Description - Ajith defended his thesis on application and data portability in cloud computing. More details on Ajith's research and publications can be found at http://knoesis.wright.edu/researchers/ajith/ Video can be found at : http://www.youtube.com/watch?v=oDBeBIIFmHc&list=UUORqXk1ZV44MOwpCorAROyQ&index=1&feature=plpp_video

1. Image credit : http://www.epic-cities.eu
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2. The Story of the
Biology Professor
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3. What is the best way
for me to crunch my
numbers?
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4. Private
cloud
In house cluster
Public
cloud
All logos are trademarks of the respective organizations
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5. What is the issue
here?
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6. Programming for the
cloud is hard!
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7. Cloud software
stacks are
incompatible!
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8. Abstraction Driven Application
and Data Portability in Cloud
Computing
Ajith H. Ranabahu
PhD Candidate
Ohio Center of Excellence in Knowledge-enabled Computing (kno.e.sis)
Wright State University
Dayton OH
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9. Carefully crafted abstractions
provide a means to develop, deploy
and manage cloud applications in a
platform agnostic manner
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10. Agenda
• Overview of Using Abstractions
• Abstractions for program
generation
• Abstractions for cloud interaction
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11. Cloud in a nutshell
Data
Software as a service (SaaS)
Analytics
Hadoop XaaS
Platform as a service (PaaS)
Infrastructure as a service (IaaS)
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12. What is the problem?
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13. Programming for the
cloud and keeping the
applications portable is
hard!
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14. Vendor lock-in is a
major concern in
cloud adoption
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15. Future of Cloud computing survey by North Bridge, showing the top 10 concerns in
Cloud computing. Full survey available at http://www.northbridge.com/2012-cloud-
computing-survey, released on June 20th 2012
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16. • Overview of Using Abstractions
• Abstractions for program
generation
• Abstractions for cloud interaction
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17. Why Abstract?
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18. Completely decouple the cloud
from applications!
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19. What to Abstract?
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20. Development of cloud
applications
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21. Deployment of cloud
applications
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22. Management of cloud
applications
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23. How to Abstract?
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24. What is already out
there?
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25. Abstraction Based Mobile
Application Generators
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26. Abstraction Based Cloud Web
Application Generators
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27. General
Programming
Platform Independence
Solution area we Language
are interested in based
Frameworks
Direct
Programming
Complexity
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28. Abstractions for cloud interaction -
Cloud Brokers and Integrators
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29. API Libraries
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30. Cloud
Platform Independence
Solution Area we brokers
are interested in
API Based
solutions
Original
Cloud APIs
Complexity
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31. What are our
Solutions?
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32. Program using
Domain Specific
Languages
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33. Interact
(Deploy and Manage)
via Middleware
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34. • Overview of Using Abstractions
• Abstractions for program
generation
• Abstractions for cloud interaction
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35. Preliminaries – A
background on
Languages
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36. What makes up a
Language?
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37. • Abstract Syntax Model (ASM)
o An abstract model of what the language
represents
• Concrete Syntax Model (CSM)
o The syntax of the language
• Transformations
o A mapping from ASM to CSM or vice versa
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38. Abstract Syntax Concrete
Transformation
Model Syntax Model
=
X+Y=Z
+ Z
X Y
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39. What is a Domain
Specific Language
(DSL)?
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40. A domain-specific language (DSL) is a
programming language or executable
specification language that offers, through
appropriate notations and abstractions,
expressive power focused on, and usually
restricted to, a particular problem domain.
A. van Deursen, P. Klint, and J. Visser, “Domain-specific languages: an annotated
bibliography,” SIGPLAN Not., vol. 35, no. 6, pp. 26–36, 2000.
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41. A domain is a set of operations
/ activities of interest
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42. A model is an abstraction of
a system or its environment
or both
K. Czarnecki and S. Helsen, “Feature-based survey of model transformation
approaches,” IBM Systems Journal, vol. 45, no. 3, pp. 621–645, 2006.
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43. Domain Models and
DSLs
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44. The Modeling
Hierarchy
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45. Meta-Metamodels
describe
Metamodels
describe
Domain Models
describe
Computer Based Systems
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46. ASM = Domain Meta
Model
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47. Where do we use
DSLs in the context of
cloud applications?
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48. Breaking down the
Cloud Application
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49. System Aspects Data Aspects
Cloud Application
Non-Functional Functional
Aspects Aspects
Amit Sheth and Ajith Ranabahu. Semantic Modeling for Cloud Computing, Part 2, IEEE Internet
Computing, vol. 14, no. 4, July/Aug 2010 pages 81-84
Amit Sheth and Ajith Ranabahu. Semantic Modeling for Cloud Computing, Part 1, IEEE Internet
Computing, vol. 14, no. 3, May/June 2010 pages 81-83
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50. Introduce DSLs to
cover each aspect!
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51. Problem Formation
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52. How do we put
things in a theoretical
perspective?
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53. Focus on the
transformations
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54. Transformations
from domain models
to cloud supported
models
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55. Focus on the
properties of
language model
transformations
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56. Assertion :
Each metamodel is a
graph
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57. Model Transformations – Relationship between models,
metamodels and transformations
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58. Model Transformations – Relationship between models,
metamodels and transformations expressed symbolically
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59. Condition 1 : Each semantically
distinct concept must be
distinctly defined in the domain
metamodel
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60. 26th July 2012 60

61. Example
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62. Typical
Required
Metamodel for expressions is a simplified version from Software Language Engineering:
Creating Domain-Specific Languages Using Metamodels By Anneke Kleppe
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63. Condition 2 : The
transformation must completely
define the target model
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64. 26th July 2012 64

65. Lemma 1 : The transformation
is not reversible
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66. Derived condition for Map-Reduce
style computations:
Domain meta model must be
mappable to a map-reduce task
model
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67. Practical
Implications
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68. More detailed
domain models are
needed!
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69. Not all models can
be transformed to
parallel architectures
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70. Don’t keep hopes on
Reverse Engineering!
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71. What about Data?
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72. Data schema
Incorporated using
DSLs
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73. Ontologies as data
schemas
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74. Practical Applications :
MobiCloud
My Contribution : Conceptualization and primary portion of implementation
1. A Domain Specific Language for Enterprise Grade Cloud-Mobile Hybrid Applications, 11th Workshop on
Domain-Specific Modeling (DSM), 2011
2. Power of Clouds In Your Pocket: An Efficient Approach for Cloud Mobile Hybrid Application Development ,
Cloudcom 2010
3. Towards Cloud Mobile Hybrid Application Generation using Semantically Enriched Domain Specific
Languages , International Workshop on Mobile Computing and Clouds (MobiCloud 2010)
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75. MobiCloud is a
Cloud-Mobile hybrid
application generator
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76. • Front-end is a native Mobile
application
• Back-end sits in a cloud,
exposed by a service interface
• Both pieces considered the 'app'
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77. Service Server
Service
UI provider side Persistent
Client Implementation handler Storage
Data Structures Data Structures
Mobile Device Cloud
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78. MobiCloud
Architecture
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79. Graphical Text based Other
Composer Composer Composers
MobiCloud DSL
Code Generation Templating Engine
GAE EC2 Android Blackberry
Templates Templates Templates Templates
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80. MobiCloud DSL
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81. recipe(:todolist) do
metadata({:id => 'task-manager'})
# models
model(:task, { :name=>:string,:description => :string,
:time => :date,:location => :string})
#controllers
controller(:taskhandler) do
action :create, :task
action :retrieve, :task
end
# views
view :add_task, {:models =>[:task],:controller => :taskhandler,
:action => :create}
view :show_tasks, {:models =>[:task],:controller => :taskhandler,
:action => :retrieve}
end
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82. MobiCloud Tools
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83. MobiCloud Graphical Composer
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84. Available publicly at
http://mobicloud.knoesis.org
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85. MobiCloud Code Catalog
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86. Available publicly at
http://mobicloud-catalog.knoesis.org
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87. MobiCloud has extensions that
enable the use of known ontologies
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88. A Scenarios in a
nutshell
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89. Blood pressure
recorder : Personal
Web Application
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90. Objective : Record
daily BP values
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91.  Data Driven
 4 data items to be recorded and
retrieved (BP figures and date)
 Simple user interface
 Personal
 Private (own) data source
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92. Visual composition of the blood pressure date recorder
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93. Different Android views, showing the index and the addbp
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screens 94

94. showbp view of Android application
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95. With MobiCloud, this
application was built and
deployed under 5 minutes !
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96. MobiCloud is the recipient of the
Technology award at the Fukuoka
Ruby Innovators Competition
One of two winners of the technology award from 82 competitors
over 9 countries
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97. A helping hand to our biology professor !
Practical Applications :
SCALE
My Contribution : Concept and Implementation
1. Identifying and Implementing the Underlying Operators for Nuclear Magnetic Resonance Based
Metabolomics Data Analysis, Third International Conference on Bioinformatics and Computational
Biology (BICoB-2011)
2. The Cloud Agnostic e-Science Analysis Platform, IEEE Internet Computing 2011
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98. SCALE is a DSL based
Statistical Application
Generator
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99. SCALE DSL
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100. # load data
original_data = load_data(:raw_data_file,{:format =>
"csv"})
# sum normalize
normalized = sum_normalize(original_data)
# Auto scale
scaled = auto_scale(normalized)
# write the file
store_data(:scaled, scaled)
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101. Supports 3 Target
Platforms
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102. • Hadoop (Local cluster or
Amazon EC2)
• Windows Azure (using the
experimental Daytona
framework)
• Any desktop OS using Ruby
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103. SCALE Architecture
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104. Graphical Text based Other
Composer Composer Composers
SCALE DSL
Code Generation Templating Engine
Java (Hadoop) C# (Azure / Ruby
Templates Daytona) Templates Templates
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105. SCALE Tools
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106. SCALE Graphical Composer
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107. Available publicly at
http://metabolink.knoesis.org/SCALE
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108. Our friendly biologist can
now quickly compose his
programs and run them with
any resource available!
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109. What did we learn
from these projects?
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110. Code Metrics
comparison
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111. LOC counts of
generated
applications
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112. 26th July 2012 113

113. 26th July 2012 114

114. Significant savings
in effort can be
obtained by using
DSLs
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115. Effort Comparison –
LOC counts in
templates
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116. 26th July 2012 117

117. 26th July 2012 118

118. The effort required to
create the templates
is manageable
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119. General
DSL based Programming
Platform Independence
Solutions Language
based
Frameworks
Direct
Programming
Complexity
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120. • Overview of Using Abstractions
• Abstractions for program
generation
• Abstractions for cloud interaction
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121. Preliminaries –
Basics of Middleware
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122. Application
Application 1 Application 2
N
APIs
Middleware
Interface Interface Interface
Lower Lower Lower
level level level
services services services
Platform 1 Platform 2 Platform M
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123. Using Middleware In
the Cloud Context
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124. What Operations can
we abstract?
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125. Application
Deployment
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126. Application
Undeployment
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127. Data Snapshots
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128. Additional Benefits
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129. Enforcing / Reusing
Patterns
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130. How to Apply
Middleware in the
cloud context?
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131. General Architecture for using Middleware in a cloud context
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132. Practical Applications :
Altocumulus
My Contribution : Evolving the concept and major portion of implementation
(Member of the 4 person team. Internship work at IBM Research 2009)
1. Toward Cloud-Agnostic Middlewares, OOPSLA, 2009
2. A Best Practice Model for Cloud Middleware Systems , Best Practices in Cloud Computing: Designing
for the Cloud workshop OOPSLA, 2009
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133. Cloud Middleware
System from IBM
Research
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134. Supported 3 target
platforms
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135. • Amazon EC2
o Included EC2 clones such as Eucalyptus
• Google App Engine
• IBM HiPODS
o IBM private cloud system, providing
infrastructure cloud services
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136. Introduced the
Concept of Best
Practices
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137. Altocumulus
Architecture
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138. 26th July 2012 139

139. Altocumulus
Dashboard
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140. Altocumulus Dashboard – Showing the list of deployments and
their status
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141. Altocumulus /
Platform Independence
Middleware
Solutions Cloud
brokers
API Based
solutions
Original
Cloud APIs
Complexity
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142. Altocumulus technology is now
part of the IBM PureSystems Cloud
offering, as part of the IBM Workload
Deployer
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143. Publication Coverage
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144. Altocumulus MobiCloud SCALE Others
2009 1. OOPSLA [1]
2. OOPSLA cloud
workshop [1]
* Altocumulus
demonstration
2010 1. IEEE Cloudcom [2] 2 part article on
2. MobiCase MobiCloud cloud application
workshop [1] modeling in IEEE
* MobiCloud demonstration Internet Computing
2011 1. workshop at SPLASH 1. BiCob [1]
[1] 2. IEEE Internet
2. IEEE COMSOC Computing [1]
MMTC E-Letter [1]
(invited)
2012 Paper under review
in IEEE TSC
26th July 2012 Total of 11 publications and 2 demonstrations covering this research 145

145. Publications
• Ajith Ranabahu, Michael Maximilien, Amit Sheth and Krishnaprasad
Thirunarayan. A Domain Specific Language for Enterprise Grade Cloud-
Mobile Hybrid Applications, 11th Workshop on Domain-Specific Modeling
(DSM) 2011 , Portland OR, USA.
• Ashwin Manjunatha, Ajith Ranabahu, Amit Sheth and Krishnaprasad
Thirunarayan. Power of Clouds In Your Pocket: An Efficient Approach for
Cloud Mobile Hybrid Application Development , 2nd IEEE International
Conference on Cloud Computing Technology and Science, 2010,
Indianapolis IN, USA. Pages 496-503
• Ajith Ranabahu, Ashwin Manjunatha, Amit Sheth and Krishnaprasad
Thirunarayan. Towards Cloud Mobile Hybrid Application Generation using
Semantically Enriched Domain Specific Languages , International Workshop
on Mobile Computing and Clouds (MobiCloud 2010) ,Santa Clara CA 2010.
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146. Publications (Cont.)
• Ashwin Manjunatha, Paul Anderson, Ajith Ranabahu and Amit Sheth.
Identifying and Implementing the Underlying Operators for Nuclear Magnetic
Resonance Based Metabolomics Data Analysis, Third International
Conference on Bioinformatics and Computational Biology (BICoB-2011),
2011, New Orleans LA, USA. pages 205-209
• Ajith Ranabahu and Amit Sheth. Semantics Centric Solutions for Application
and Data Portability in Cloud Computing, 2nd IEEE International
Conference on Cloud Computing Technology and Science, 2010,
Indianapolis IN, USA. pages 234-241
• Kalpa Gunaratna, Ajith Ranabahu, Paul Anderson and Amit Sheth. A Study
in Hadoop Streaming with Matlab for NMR Data Processing , 2nd IEEE
International Conference on Cloud Computing Technology and Science,
2010, Indianapolis IN, USA. pages 786-789
• Michael Maximilien, Ajith Ranabahu, Roy Engehausen and Laura Anderson.
Toward Cloud-Agnostic Middlewares, 24th ACM SIGPLAN International
Conference on Object-Oriented Programming, Systems, Languages, and
Applications (OOPSLA), 2009, Orlando FL, USA. pages 619-626
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147. Publications(Cont.)
• Ajith Ranabahu and Michael Maximilien. A Best Practice Model for Cloud
Middleware Systems , Proceedings of the Best Practices in Cloud
Computing: Designing for the Cloud workshop at the 24th ACM SIGPLAN
International Conference on Object-Oriented Programming, Systems,
Languages, and Applications (OOPSLA) pages 41-51
• Ajith Ranabahu, Paul Anderson and Amit Sheth. The Cloud Agnostic e-
Science Analysis Platform, IEEE Internet Computing, vol. 15, no. 6,
Nov/Dec. 2011 pages 85-89
• Amit Sheth and Ajith Ranabahu. Semantic Modeling for Cloud Computing,
Part 2, IEEE Internet Computing, vol. 14, no. 4, July/Aug 2010 pages 81-84
• Amit Sheth and Ajith Ranabahu. Semantic Modeling for Cloud Computing,
Part 1, IEEE Internet Computing, vol. 14, no. 3, May/June 2010 pages 81-
83
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148. Conclusion
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149. Using DSLs to provide domain
abstractions is a feasible way to
develop cloud applications
in a platform agnostic manner
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150. Middleware based process
abstractions are a feasible
way to deploy and manage
applications in the cloud
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151. My Other Research Activities
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152. SCALE
Cloud MobiCloud
Application
Generation
Research and Contributions
IBM
Altocumulus
publication
Cloud
Middleware Open source / public tool
Patent
IBM Sharable
Code
Service
Composition
SA-WSDL SA-REST Kino Annotation Tools
Annotation
Faceted Search / APIHut
SOA
Event
Mediatability
Detection
Year
2007 2008 2009 2010 2011 2012
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153. Questions
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154. 26th July 2012 155

155. 26th July 2012 156

156. Thank You
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157. Extra Slides
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158. Salesforce Contact
Manager : Enterprise
Web application
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159. Objective: View
contacts from your
Salesforce account
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160. • Connected to external data
sources
• Likely to be shared
• Rigorous security
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161. Uses 2nd
Generation
MobiCloud with the
Salesforce Extension
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162. Text Mode, editing the salesforce contact manager Application –
Graphical mode is not active in the advanced mode
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163. Different Android views, showing the index,
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salesforce_accounts and salesforce_login screens 164