cloud Computing and Related Paradigms
  • Trends, Definition, Characteristics, Architecture
  • Market-Oriented Cloud Architecture
  • SLA-oriented Resource Allocation
  • Global Cloud Exchange
  • Emerging Cloud Platforms
  • Cloudbus Melbourne Cloud Computing Initiative
  • Summary and Thoughts for Future

31
Some Commercial-Oriented Cloud platforms/technolog
ies
System Property Amazon EC2 S3 Google App Engine Microsoft Azure Manjrasoft Aneka
Focus IaaS IaaS/PaaS IaaS/PaaS PaaS
Service Type Compute (EC2), Storage (S3) Web apps Web and non-web apps Compute/Data
Virtualisation OS Level Xen Apps container OS level/Hyper-V Resource Manager and Scheduler
Dynamic Negotiation of QoS None None None SLA-oriented/ Resource Reservation
User Access Interface EC2 Command-line Tools Web-based Administration Console Windows Azure portal Workbench, Tools
Web APIs Yes Yes Yes Yes
Value-added Service Providers Yes No Yes No
Programming Framework Amazon Machine Image (AMI) Python .NET framework Multiple App models in.NET languages
32
Outline
  • Computer Utilities
  • Vision and Promising IT Paradigms/Platforms
  • Cloud Computing and Related Paradigms
  • Trends, Definition, Cloud Benefits and Challenges
  • Market-Oriented Cloud Architecture
  • SLA-oriented Resource Allocation
  • Global Cloud Exchange
  • Emerging Cloud Platforms
  • Cloudbus Melbourne Cloud Computing Initiative
  • Summary and Thoughts for Future

33
Cloudbus_at_CLOUDS Lab Melbourne Cloud Computing
Initiative
  • Market-Oriented Clouds
  • SLA-based Resource Management
  • Global Cloud Exchange Elements Brokers
  • Aneka .NET-based Cloud Computing
  • PaaS for Enterprise and Public Clouds
  • Scaling Across Clouds (Meta Brokering)
    Harnessing Compute resources
  • Federation of clouds for application scaling
    across distributed resources
  • 3rd Party Cloud Services (e.g., MetaCDN)
    Harnessing Storage resources
  • Building Content Delivery Networks using
    different vendors Storage Clouds
  • Green Clouds / Data Centers
  • Energy Efficiency and QoS Oriented Resource
    Allocation
  • CloudSim Toolkit for Simulation of Clouds
  • Design and evaluation for resource management
    policies algorithms

34
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35
Innovative Solutions for Simplifying and
Accelerating Applications in .NET-based Cloud
Computing Environments
36
Aneka and Hour Glass Model (many in one, one in
many)
multiple applications
multiple applications
Thread
Task
...
MapReduce
TCP/IP
Aneka
Multi-core
Cluster
Grid
Cloud
multiple networks
Internet Architecture
Aneka Architecture
37
Aneka as Cloud Platform
38
Aneka components
public DumbTask ITask public void
Execute()
Aneka enterprise Cloud
for(int i0 iltn i) DumbTask task
new DumbTask() app.SubmitExecution(task)
work units
internet
work units
Aneka Worker Service
Aneka Manager
internet
Aneka User Agent
39
Aneka Virtual Resource Pools Integration
  • XenServer Pool
  • Provisioning over private Cloud managed by Xen
    Server
  • VMWare Pool
  • Provisioning over private Cloud managed by VMWare
  • Amazon EC2 Pool
  • Provisioning over public Cloud provider Amazon
    EC2

Executors
private enterprise network
internet
publicly available resources (physical and
virtual)
Private Cloud
VPN (virtual resources)
Executors/Schedulers
Client Libraries
Public Cloud
40
Aneka Case Studies
41
(GoFront A unit of China Southern Railway Group)
Application Locomotive design CAD rendering
42
A scalable architecture for TitanStrike on-line
Gaming Portal
43
Demo Time
44
Using Aneka in Teaching and Research
45
Teaching Tools
  • Theory
  • Use an introductory parallel/distributed
    computing book to teach concepts..
  • Labs/Hands on Experience on Aneka Platform
  • Use Aneka to setup on enterprise cloud/grid using
    Aneka
  • Teach parallel/distributed application
    programming
  • Give assignment to students to write
    parallel/distributed programs using Aneka
  • Encourage students to conduct speedup analysis

46
Large Projects / Research Exploration
  • Encourage students to write applications
  • Parallel data mining
  • Parallel searching
  • Parallel sorting
  • Mass document searching
  • Image processing..
  • Science, Engineering, Medical applicatiions
  • Aneka can be use for
  • Parallel programming models research
  • Scheduling algorithms research
  • SLA-oriented resource allocation research
  • Reconfigurable software systems research
  • .

47
Development of Your Own Model
  • Extensibility Implement your own model!
  • Defines the user abstractions
  • Provide an implementation for..
  • Execution Service (middleware)
  • Scheduling Service (middleware)
  • Application Manager (client component)
  • Where to start
  • Aneka.Entity., Aneka.Data.Entity
  • Aneka.Execution.
  • Aneka.Runtime.Scheduling.

48
Early Customers/Users
  • China Southern Railways, China
  • Engineering applications
  • Titan Gaming Inc, USA
  • Scalable gaming applications
  • C-DAC (Hyderabad), India
  • Research and Education Activities
  • Vel Tech University
  • A autonomous institute in Chennai, India
  • M S Ramaiah Institute of Technology
  • A autonomous institute in Bangalore, India
  • MAM College of Engineering
  • Affiliated with Anna University, Tirchi, India

49
Manjrasofts Solutions Procurement Usage
  • Evaluation version available for Download
  • Software www.manjrasoft.com
  • Manual Setting up Clouds using your LAN-network
    computers
  • Teaching material
  • parallel and distributed computing and
    programming.
  • List of possible assignments for students.
  • Possible Projects for Final year students.
  • Full software can be procured from Manjrasoft
  • Comes with documentation (some teaching
    material) and support with guidance on setting
    up a lab (charged at 1/3rd of enterprise license
    price).
  • Applications
  • Other Departments (Physics, Chemistry, Biology,
    Finance, Engineering) can use it for their
    applications.

50
Outline
  • Computer Utilities
  • Vision and Promising IT Paradigms/Platforms
  • Cloud Computing and Related Paradigms
  • Trends, Definition, Cloud Benefits and Challenges
  • Market-Oriented Cloud Architecture
  • SLA-oriented Resource Allocation
  • Global Cloud Exchange
  • Emerging Cloud Platforms
  • Cloudbus Melbourne Cloud Computing Project
  • Summary and Thoughts for Future

51
Summary
  • Recent advances have made, Parallel and
    Distributed Computing gain first class status in
    IT field.
  • All computers including laptops and desktops will
    have multiple CPUs.
  • Parallel processing become a RULE (no more
    optional)
  • Network-based Parallel Distributed Computing
    technologies such as Aneka offer low-cost
    solution for teaching and learning this field.

52
Summary
  • Several Computing Paradigms have promised to
    deliver Computing Utilities vision
  • Cloud Computing is the most recent kid in the
    block promising to turn vision into reality
  • Many exciting business and consumer applications
    enabled.
  • Aneka is rapidly emerging as a platform for
  • Building Clouds (especially private) and their
    apps.
  • Accelerating Applications and Managing their
    execution.
  • Already used in engineering, life science,
    gaming, and business intelligence applications.

53
Convergence of Competing Paradigms/Communities
Needed
?
  • Web
  • Data Centres
  • Utility Computing
  • Service Computing
  • Grid Computing
  • P2P Computing
  • Cloud Computing
  • Market-Oriented Computing

  • Ubiquitous access
  • Reliability
  • Scalability
  • Autonomic
  • Dynamic discovery
  • Composability
  • QoS
  • SLA
  • Trillion business
  • Who will own it?

Paradigms
Attributes/Capabilities
54
References
  • Blueprint Paper!
  • R. Buyya, C. S. Yeo, S. Venugopal, J. Broberg, I.
    Brandic, Cloud Computing and Emerging IT
    Platforms Vision, Hype, and Reality for
    Delivering Computing as the 5th Utility, Future
    Generation Computer Systems (FGCS) Journal, June
    2009.
  • R. Buyya, S. Pandey, C. Vecchiola, Cloudbus
    Toolkit for Market-Oriented Cloud Computing,
    Proceedings of the 1st International Conference
    on Cloud Computing (CloudCom 2009), Beijing,
    China, Dec. 1-4, 2009.
  • Aneka
  • C. Vecchiola, X. Chu, and R. Buyya, Aneka A
    Software Platform for .NET-based Cloud Computing,
    High Speed and Large Scale Scientific Computing,
    267-295pp, IOS Press, Amsterdam, Netherlands,
    2009.

Wiley Press, New York, USA, March 2011
55
Thanks for your attention!
  • Are there any
  • Questions?
  • Comments/Suggestions

We welcome you to Study/Research with Us Do
Business with us! http/www.cloudbus.org
www.Manjrasoft.com rbuyya_at_unimelb.edu.au
raj_at_manjrasoft.com
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