20-11-2012, 12:13 PM
Cloud Computing: Concepts, Technologies and Business Implications
Cloud Computing Concepts,.ppt (Size: 2.21 MB / Downloads: 558)
Speakers’ Background in cloud computing
Bina:
Has two current NSF (National Science Foundation of USA) awards related to cloud computing:
2009-2012: Data-Intensive computing education: CCLI Phase 2: $250K
2010-2012: Cloud-enabled Evolutionary Genetics Testbed: OCI-CI-TEAM: $250K
Faculty at the CSE department at University at Buffalo.
Kumar:
Principal Consultant at CTG
Currently heading a large semantic technology business initiative that leverages cloud computing
Adjunct Professor at School of Management, University at Buffalo.
Challenges
Alignment with the needs of the business / user / non-computer specialists / community and society
Need to address the scalability issue: large scale data, high performance computing, automation, response time, rapid prototyping, and rapid time to production
Need to effectively address (i) ever shortening cycle of obsolescence, (ii) heterogeneity and (iii) rapid changes in requirements
Transform data from diverse sources into intelligence and deliver intelligence to right people/user/systems
What about providing all this in a cost-effective manner?
Enter the cloud
Cloud computing is Internet-based computing, whereby shared resources, software and information are provided to computers and other devices on-demand, like the electricity grid.
The cloud computing is a culmination of numerous attempts at large scale computing with seamless access to virtually limitless resources.
on-demand computing, utility computing, ubiquitous computing, autonomic computing, platform computing, edge computing, elastic computing, grid computing, …
It is a changed world now…
Explosive growth in applications: biomedical informatics, space exploration, business analytics, web 2.0 social networking: YouTube, Facebook
Extreme scale content generation: e-science and e-business data deluge
Extraordinary rate of digital content consumption: digital gluttony: Apple iPhone, iPad, Amazon Kindle
Exponential growth in compute capabilities: multi-core, storage, bandwidth, virtual machines (virtualization)
Very short cycle of obsolescence in technologies: Windows Vista Windows 7; Java versions; CC#; Phython
Newer architectures: web services, persistence models, distributed file systems/repositories (Google, Hadoop), multi-core, wireless and mobile
Diverse knowledge and skill levels of the workforce
You simply cannot manage this complex situation with your traditional IT infrastructure:
Windows Azure
Enterprise-level on-demand capacity builder
Fabric of cycles and storage available on-request for a cost
You have to use Azure API to work with the infrastructure offered by Microsoft
Significant features: web role, worker role , blob storage, table and drive-storage
Google App Engine
This is more a web interface for a development environment that offers a one stop facility for design, development and deployment Java and Python-based applications in Java, Go and Python.
Google offers the same reliability, availability and scalability at par with Google’s own applications
Interface is software programming based
Comprehensive programming platform irrespective of the size (small or large)
Signature features: templates and appspot, excellent monitoring and management console
Fault tolerance
Failure is the norm rather than exception
A HDFS instance may consist of thousands of server machines, each storing part of the file system’s data.
Since we have huge number of components and that each component has non-trivial probability of failure means that there is always some component that is non-functional.
Detection of faults and quick, automatic recovery from them is a core architectural goal of HDFS.