• Why Cloud Computing?

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Cloud Computing - Overview

-I-

“Alexandru Ioan Cuza” University of Iasi Faculty of Computer Science

Prof. Lenuța Alboaie [email protected]

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Content

• Why Cloud Computing?

• History & Evolution

• Grid/Cluster computing – general aspects

• Cloud Computing – definitions

• Grid versus Cloud

• Cloud Computing - aspects

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Cloud Computing

• Do you use Cloud Computing?

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Cloud Computing

• Cloud computing “in your pocket”?

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Why Cloud Computing?

• Understanding the basic principles

– How something scalable can be built?

– Various development environments

• What is behind a Cloud Platform?

– How does it work? Advantages? Disadvantages?

– Technologies: Web Services, SOA, Ajax, XML, NoSQL, MapReduce,….

• Would you like to build the ‘next’ Facebook?

– Scalability, efficiency, fault tolerance, security,…

• Knowing the impact on society – Vulnerabilities, security issues,

• Anticipating a possible future How do we reach Cloud Computing?

(Now)

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History & Evolution

• 1945-1985: “computers were large and expensive”

• … improvements:

Processors Memory Networking

Storage

Protocols

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History & Evolution

• Microprocessor industry (8-biti, 16,32,64,…) has evolved rapidly

• Computers have become – Smaller

– Cheaper – Faster

• “…from machine that cost 10 million dollars and executed 1 instruction per second (IPS) we have come to machines that cost 1000 dollars and are able to execute 1 billion instructions per second, a price/performance gain of 1013”

• “In 2019, Google announced that its Sycamore quantum computer had completed a task in 200 seconds that would take a conventional computer 10,000 years.”

– IBM's 127-qubit Eagle processor (Nov 2021)

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Year Cost ($/MB) Capacity (average)

1977 $32,000 16K

1987 $250 640K-2MB

1997 $2 64MB-256MB

2007 $0.06 512MB-2GB+

2014 $0.0091 8GB->…

2022 $0.000… 16Gb->

[http://www.cs.rutgers.edu/~pxk/]

History & Evolution

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• 1977: 310KB floppy drive ~ $1480

• 1987: 40 MB drive ~ $679

• 2008: 750 GB drive ~ $99

• 2022: 3-4TB drive ~ $100

• “Areal density is a measure of the quantity of information bits that can be stored on a given length of track, area of surface, or in a given volume of a computer storage

medium - TPI (tracks per inch) or bits per inch. ”

• “Recording density increased over 60,000,000 times over

History & Evolution

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1961-1972: first communication's attempts using packet-switching

• 1961: Kleinrock – proposed a theoretical model

• 1964: Baran – implemented the communication among US military computers

• 1967: ARPAnet was projected by Advanced Research Projects Agency

• 1969: first operational node ARPAnet, a network formed by 4 computers

• 1972:

• public demonstration of ARPAnet technologies

• NCP (Network Control Protocol) – the first host-host protocol

• First program for electronic mail (e-mail)

• The sign @ is introduced

• ARPAnet contains 15 nodes

History & Evolution

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• 1972-1980: The Internetworking concept appeared. Also, proprietary networks appeared.

• 1973: DARPA (Defense Advanced Research Projects Agency) – interconnected networks; Robert Metcalf (Hardvard) developed Ethernet technology that allowed data transfer using coaxial

cable

• 1974: Cerf and Kahn – proposed a communication protocol entitled TCP(Transmission Control Protocol)

• 1978: TCP/IP protocols stack was standardized via RFC (Request For Comments) documents

• In the late 70s: proprietary networks stacks appeared: DECnet, SNA, XNA

• 1979: ARPAnet contained 200 nodes

History & Evolution

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• 1980-1990: new protocols, the network number was increasing, Internet

• 1983: TCP/IP was used

• 1982: SMTP (Simple Mail Transfer Protocol) was defined

• 1983: DNS (translation of host name into IP address and vice versa) appeared

• 1985: FTP(File Transfer Protocol) protocol appeared

• 1986: Internet backbone appeared

• 1988: some congestion control mechanisms for TCP were introduced

History & Evolution

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LAN – speed:

– Original Ethernet: 2.94 Mbps

– 1985: thick Ethernet: 10 Mbps; 1 Mbps with twisted pair networking

– 1991: 10BaseT - twisted pair: 10 Mbps – 1995: 100 Mbps Ethernet

– 1998: 1 Gbps (Gigabit) Ethernet

– 1999: 802.11b (wireless Ethernet) standardized – 2001: 10 Gbps introduced

– 2005: 100 Gbps (over optical link) – 2022: … Gbps

History & Evolution

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History & Evolution

[https://worldpopulationreview.com/country-rankings/internet-speeds-by-country]

“According to internet speed specialists Ookla (https://www.speedtest.net/) the global average download speed on fixed broadband as of September 2021 was 113.25 Mbps on fixed broadband and 63.15 Mbps on mobile. These are both notable improvements over the scores of 85.73 Mbps broadband and 35.96 Mbps mobile just one year earlier in September 2020”

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History & Evolution

Figure. Hosts number form January 1994 till January 2019 Source: Feb 2020| https://www.isc.org/network/survey/

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Trends

* From supercomputers to workstations that can be connected together

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What means computing?

• Computing

• The way one thinks

In computer science?

• “we can define computing to mean any goal-

oriented activity requiring, benefiting from, or

creating computers.”

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… Computing?

“… computing may someday be organized as a public utility just as the telephone system is a public utility... The computer utility could become the basis of a new and important industry.”−John McCarthy (a professor of MIT) 1961.

“As of now, computer networks are still in their infancy, but as they grow up and become sophisticated, we will probably see the

spread of computer utilities which, like present electric and

telephone utilities, will service individual homes and offices across the country.−L. Kleinrock(one of the chief scientists of the original ARPANET project) 1969” −John McCarthy (a professor of MIT)

1961.

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… Computing?

“it was transformed in a model consisting of consumer services

(commodity computing) and can be provided in a manner similar to traditional utilities “

Fifth utility -> Utility Computing or “Computing as a Utility”

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Computing Power ?

Required:

• solving problems involving modeling, simulation and analyzes

• Using unoccupied resources:

– in the 90s almost 90% of a processor power was not used

– the possibility to solve a wide variety of problems at affordable prices – cost/performance report in relation with a super-computer (HPC - high

performance computer) => ….

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Grid Computing

• The Grid concept appeared in the 90s

 In analogy with electric power grids ~ 1910

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Grid Computing

• Foster and Kesselman (1998): “A computational grid is a hardware and software infrastructure that provides dependable, consistent,

pervasive, and inexpensive access to high-end computational capabilities.”

• “The Grid is an emerging infrastructure that will fundamentally change the way we think – and use – computing. The word Grid is used by

analogy with the electric power grid, which provides pervasive access to electricity and, like the computer and a small number of other

advances has had a dramatic impact on human capabilities and society.

Many believe that by allowing all components of our information

technology infrastructure – computational capabilities, databases,

sensors, and people – to be shared flexibly as true collaborative tools,

the Grid will have a similar transforming effect, allowing new classes of

application to emerge.” (Foster and Kesselman 2004)

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Grid Computing

 Distributed computing architecture originally designed scientific projects and then the industrial ones

 Offers the existance of a software and hardware infrastructure which allows:

permanent and affordable access in a consistent manner to computing resources

 Offers various mechanism to process data in a distributed manner

 Allows the execution of tasks on multiple machines that can be viewed as a single computer

 Offers support for searching and retrieving information, regardless of their physical location

 Offers the context to create VO - virtual organizations – which shares application, data in an open and heterogeneous environment in order to solve various complex problems

It is shared:

Computing/processing power, Data storage/networked file systems,

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Grid Computing

 Terminology:

 Grid middleware – software level providing the required

functionalities needed for heterogeneous resources sharing and creating a virtual organization

 Grid infrastructure – refers to the combination of hardware and Grid middleware which transforms disparate and

heterogeneous computing resources in a virtual

infrastructure that offers the view of a single machine to the end user

 Utility computing – Grid Computing and applications are provided as services (e.g. hosting solutions for VO, et. al.)

- Utility computing is based on business pay-per-use model

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Grid Computing| Architecture

 Grid Architectures use simultaneously a large number of resources (hardware, software, logical)

 Resource – a sharing entity that can be present in a Grid infrastructure:

 Computation: PDA, PC, workstation, server, cluster

 Storage: hard disk, RAID, SAN, …

 I/O type: sensors, networks, printersetc.

 Logical: timers, …

• Obs. Systems as: scientific instruments or HPC can be part of a Grid

 A Grid architecture focuses on interoperability issues , communication protocols between suppliers and the resource used in order to

establish sharing relationships

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Grid Computing| Architecture

 Generic Grid architecture

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Grid Computing|Classification

 Classifications:

 In relation to the type of managed resources

 Compute Grid – used to share computing resources (e.g. CPU) - Examples: intensive graphic processing

 Data Grid – focused on storage, management and sharing of distributed and heterogeneous resources

 Application Grid – focused on application management and

transparently providing remote access to software and libraries;

Example: grids in the bioinformatics field or earth science

 Service Grid – resulting from Grid and SOA convergence, offers support to share services in an efficient manner

 In relation to the resource sharing domain:

 Cluster Grid

 Enterprise Grid

 Utility Grid Services

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Grid Computing| Evolution

 Generation 1 – Globus project (Goble & Foster)

 Applications requiring high computing power

 Includes protocols (LDAP, FTP) and heterogeneous development tools

 Support for access and files transfer

 Use Internet technologies, but ignore the Web

 Employed mainly in academic environment

 Sharing resources is achieved via GridFTP

 Implementations: …Legion, Condor, Unicore, ….

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Grid Computing| Evolution

 Generation 2 – OGSA (Open Grid Services Architecture)

 There is convergence of Service-oriented computing (SOC) and Grid Computing

• We notice the interoperability and sharing vision of SOC at application lever versus Grid computing vision mainly at hardware level

 Generation 1: Grid Computing architecture consists of protocols and services used to describe and share available physical resources

 By using Web Services Standard ( such as: WSDL, SOAP, BPL4WS,…) Grid

protocols and Services can be described in a standardized manner

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Grid Computing| Evolution

 Generation 2 – OGSA (Open Grid Services Architecture)

 OGSA:

 Using the same standards

=> it was possible the

convergence between Grid Computing and SOC =>

besides hardware and system resources, the

applications have become

shareable

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Implementation

 Generation 2 – OGSA (Open Grid Services Architecture)

Grid services must be:

– Dynamic and volatile – set of composed services that can be invoked or removed “on the fly”

– Ad-hoc – there is no central location or central control

– Widespread– orchestrating a large number of services (> 100) should be performed anytime

– Available – potentially long-term (e.g. a simulation can take weeks) – OGSI (Open Grid Service Infrastructure)

 OGSA Infrastructure - “accommodates” interactions between Grid resources and Web Services

 Model implemented by Globus Toolkit 3.0

» OGSI was replaced by WSRF (Web Service Resource Framework):

WS- Security, WS- Management and other standards for Web

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Grid Computing| Evolution

 Generation 3 – present and future

 Convergence of Grid Computing and SaaS (Software-as-a-Service) paradigm

 SaaS

 Designates software that is owned, delivered and managed by a provider

 It is used in the pay-per-use principle via a Web browser or APIs

 Versus traditional software

 The user pays for the time of use

 The user does not have the software, he does not invest in the infrastructure or licenses

 History: Application Service Provisioning (ASP) – appeared in 1988

 It was a step for IT outsourcing and it came with the idea of Web

applications that could be provided by a central supplier (one-to-many delivery model)

 The main problem: the inability to provide personalized services

 Issues regarding scalability, robustness,….

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Grid Computing| Evolution

 Generation 3 – present and future

 ASP problems can be solved by using Grid Computing + Web Services

 Web Services allows services personalization

 Grid Environment offer flexibility and scalability

=> many-to-many delivery model

[Grid and Cloud Computing - A Business Perspective on

Technology and

Applications, 2010]

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Present and future

Overview

 Two directions of evolution:

 Grid Computing

 Mature technology

 It provides computational power in pay-per-use manner => new business models for utility computing

 There were many initiatives at hardware level: Sun, IBM, etc.

 There were many initiatives at software level -> SaaS

 Microsoft, SAP et. al.

 ? Next step…

 A scalable , robust and reliable physical infrastructure,

 Services that provide developers access to infrastructure by manipulating abstracted interfaces

 SaaS running on a flexible and scalable infrastructure

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Cloud Computing

 What is?

Larry Ellison, founder of

“We’ve redefined Cloud

Computing to include everything that we already do. . . . I don’t understand what we would do differently in the light of Cloud

Computing other than change the

wording of some of our ads.”

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Cloud Computing

 What is?

Richard Stallman

•“cloud computing is evil”

•“I think that marketers like cloud computing because it is devoid of substantive meaning. The term’s meaning is not substance, it’s an

attitude: ‘Let any Tom, Dick and Harry

hold your data, let any Tom, Dick and

Harry do your computing for you (and

control it).’ Perhaps the term ‘careless

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Cloud Computing

Definition from the end user perspective:

• “the idea of delivering personal (e.g., email, word

processing, presentations.) and business productivity applications (e.g., sales force automation, customer service, accounting) from centralized servers” (Merrill Lynch)

Definition that contains architectural aspects:

• “a service model that combines a general organizing principle for IT delivery, infrastructure components, an

architectural approach and an economic model – basically,

a confluence of grid computing, virtualization, utility

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Cloud Computing

Definition that contains both architectural and final use aspects:

• “Cloud Computing refers to both the applications delivered as services over the Internet and the hardware and systems

software in the datacenters that provide those services. The

services themselves have long been referred to as Software as a Service (SaaS). The datacenter hardware and software is what we will call a Cloud. When a Cloud is made available in a pay-as- you-go manner to the general public, we call it a Public Cloud;

the service being sold is Utility Computing. We use the term Private Cloud to refer to internal datacenters of a business or other organization, not made available to the general public.

Thus, Cloud Computing is the sum of SaaS and Utility

Computing, but does not include Private Clouds. People can be users or providers of SaaS, or users or providers of Utility

Computing.” (Berkeley Lab, 2009)

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Cloud Computing

Definitions

“a large-scale distributed computing paradigm that is driven by economies of scale, in which a pool of abstracted, virtualized, dynamically-scalable, managed computing power, storage, platforms, and services are delivered on demand to external customers over the Internet.” (Foster et al. (2008))

• http://jameskaskade.com/?p=594

• “a style of computing in which massively scalable IT-related capabilities are provided “as a service” using Internet

technologies to multiple external

customers” (Gartner)

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Cloud Computing

The relation with Grid Computing:

• “We argue that Cloud Computing not only overlaps with Grid Computing, it is indeed evolved out of

Grid Computing and relies on Grid Computing as its backbone and infrastructure support. The

evolution has been a result of a shift in focus from an infrastructure that delivers storage and

compute resources (such is the case in Grids) to

one that is economy based aiming to deliver more

abstract resources and services (such is the case in

Clouds).” (Foster et al., 2008)

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Cloud Computing

Versus Grid Computing

Grid Computing Cloud Computing

Business Model

(Traditional: pay only once for the unlimited use of the software)

Grid: project oriented, negotiation, allocate resources depending on the level of the provided services

Cloud: the pay is allocated depending on the consumption (computing, storage, ..)

Arhitectura Fabric Level – consists in resources, similar to

Grid

Unified Resource Level – resources that have been encapsulated (e.g. virtualization) – cluster or virtual system, file system logic, etc.

Platform Level- environment to host web, develop the services, etc.

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Cloud Computing

Versus Grid Computing

Computing Model Batch-scheduled (queued systems)

Assigning multiple resources/

servers for a single task

Simultaneouslyuser shared resources, as opposed to dedicated

Challenge: QoS Exploitation pattern Running programs for a limited

amount of time

Frequently used for “long- running services”

Various relationships between resources providers

Main purpose – creating => user policies and agreements

(multiple domains)

Overrides this necessity (single domain)

Different purpose Provides infrastructure as service

Provides IaaS, PaaS, SaaS Final user perspective The Grid interfaces are based on

protocols and API’s oriented to expert users

Provides interfaces available in browser or API.

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Cloud Computing

Versus Grid Computing

Data location – in order to achieve better scalability, the data are distributed on several computers

Based on distributed files systems (NFS, GPFS,PVFS, Lustre)

Based on map-reduce mechanisms

Monitoring Monitoring tools: Ganglia

(http://meta.rocksclusters.org/g anglia/) -Grid Report for Sun, 19 Feb 2012

A low granularity control is difficult to achieve because virtualization (issues for users and administrators)

Vision : self-maintained autonomous clouds Programming models Employs flux control tools to

manage large quantities of data and tasks (MPICH-G2, GridRPC,

…)

Employs map-reduce models.

Implementation examples:

Hadoop using Pig as programming

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Cloud Computing

• “How big is the

Cloud?” 

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Cloud Computing

• “How big is the

Cloud?” 

[https://zephoria.com/top-15-valuable-facebook-statistics/]

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Cloud Computing

• “How big is the

Cloud?” 

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Cloud Computing

• “How big is the Cloud?” 2019 

[http://www.internetlivestats.com/one-second/#google-band]

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Cloud Computing

• “How big is the

Cloud?” 2022 

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Cloud Computing

• “How big is the

Cloud?

”  Flickr

[http://www.live-counter.com/how-big-is-the-internet/]

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2015

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2016

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2017

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2019

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2020

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2021

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2022

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Cloud Computing

• The trend: data-centric computing – Big data

• Current currency on the Internet?

– Users “pay” Facebook, Google, Instagram use … all actions, links, shares are recorded

– Also, data have another dimension (besides economic)

• Better answers to various questions, validate hypotheses on various social interactions,….

• Example: Online Social Network research

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Cloud Computing

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Cloud Computing

• At this point, near search engines, there are other BigData

“players”

– banks, academia, financial environment, government,….

 Everything is possible thank to the new generation of

“hardware hosting services”  cloud and new programming models

• Cloud Services are deeply embedded in modern society – Communication: Twitter, Facebook, Skype, IM,…

– Media: iTunes, Netflix,….

– Market: Amazon, eBay, stock exchanges, advertising,…

– ….

• True understanding  understanding the interactions between

technology, systems, networks and people  purpose of this

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Bibliography

• Katarina Stanoevska Slabeva, Thomas Wozniak, Grid and Cloud Computing - A Business

Perspective on Technology and Applications, 2010, Editors Santi Ristol, Springer-Verlag Berlin Heidelberg

• Massimo Cafaro, Givani Aloisio, Grids, Clouds and Virtualization, 2011

• Foster I, Kesselman, C, Tuecke S (2001) The Anatomy of the Grid: Enabling Scalable Virtual Organization. International Journal of High Performance Computing Applications 15(3):200- 222

• Massimo Cafaro, Givani Aloisio, Grids, Clouds and Virtualization, 2011

• Katarina Stanoevska Slabeva, Thomas Wozniak, Grid and Cloud Computing - A Business

Perspective on Technology and Applications, 2010, Editors Santi Ristol, Springer-Verlag Berlin Heidelberg

• DMTF - http://dmtf.org/standards/cloud

• LIBVRT - http://libvirt.org/apps.html

• 2016 - http://expandedramblings.com/index.php/flickr-stats/

• 2016 -http://expandedramblings.com/index.php/by-the-numbers-a-gigantic-list-of-google- stats-and-facts/2/

• https://www.computerworld.com/article/3030642/flash-memorys-density-surpasses-hard-

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Bibliography

• Chow et al., Cloud Computing: Outsourcing Computation without Outsourcing Control, 1

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