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Robert Martin Computer Science & Engineering Department The University of Connecticut

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CSE 5810 Individual Research Project: Integration of Named Data Networking for Improved Healthcare Data Handling. Robert Martin Computer Science & Engineering Department The University of Connecticut 371 Fairfield Road, Box U-255 Storrs, CT 06269-2155. [email protected]

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CSE 5810 Individual Research Project:Integration of Named Data Networking for Improved Healthcare Data Handling

Robert Martin

Computer Science & Engineering Department

The University of Connecticut

371 Fairfield Road, Box U-255

Storrs, CT 06269-2155

[email protected]

motivation
Motivation
  • Technology limitations
    • Larger data files
    • Multiple databases
    • Ever expanding healthcare network
  • Fast pace hospital environment
    • Providers constantly moving
    • Intolerant to delayed data access
  • Lack of communication between departments
    • Clinical, technical, business management, financial, etc.
large scope
Large Scope
  • Keep up with change
    • Larger data files
    • Mobile devices
    • Real-time data availability
  • Conform to busy hospital environment
    • Revamp current network
    • Transparent infrastructure
overall goal
Overall Goal
  • Apply Named Data Networking within a hospital environment
    • Data connectivity
    • Improved transmission speeds (compared with regular IP networking)
    • Improved mobile device handling
    • Interoperability between diverse departments
named data networking ndn
Named Data Networking (NDN)

Image adapted from:

Tsudik, Gene. NSF FIA PI meeting: “NDN team presentation.” Berkeley, CA, May 25, 2011.

ndn vs ip networking
NDN vs. IP Networking
  • Named Data Networking
    • Data centric approach
  • IP Networking
    • Looks at where data is located

Image adapted from:

Jacobson et al. (full reference in notes)

interest and data packets
Interest and Data Packets
  • Interest Packet
    • Data name in query
    • Nonce is unique identifier
    • Selectors help better match interest to data
    • Scope and interest lifetime help guide packet to intended data
  • Data Packet
    • Content is of arbitrary data size
    • Signature is used to verify the packet’s producer and its integrity throughout transmission
pending interest table pit
Pending Interest Table (PIT)
  • Monitors all unsatisfied interest packets
  • Entry classified as unsatisfied until either a data packet is received (to match its interest) or the interest lifetime value is reached

“A Case for Stateful Forwarding Plane” by C. Yi et al. depicts a great image for how node’s use PITs(see full reference in notes)

forwarding information base fib
Forwarding Information Base (FIB)
  • Monitors downstream data location through next hop neighbor

“A Case for Stateful Forwarding Plane” by C. Yi et al. depicts a great image for how node’s use FIBs(see full reference in notes)

content storage
Content Storage
  • Cache data locally
  • Pushes data closer to consumer(s)
  • Allows network to become “data focused”
    • Quicker fetching of data for consumer
  • Data architecture can vary
    • FIFO, LRU, etc.
data naming
Data Naming
  • Application specific
  • Flexible standards
    • Classifications and standards can be adjusted
security
Security
  • Nurse fetching data which is unrelated to her role in the hospital (e.g. Patent’s social security number)
  • Security integrated into data packet
    • Authentication process
fetching data
Fetching Data
  • Filtering naming system
    • Adjust documentation standards for each department
      • E.g. Financial employee and patient see “heart attack” vs. global view classification as “Myocardial Infarction”
  • Paths are dynamic while being transparent to end user
    • Nodes can be added or removed without having an effect on the user
    • Robust among dense networks

We must make network aware of newly added data in an efficient manner

discovery service
Discovery Service
  • Maps out data on network (similar to DNS)
mobility with ip networking
Mobility with IP Networking
  • Illustration through example:
    • Pre-loading patient’s data
    • Large data files
    • Based on IP network
mobility with ip networking1
Mobility with IP Networking
  • Provider must request file again
  • Additional stress to hospital network
mobility with named data networking
Mobility with Named Data Networking
  • Illustration through example:
    • NDN based network
mobility with named data networking2
Mobility with Named Data Networking
  • Data requested again
  • Reduced redundant data packets
simulation settings
Simulation Settings
  • Ns3 and ndnSIM extension used
  • Regular IP based network vs. NDN integrated network
  • Focus:
    • Transmission times
    • Network stress
preliminary simulation data
Preliminary Simulation Data

Network Stress

Overall Transmission Time

conclusion
Conclusion
  • Apply NDN concepts in hospital infrastructure
    • “What” data instead of “Where”
    • Reduce stress on keynote features
    • Less bandwidth usage
    • Friendlier to mobile devices
  • Additional features
    • Adaptability with discovery service
    • Integrated security through data
  • Challenges
    • Acceptability by healthcare
    • Ensuring security of data
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