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Cloud Computing and Software
as a Service in BMI
Timoteus Ziminski
Computer Science & Engineering Department
The University of Connecticut
tbz@engr.uconn.edu
Spring 2011
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Overview
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Background
 Definition
 Providers
 Technologies
BMI in the Cloud
 Application Fields
 Example: Virtual Patient Chart
 Limitations
Conclusion
 Critique
 Research topics
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Overview
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Background
 Definition
 Providers
 Technologies
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Background
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What is the Cloud?
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Definition
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NIST definition:
“Cloud computing is a model for enabling ubiquitous,
convenient, on-demand network access to a shared pool
of configurable computing resources (e.g., networks,
servers, storage, applications, and services) that can be
rapidly provisioned and released with minimal
management effort or service provider interaction.”
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Bottom line: computing paradigm that hides
complexity through a notion of abstract resources
Although this paradigm is still considered to be under
development, several very mature platforms are
apparent.
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Providers
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Google
 Mail, Calendar, Health, Maps, Docs, Google Apps
Amazon
 Amazon Web Services (AWS), Simple Storage
System (Amazon S3)
IBM
 SmartCloud Services, LotusLive, Blueworks,
Collaborative Care
Microsoft
 Azure, WindowsServer Hyper-V, Office 365
And many, many more…
 Enormous range of products covering a variety of
tasks: development, testing, training, archiving,
analysis, and collaboration
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Service Models
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Heterogeneous types of service can be embedded into
the cloud
 All options hide underlying infrastructure to a
certain level
Software as a Service (SaaS)
 Provides applications
 Cross-device and cross-platform capabilities
Platform as a Service (PaaS)
 Access to the cloud hosting environment
 Deployment of applications
Infrastructure as a Service (IaaS)
 Provides access to basic resources
 CPU, network, storage
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Characteristics
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On-demand self service
 Services are mostly automatic
Broad network access
 Usage of standard mechanisms
 Allows thin clients
Resource pooling
 No control about physical instances
Rapid elasticity
 Resources are presented as unlimited
 Capacities grow and shrink automatically
according to requirements
Measured service
 Pay for what you use
 Little up-front capital needed
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Deployment Models for Cloud Infrastructure
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Private
 Access by one organization
 Management in-house or by third party
Community
 Shared across multiple organizations
Public
 Accessible by general public or large number of
organizations
 Typically used for selling cloud applications
Hybrid
 Composite of multiple clouds
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Importance to IT Market
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Citigroup estimates Amazon will
generate $650 million revenues through
AWS in 2011.
IBM intends to generate revenues of
$7.0 billion from cloud computing by
2015 (over 5% of total revenues.)
Microsoft will be spending 90% of its
$9.6 billion research and development
budget on cloud strategies in 2011.
Gartner predicts the cloud market to
grow to $102.1 billion net this year
from $68.3 billion in 2010.
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Technologies: On the Hard Side
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Cloud computing requires reliable, efficient and
powerful data centers
General hardware progress gives advantages
 Disc space, memory, energy efficiency
More important, networking and virtualization
technologies are fueling the development of cloud
applications
 Omnipresent access to low latency broadband
internet
 Multiplexing architectures
 Hardware virtualization support
 Clustering techniques
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Technologies: On the Hard Side (ctd.)
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Lightweight, always connected end devices are
increasingly popular
 Tablet PCs, Smartphones, Laptops (Cr-48)
Usage of multiple platforms simultaneously creates
synchronization issues
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Technologies: On the Soft Side
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On the server side virtualization software plays an
important role
 VMware, VirtualBox, Virtual PC, Xen
From an organizational perspective, Service-oriented
Architectures allow the decomposition of IT processes
 Encapsulation into service with interfaces
 Create potential for replacement of local services
with options from the cloud
 Possible implementations
 REST: HTTP/S or SOAP RPC
 Web Services: XML, WSDL, UDDI, SOAP
 CORBA
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Technologies: On the Soft Side (ctd.)
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Development of operating systems which heavily rely
on cloud applications
 Android, iOS, Chromium OS
Increasingly sophisticated web browsers
 IE9, Firefox 4, Chrome, Safari 5
 HTML5, JavaScript/AJAX, Flash, Silverlight
To some extent also programming language concepts
and libraries
 Java, Python, Perl, Ruby, Scala
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Overview
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PaaS
SaaS
IaaS
Use
Cloud Resources
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Overview
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BMI in the Cloud
 Application Fields
 Example: Virtual Patient Chart
 Limitations
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Application Fields
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In which BMI areas can we leverage the benefits of
Cloud Computing?
Clinical
Informatics
Imaging
Informatics
Bioinformatics
BMI
Clinical
Research
Informatics
Public Health
Informatics
HIT Training
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Clinical Informatics Challenges
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Patient records
 Electronic Medical Records, Personal Healthcare
Records
 Inherit need for efficient and reliable large-scale
data storage and exchange
Collaboration between
 Healthcare professionals
 Team-based collaboration
 Transition of care
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Healthcare organizations
 Practices, Labs, Pharmacies, Clinics, Hospitals
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Domains
 Providers, Payers, Researchers
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CC Benefits for Clinical Informatics
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Personal Healthcare Records
 Google Health, Microsoft Health Vault, WebMD
Electronic Medical Records
 First attempts to organize EMRs in private clouds
 Modular approaches with plug-in architectures
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Health information exchange
Decision support
Automatic note processing, voice recognition
Patient education
Opens the door for stepwise integration via a cloud
of clouds
 Hybrid clouds regulate the amount of exchanged data
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CC Benefits for Clinical Informatics
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Implementing HIE in the context of small practices
 Application service provider model
 Limits requirements and costs
 Technical knowledge can remain on provider side
 Maintenance reduces to thin clients
 Compliance with regulations becomes provider task
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Data warehousing
 Example: Data from the pathology laboratory
 In-house solutions create further data silos
 The cloud concept opens the doors for affordable
generic solutions
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Virtual Patient Chart
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CC benefits for Clinical Informatics (ctd.)
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Virtual chart
 Cloud computing services can provide very
abstract storage resources
 Space and performance is presented as limitless
and automatically adjustable
 Highly accessible and easy to synchronize across
platforms
 We are starting to have experience real-life proof
platforms for real-time collaboration on documents
Is that enough?
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A Word of Warning…
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Cloud Computing is
another useful tool,
not the silver bullet!
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Bioinformatics Challenges
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Heavy computational analysis tasks
 DNA sequencing
 Genomics
 Protein microarrays
 Mutation analysis
In addition to the specific hardware for the analysis,
we need
 Storage
 Petabyte scale
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CPU cycles
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CC Benefits for Bioinformatics
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The cloud starts to offer elegant solutions for largescale data storage
 Know-how about hardware and data management
can cumulate at service providers
 Elastic nature and “pay as you go” payment
models increase accessibility for institutions
 Do research rather than worrying about backups
Algorithmic tasks are the more at home in the domain
of Grid computing
However, the cloud can increase discoverability and
streamline the access to Grid resources
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Medical Imaging Informatics
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Essentially very similar arguments as discussed for the
field of Bioinformatics
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Public Health Informatics Challenges
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Tracking trends
 Large scale data warehousing
 Regional
 State-wide
 Population wide
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Disease Control and Prevention
Emergency response
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CC Benefits for Public Health Informatics
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Collection of public health data
 Virtual chart would a valuable source
 Inter-cloud communication
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The nature of the cloud facilitates:
 Storage of public health data
 Analysis of public health data
Outcomes can be provided through cloud services
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Clinical Research Informatics Challenges
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Repositories and Databases
 Data acquisition
 De-identification
 Data sharing
 Cohort building
Support of clinical trials
 Data collection
 Data management
 Data analysis
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CC Benefits for Clinical Research Informatics
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Outsource responsibility for regulation conform deidentification
Data management services
 Break open data silos
 Reuse collected data
Template based solutions for trial management
 Promotion of best practices
 Supporting tools
Exploit mobile devices and adequate apps for data
collection during trials
 Mobile phones, tablets
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HIT Training Challenges
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Training is an important and often underestimated
component
Who requires training?
 Healthcare professionals
 Students of related fields
In what areas can we train
 Medical education
 Transfer of new knowledge
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Skills in using software components
 EHR, Practice Management, e-Prescribing
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Adherence to best practices
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CC Benefits for HIT Training
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Virtualization has proven to be a powerful tool to
provide training environments and programs
Training in a Cloud is a popular product
 Scalable
 Flexible
 Cost efficient
Deployment and management of training
environments is largely simplified by the “disposable”
nature of virtual platforms
Service providers can offer cost efficient programs and
cover a larger variety of topics
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Limitations
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Cloud computing and SaaS has some risks and
limitations that we need to recognize in the context of
BMI
 Trust and Security
 Reliability and Availibility
 Performance
 Standardization
 Overhead
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Trust and Security
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Loading data off sensitive outside of organizational
boundaries is by definition a security risk that has to
be weighted against potential benefits
 Third parties are gaining access
 Service providers, governmental institutions
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Limitations through policies and regulations have to
be taken into consideration
Cloud computing does not make any assumptions
about physical locations
 Data can travel outside of country boarders
Employ suitable secure data transfer and encryption
techniques
 Currently still performance problems
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Reliability and Availability
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BMI systems are frequently of critical importance
 Clinical care systems can directly influence
decisions that can have potentially crucial impact
on the well being of patients
Risk system outages and performance problems
 Recent outage of AWS
 Not an acceptable scenario for many BMI settings
Absorbing the impact
 Local failover
 Sacrifices advantages of low complexity
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Performance
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SaaS solutions have matured over the past years
 Sophisticated Frontends
 Low latency broadband internet
However, the healthcare domain tends to be very
unforgiving towards workflow disruptions
 Potential fluctuations in QoS can have harsh
impact on the acceptance of services
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Standardization
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Cloud Computing does not give any immediate
advantages regarding interoperability
 Data models, standards and ontologies are a
completely separate issue.
Even worse, there are binding standards for cloud
interfaces
 Potential vender lock
Over 10 national and international organizations are
currently working on establishing standards
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Overhead
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Technologies such as Web Service and SOAP RPC
which are used in Cloud Computing might be still too
heavy weight for building a system that is aiming to
span over the complete healthcare system
From this ultra large scale system perspective we
might need to rely on even more abstract concepts
such as HTTP/S REST.
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Overview
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Conclusion
 Critique
 Research topics
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Critique
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Just another hype?
 A lot of advertisement
 Similar buzz-word overload as with SOA
 In fact, often no solid distinguishing of the patterns
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Nothing new?
 Similar middleware concepts and ideas go far back
 Existent services get tagged with the Cloud label
But noteworthy
 Aligns with the current development of clients
 Conceptually targets many BMI problems
 Hardware and network progress enabled well
convincing platforms and application suites
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Research Topics
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Improving the Cloud
 Trust and Security
 Scheduling and Virtualization
 Mobile Cloud Computing
 Inter-cloud communication (cloud of clouds)
Leveraging the Cloud
 Data Analysis
 Data Management
 Data Modeling
 Text and Voice recognition
Conferences
 IEEE CLOUD, Cloud Expo, Cloud Connect
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Thank you!
Questions?
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