Cloud and Grid Computing PPT computer science.pdf

Cloud and Grid Computing PPT in computer science

2. UNIT IINTRODUCTION
EvolutionofDistributedcomputing:Scalablecomputing
overtheInternet–Technologiesfornetworkbased
systems–clustersofcooperativecomputers-Grid
computingInfrastructures–cloudcomputing-
serviceorientedarchitecture–IntroductiontoGrid
Architectureandstandards–ElementsofGrid–
OverviewofGridArchitecture.
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3. Distributed Computing
Definition
y“A distributed systemconsists of multiple
autonomous computersthat communicate through
a computer network.
y“Distributed computing utilizes a network of many
computers, each accomplishing a portion of an
overall task, to achieve a computational result
much more quicklythan with a single computer.”
y“Distributed computing is any computing that
involves multiple computers remotefrom each
other that each have a rolein a computation
problem or information processing.”
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4. Introduction
yA distributed system is one in which hardware or
software components located at networked
computerscommunicate and coordinate their actions
only by message passing.
yIn the term distributed computing, the word
distributed means spread out across space. Thus,
distributed computing is an activity performed on a
spatially distributed system.
yThese networked computers may be in the same
room, same campus, same country, or in different
continents
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5. Introduction
Cooperation
Cooperation
Cooperation
Internet
Large-scale
Application
Resource
Management
Subscription
Distribution
Distribution Distribution
Distribution
Agent
Agent Agent
Agent
Job Request
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6. Motivation
yInherently distributed applications
yPerformance/cost
yResource sharing
yFlexibility and extensibility
yAvailability and fault tolerance
yScalability
yNetwork connectivity is increasing.
yCombination of cheap processors often more cost-effective
than one expensive fast system.
yPotential increase of reliability.
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7. History
y1975 –1985
yParallel computing was favored in the early years
yPrimarily vector-based at first
yGradually more thread-based parallelism was introduced
yThe first distributed computing programs were a pair of
programs called Creeper and Reaper invented in 1970s
yEthernet that was invented in 1970s.
yARPANET e-mail was invented in the early 1970s and
probably the earliest example of a large-scale distributed
application.
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8. History
y1985 -1995
yMassively parallel architectures start rising and message
passing interface and other libraries developed
yBandwidth was a big problem
yThe first Internet-based distributed computing project was
started in 1988 by the DEC System Research Center.
yDistributed.net was a project founded in 1997 -considered
the first to use the internet to distribute data for calculation
and collect the results,
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9. History
y1995 –Today
yCluster/grid architecture increasingly dominant
ySpecial node machines eschewed in favor of COTS
technologies
yWeb-wide cluster software
yGoogle take this to the extreme (thousands of nodes/cluster)
ySETI@Home startedin May 1999 -analyze the radio signals
that were being collected by the Arecibo Radio Telescope in
Puerto Rico.
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10. Goal
yMaking Resources Accessible
yData sharing and device sharing
yDistribution Transparency
yAccess, location, migration, relocation, replication,
concurrency, failure
yCommunication
yMake human-to-human comm. easier. E.g.. : electronic mail
yFlexibility
ySpread the work load over the available machines in the
most cost effective way
yTo coordinate the use of shared resources
yTo solve large computational problem10 Dr Gnanasekaran Thangavel 8/30/2016

11. Characteristics
yResource Sharing
yOpenness
yConcurrency
yScalability
yFault Tolerance
yTransparency
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12. Architecture
yClient-server
y3-tier architecture
yN-tier architecture
yloose coupling, ortight coupling
yPeer-to-peer
ySpace based
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13. yExamples of commercial application :
yDatabase Management System
yDistributed computing using mobile agents
yLocal intranet
yInternet (World Wide Web)
yJAVA Remote Method Invocation (RMI)
Application
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14. Distributed Computing Using Mobile Agents
yMobile agents can be wandering around in a network
using free resources for their own computations.
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15. Local Intranet
yA portion of Internet that is separately administered & supports
internal sharing of resources (file/storage systems and printers) is
called local intranet.
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16. Internet
yThe Internet is a global system of interconnected computer
networks that use the standardized Internet Protocol Suite
(TCP/IP).
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17. JAVA RMI
yEmbedded in language Java:-
yObject variant of remote procedure call
yAdds naming compared with RPC (Remote Procedure Call)
yRestricted to Java environments
RMI Architecture
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18. Categories of Applications in distributed
computingyScience
yLife Sciences
yCryptography
yInternet
yFinancial
yMathematics
yLanguage
yArt
yPuzzles/Games
yMiscellaneous
yDistributed Human Project
yCollaborative Knowledge Bases
yCharity
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19. Advantages
yEconomics:-
yComputers harnessed together give a better price/performance ratio
than mainframes.
ySpeed:-
yA distributed system may have more total computing power than a
mainframe.
yInherent distribution of applications:-
ySome applications are inherently distributed. E.g., an ATM-banking
application.
yReliability:-
yIf one machine crashes, the system as a whole can still survive if
you have multiple server machines and multiple storage devices
(redundancy).
yExtensibility and Incremental Growth:-
yPossible to gradually scale up (in terms of processing power and
functionality) by adding more sources (both hardware and software).
This can be done without disruption to the rest of the system.
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20. Disadvantages
yComplexity :-
yLack of experience in designing, and implementing a distributed
system. E.g. which platform (hardware and OS) to use, which
language to use etc.
yNetwork problem:-
yIf the network underlying a distributed system saturates or goes
down, then the distributed system will be effectively disabled thus
negating most of the advantages of the distributed system.
ySecurity:-
ySecurity is a major hazard since easy access to data means easy
access to secret data as well.
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21. Issues and Challenges
yHeterogeneity of components :-
yvariety or differences that apply to computer hardware,
network, OS, programming language and implementations
by different developers.
yAll differences in representation must be deal with if to do
message exchange.
yExample : different call for exchange message in UNIX
different from Windows.
yOpenness:-
ySystem can be extended and re-implemented in various
ways.
yCannot be achieved unless the specification and
documentation are made available to software developer.
yThe most challenge to designer is to tackle the complexity of
distributed system; design by different people.
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22. Issues and Challenges cont…
yTransparency:-
yAim : make certain aspects of distribution are
invisible to the application programmer ; focus
on design of their particular application.
yThey not concern the locations and details of
how it operate, either replicated or migrated.
yFailures can be presented to application
programmers in the form of exceptions –must
be handled.
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23. Issues and Challenges cont…
yTransparency:-
yThis concept can be summarize as shown in this
Figure:
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24. Issues and Challenges cont…
ySecurity:-
ySecurity for information resources in distributed system
have 3 components :
a. Confidentiality: protection against disclosure to
unauthorized individuals.
b. Integrity: protection against alteration/corruption
c. Availability: protection against interference with the
means to access the resources.
yThe challenge is to send sensitive information over Internet
in a secure manner and to identify a remote user or other
agent correctly.
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25. Issues and Challenges cont..
yScalability :-
yDistributed computing operates at many different scales,
ranging from small Intranet to Internet.
yA system is scalable if there is significant increase in the
number of resources and users.
yThe challenges is :
a. controlling the cost of physical resources.
b. controlling the performance loss.
c. preventing software resource running out.
d. avoiding performance bottlenecks.
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26. Issues and Challenges cont…
yFailure Handling :-
yFailures in a distributed system are partial –some
components fail while others can function.
yThat’s why handling the failures are difficult
a. Detecting failures : to manage the presence of failures
cannot be detected but may be suspected.
b. Masking failures : hiding failure not guaranteed in the
worst case.
yConcurrency :-
yWhere applications/services process concurrency, it will
effect a conflict in operations with one another and produce
inconsistence results.
yEach resource must be designed to be safe in a concurrent
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27. Conclusion
yThe concept of distributed computing is the most efficient
way to achieve the optimization.
yDistributed computing is anywhere : intranet, Internet or
mobile ubiquitous computing (laptop, PDAs, pagers, smart
watches, hi-fi systems)
yIt deals with hardware and software systems, that contain
more than one processing / storage and run in concurrently.
yMain motivation factor is resource sharing; such as files ,
printers, web pages or database records.
yGrid computing and cloud computing are form of distributed
computing.
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28. Grid Computing
Grid computingis a form of distributed computingwhereby a
"super and virtual computer" is composed of a clusterof
networked, loosely coupled computers, acting in concert to
perform very large tasks.
Grid computing(Foster and Kesselman, 1999) is a growing
technology that facilitates the executions of large-scale
resource intensive applicationson geographically distributed
computing resources.
Facilitates flexible, secure, coordinated large scale resource
sharing among dynamic collections of individuals, institutions,
and resource
Enable communities(“virtual organizations”) to share
geographically distributed resources as they pursue common
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29. Criteria for a Grid:
Coordinates resources that are not subject to centralized
control.
Uses standard, open, general-purpose protocolsand
interfaces.
Delivers nontrivial qualities of service.
Benefits
?Exploit Underutilized resources
?Resource load Balancing
?Virtualizeresources across an enterprise
?Data Grids, Compute Grids
?Enable collaborationfor virtual organizations
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30. Grid Applications
Dataandcomputationallyintensiveapplications:
Thistechnologyhasbeenappliedtocomputationally-intensivescientific,
mathematical,andacademicproblemslikedrugdiscovery,economic
forecasting,seismicanalysisbackofficedataprocessinginsupportofe-
commerce
yAchemistmayutilizehundredsofprocessorstoscreenthousandsof
compoundsperhour.
yTeams of engineers worldwide pool resources to analyze terabytes of
structural data.
yMeteorologists seek to visualize and analyze petabytes of climate data
with enormous computational demands.
Resource sharing
yComputers, storage, sensors, networks, …
ySharing always conditional: issues of trust, policy, negotiation, payment,
…
Coordinated problem solving
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31. Grid Topologies
• Intragrid
–Local grid within an organization
–Trust based on personal contracts
• Extragrid
–Resources of a consortium of organizations
connected through a (Virtual) Private Network
–Trust based on Business to Business contracts
• Intergrid
–Global sharing of resources through the internet
–Trust based on certification
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32. 8/30/2016Dr Gnanasekaran Thangavel32
Computational Grid
“A computational grid is a hardware and software
infrastructurethat provides dependable, consistent, pervasive,
and inexpensive access to high-end computational
capabilities.”
”The Grid: Blueprint for a New Computing Infrastructure”,
Kesselman & Foster
Example : Science Grid (US Department of Energy)

33. Data Grid
yA data gridis a grid computing system that deals with data —
the controlled sharing and management of large amounts
of distributed data.
yData Grid is the storage component of a grid environment.
Scientific and engineering applications require access to large
amounts of data, and often this data is widely distributed. A
data grid provides seamless access to the local or remote data
required to complete compute intensive calculations.
Example :
Biomedical informatics Research Network (BIRN),
the Southern California earthquake Center (SCEC).
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34. Methods of Grid Computing
yDistributed Supercomputing
yHigh-Throughput Computing
yOn-Demand Computing
yData-Intensive Computing
yCollaborative Computing
yLogistical Networking
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35. Distributed Supercomputing
yCombining multiple high-capacity resourceson a
computational grid into a single, virtual distributed
supercomputer.
yTackle problems that cannot be solved on a single
system.
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36. High-Throughput Computing
yUses the grid to schedule large numbers of loosely
coupled or independent tasks, with the goal of putting
unused processor cycles to work.
On-Demand Computing
|Uses grid capabilities to meet short-term requirements for
resourcesthat are not locally accessible.
|Models real-time computing demands.
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37. Collaborative Computing
yConcerned primarily with enabling and enhancing human-to-
human interactions.
yApplications are often structured in terms of a virtual shared
space.
Data-Intensive Computing
|The focus is on synthesizing new informationfrom data that is
maintained in geographically distributed repositories, digital
libraries, and databases.
|Particularly useful for distributed data mining.
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38. Logistical Networking
yLogistical networks focus on exposing storage
resourcesinside networks by optimizing the global
schedulingof data transport, and data storage.
yContrasts with traditional networking, which does not
explicitly model storage resources in the network.
yhigh-level services for Grid applications
yCalled "logistical" because of the analogy it bears with
the systems of warehouses, depots, and distribution
channels.
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39. P2P Computing vs Grid Computing
yDiffer in Target Communities
yGrid system deals with more complex, more
powerful, more diverse and highly
interconnected set of resources than
P2P.
yVO
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40. A typical view of Grid environment
User
Resource Broker
Grid Resources
Grid Information Service
A Usersends computation or data
intensive application to Global Grids in
order to speed up the execution of the
application.
AResourceBrokerdistribute the jobs in an
application to the Grid resources based on user’s
QoS requirements and details of available Grid
resources for further executions.
Grid Resources(Cluster, PC, Supercomputer,
database, instruments, etc.) in the Global Grid
execute the user jobs.
Grid Information Servicesystem
collects the details of the available Grid
resources and passes the information
to the resource broker.
Computation result
Grid application
Computational jobs
Details of Grid resources
Processed jobs
1
2
3
4
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41. Grid Middleware
yGrids are typically managed by grid ware -
a special type of middleware that enable sharing and manage grid
componentsbased on user requirements and resource attributes (e.g.,
capacity, performance)
ySoftware that connects other software components or applications to
provide the following functions:
Run applicationson suitable available resources
–Brokering, Scheduling
Provide uniform, high-level access to resources
–Semantic interfaces
–Web Services, Service Oriented Architectures
Address inter-domain issuesof security, policy, etc.
–Federated Identities
Provide application-level status
monitoring and control
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42. Middleware
yGlobus –chicago Univ
yCondor –Wisconsin Univ –High throughput
computing
yLegion –Virginia Univ –virtual workspaces-
collaborative computing
yIBP –Internet back pane –Tennesse Univ –
logistical networking
yNetSolve –solving scientific problems in
heterogeneous env –high throughput & data
intensive 8/30/201642 Dr Gnanasekaran Thangavel

43. Two Key Grid Computing Groups
The Globus Alliance (www.globus.org)
yComposed of people from:
Argonne National Labs, University of Chicago, University of Southern
California Information Sciences Institute, University of Edinburgh and
others.
yOGSA/I standards initially proposed by the Globus Group
The Global Grid Forum (www.ggf.org)
yHeavy involvement of Academic Groups and Industry
y(e.g. IBM Grid Computing, HP, United Devices, Oracle, UK e-Science
Programme, US DOE, US NSF, Indiana University, and many others)
yProcess
yMeets three times annually
ySolicits involvement from industry, research groups, and academics8/30/201643 Dr Gnanasekaran Thangavel

44. Some of the Major Grid Projects
Name URL/Sponsor Focus
EuroGrid, Grid
Interoperability (GRIP)
eurogrid.org
European Union
Create tech for remote access to super comp resources
& simulation codes; in GRIP, integrate with Globus
Toolkit™
Fusion Collaboratory fusiongrid.org
DOE Off. Science
Create a national computational collaboratory for fusion
research
Globus Project™ globus.org
DARPA, DOE, NSF,
NASA, Msoft
Research on Grid technologies; development and
support of Globus Toolkit™; application and deployment
GridLab gridlab.org
European Union
Grid technologies and applications
GridPP gridpp.ac.uk
U.K. eScience
Create & apply an operational grid within the U.K. for
particle physics research
Grid Research Integration
Dev. & Support Center
grids-center.org
NSF
Integration, deployment, support of the NSF
Middleware Infrastructure for research & education
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45. Grid Architecture
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46. The Hourglass Model
yFocus on architecture issues
yPropose set of core services as basic
infrastructure
yUsed to construct high-level, domain-specific
solutions (diverse)
yDesign principles
yKeep participation cost low
yEnable local control
ySupport for adaptation
y“IP hourglass” model
Diverse global services
Core
services
Local OS
A p p l i c a t i o n s
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47. Layered Grid Architecture
(By Analogy to Internet Architecture)
Application
Fabric
“Controlling things locally”: Access to, & control
of, resources
Connectivity
“Talking to things”: communication (Internet
protocols) & security
Resource
“Sharing single resources”: negotiating access,
controlling use
Collective
“Coordinating multiple resources”: ubiquitous
infrastructure services, app-specific distributed
services
Internet
Transport
Application
Link
Internet Protocol Architecture
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48. Example:
Data Grid Architecture
Discipline-Specific Data Grid Application
Coherency control, replica selection, task management, virtual data catalog,
virtual data code catalog, …
Replica catalog, replica management, co-allocation, certificate authorities,
metadata catalogs,
Access to data, access to computers, access to network performance data, …
Communication, service discovery (DNS), authentication, authorization,
delegation
Storage systems, clusters, networks, network caches, …
Collective
(App)
App
Collective
(Generic)
Resource
Connect
Fabric
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49. Simulation tools
yGridSim–job scheduling
ySimGrid–single client multiserverscheduling
yBricks –scheduling
yGangSim-Ganglia VO
yOptoSim–Data Grid Simulations
yG3S –Grid Security services Simulator –security
services
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50. Simulation tool
GridSimisaJava-basedtoolkitformodeling,and
simulationofdistributedresourcemanagementand
schedulingforconventionalGridenvironment.
GridSimisbasedonSimJava,ageneralpurposediscrete-
eventsimulationpackageimplementedinJava.
AllcomponentsinGridSimcommunicatewitheachother
throughmessagepassingoperationsdefinedbySimJava.
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51. Salient features of the GridSim
yIt allows modeling of heterogeneoustypes of resources.
yResources can be modeled operating under space-or time-
shared mode.
yResource capability can be defined (in the form of MIPS
(Million Instructions Per Second) benchmark.
yResources can be located in any time zone.
yWeekends and holidayscan be mapped depending on
resource’s local time to model non-Grid (local) workload.
yResources can be bookedfor advance reservation.
yApplications with different parallel applicationmodels can
be simulated.
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52. Salient features of the GridSim
yApplicationtaskscanbeheterogeneousandtheycanbe
CPUorI/Ointensive.
yThereisnolimitonthenumberofapplicationjobsthatcanbe
submittedtoaresource.
yMultipleuserentitiescansubmittasksforexecution
simultaneouslyinthesameresource,whichmaybetime-
sharedorspace-shared.Thisfeaturehelpsinbuilding
schedulersthatcanusedifferentmarket-driveneconomic
modelsforselectingservicescompetitively.
yNetworkspeedbetweenresourcescanbespecified.
yItsupportssimulationofbothstaticanddynamicschedulers.
yStatisticsofallorselectedoperationscanberecordedand
theycanbeanalyzedusingGridSimstatisticsanalysis
methods.
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53. A Modular Architecture for GridSimPlatform and Components.
Appn Conf Res Conf User Req Grid Sc
Output
Application, User, Grid Scenario’s input and Results
Grid Resource Brokers or Schedulers
…
Appn
modeling
Res entity Info serv Job mgmt Res alloc Statis
GridSim Toolkit
Single CPU SMPs Clusters Load Netw Reservation
Resource Modeling and Simulation
SimJava Distributed SimJava
Basic Discrete Event Simulation Infrastructure
PCs Workstation ClustersSMPs Distributed Resources
Virtual Machine
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54. Web 2.0, Clouds, and Internet of Things
HPC: High -Performance Computing HTC: High -Throughput Computing
P2P: Peer to Peer MPP: Massively Parallel Processors
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55. 55
What is a Service Oriented Architecture?

56. 56
What is a Service Oriented Architecture (SOA)?
yA method of design, deployment, and
management of both applications and the
software infrastructure where:
yAll software is organized into business
services that are network accessible and
executable.
yService interfaces are based on public
standards for interoperability.

57. 57
Key Characteristics of SOA
yQuality of service, security and
performance are specified.
ySoftware infrastructure is responsible for
managing.
yServices are cataloged and discoverable.
yData are cataloged and discoverable.
yProtocols use only industry standards.

58. 58
What is a “Service”?
yA Service is a reusable component.
yA Service changes business data from one state
to another.
yA Service is the only way how data is accessed.
yIf you can describe a component in WSDL, it is a
Service.

59. 59
Information Technology is Not SOA
Business Mission
Information Management
Information Systems
Systems Design
Computing & Communications
Information
Technology
SOA

60. 60
Why Getting SOA Will be Difficult
yManaging for Projects:
ySoftware: 1 -4 years
yHardware: 3 -5 years;
yCommunications: 1 -3 years;
yProject Managers: 2 -4 years;
yReliable funding: 1 -4 years;
yUser turnover: 30%/year;
ySecurity risks: 1 minute or less.
yManaging for SOA:
yData: forever.
yInfrastructure: 10+ years.

61. 61
Why Managing Business Systems is Difficult?
y40 Million lines of code in Windows XP is unknowable.
yTesting application (3 Million lines) requires >10
15
tests.
yProbability correct data entry for a supply item is
<65%.
yThere are >100 formats that identify a person in DoD.
yOutput / Office Worker: >30 e-messages /day.

62. 62
How to View Organizing for SOA
STABILITY HERE
VARIETY HERE
CorporatePolicy,CorporateStandards,ReferenceModels,
DataManagementandTools,IntegratedSystems
ConfigurationDataBase,SharedComputingand
Telecommunications
ApplicationsDevelopment&Maintenance
ENTERPRISELEVEL
PROCESSLEVEL
BUSINESSLEVEL
APPLICATIONLEVEL
LOCALLEVEL
GraphicInfoWindow,PersonalTools,InquiryLanguages
CustomizedApplications,PrototypingTools,Local
ApplicationsandFiles
Applications
SecurityBarrier
Business
SecurityBarrier
Process
SecurityBarrier
Privacyand
Individual
SecurityBarrier
GLOBALLEVEL
IndustryStandards,CommercialOff-the-Shelf
ProductsandServices
PERSONALLEVELPrivateApplicationsandFiles
FunctionalProcessA
FunctionalProcessB
FunctionalProcessC
FunctionalProcessD
OSDService A Service B

63. 63
SOA Must Reflect Timing
Corporate Policy, Corporate Standards, Reference Models,
Data Management and Tools, Integrated Systems
Configuration Data Base, Shared Computing and
Telecommunications, Security and Survivability
Business A Business B
Infrastructure
Support
Applications Development & Maintenance
ENTERPRISE
PROCESS
BUSINESS
APPLICATION
LOCAL
Graphic InfoWindow, Personal Tools, Inquiry Languages
Customized Applications, Prototyping Tools, Local
Applications and Files
GLOBAL
Industry Standards, Commercial Off-the-Shelf
Products and Services
PERSONALPrivate Applications and Files
Functional Process A
Functional Process B
Functional Process C
Functional Process D
LONG TERM
STABILITY &
TECHNOLOGY
COMPLEXITY
SHORT TERM
ADAPTABILITY &
TECHNOLOGY
SIMPLICITY

64. 64
SOA Must Reflect Conflicting Interests
Enterprise
Missions
Organizations
Local
Personal

65. 65
Organization of Infrastructure Services
Infrastructure
Services
(Enterprise Information)
Data
Services
Security
Services
Computing
Services
Communication
Services
Application
Services

66. 66
Organization of Data Services
Data
Services
Discovery
Services
Management
Services
Collaboration
Services
Interoperability
Services
Semantic
Services

67. 67
Data Interoperability Policies
yData are an enterprise resource.
ySingle-point entry of unique data.
yEnterprise certification of all data definitions.
yData stewardship defines data custodians.
yZero defects at point of entry.
yDe-conflict data at source, not at higher levels.
yData aggregations from sources data, not from reports.

68. 68
Data Concepts
yData Element Definition
yText associated with a unique data element within a data
dictionary that describes the data element, give it a specific
meaning and differentiates it from other data elements.
Definition is precise, concise, non-circular, and
unambiguous. (ISO/IEC11179 Metadata Registry
specification)
yData Element Registry
yA label kept by a registration authority that describes a
unique meaning and representation of data elements,
including registration identifiers, definitions, names, value
domains, syntax, ontology and metadata attributes. (ISO

69. 69
Data and Services Deployment Principles
yData, services and applications belong to the Enterprise.
yInformation is a strategic asset.
yData and applications cannot be coupled to each other.
yInterfaces must be independent of implementation.
yData must be visible outside of the applications.
ySemantics and syntax is defined by a community of
interest.
yData must be understandable and trusted.

70. 70
Organization of Security Services
Security
Services
Transfer
Services
Protection
Services
Certification
Services
Systems
Assurance
Authentication
Services

71. 71
Security Services = Information Assurance
yConduct Attack/Event Response
yEnsure timely detection and appropriate response to
attacks.
yManage measures required to minimize the
network’s vulnerability.
ySecure Information Exchanges
ySecure information exchanges that occur on the
network with a level of protection that is matched to
the risk of compromise.
yProvide Authorization and Non-Repudiation Services
yIdentify and confirm a user's authorization to access

72. 72
Organization of Computing Services
Computing
Services
Computing
Facilities
Resource
Planning
Control &
Quality
Configuration
Services
Financial
Management

73. 73
Computing Services
yProvide Adaptable Hosting Environments
yGlobal facilities for hosting to the “edge”.
yVirtual environments for data centers.
•Distributed Computing Infrastructure
yData storage, and shared spaces for information
sharing.
•Shared Computing Infrastructure Resources

74. 74
Organization of Communication Services
Communication
Services
Interoperability
Services
Spectrum
Management
Connectivity
Arrangements
Continuity of
Services
Resource
Management

75. 75
Network Services Implementation
yFrom point-to-point communications (push
communications) to network-centric
processes (pull communications).
yData posted to shared space for retrieval.
yNetwork controls assure data synchronization
and access security.

76. 76
Communication Services
yProvide Information Transport
yTransport information, data and services
anywhere.
yEnsures transport between end-user devices
and servers.
yExpand the infrastructure for on-demand

77. 77
Organization of Application Services
Application
Services
Component
Repository
Code Binding
Services
Maintenance
Management
Portals
Experimental
Services

78. 79
Example of Development Tools
yBusiness Process Execution Language, BPEL, is an executable
modeling language. Through XML it enables code generation.
Traditional Approach BPELApproach
-Hard-coded decision logic -Externalized decision logic
-Developed by IT -Modeled by business analysts
-Maintained by IT -Maintained by policy managers
-Managed by IT -Managed by IT
-Dependent upon custom logs -Automatic logs and process
capture
-Hard to modify and reuse -Easy to modify and reuse

79. 80
A Few Key SOA Protocols
yUniversal Description, Discovery, and Integration, UDDI.
Defines the publication and discovery of web service
implementations.
yThe Web Services Description Language, WSDL, is an XML-
based language that defines Web Services.
ySOAPis the Service Oriented Architecture Protocol. It is a
key SOAin which a network node (the client) sends a request
to another node (the server).
yThe Lightweight Directory Access Protocol, or LDAPis
protocol for querying and modifying directory services.
yExtract, Transform, and Load, ETL, is a process of moving
data from a legacy system and loading it into a SOA