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Professor Yashar Ganjali
Department of Computer Science
University of Toronto
yganjali@cs.toronto.edu
http://www.cs.toronto.edu/~yganjali
Announcements
 Assignment # 1
 Submission deadline: 5PM on Friday Oct. 9th
 E-mail your solutions to me; or
 Slide them under my office door

BA5238
 Volunteers for lecture notes?
SII 199 - Computer Networks and Society
University of Toronto – Fall 2015
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Final Project
 Final project proposal
 Guidelines have been posted on class website.
 Each project completed by groups of two students

Use class mailing list to find teammates if you don’t know
anyone in class.
 1 page proposal
 Due: Fri. Oct. 16th at 5PM
 Intermediate report
 Key technologies
 2 pages
 Due: Fri. Nov. 13th at 5PM
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 Final presentation
 In class during the last two weeks
 15 minute presentation
 Final report
 Put everything together
 5 pages
 Due: Fri. Nov. 27th at 5PM
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The Story So Far …
• Introduction to computer networks
• Internet vs. mail
• The science of networks
• Characteristics, graphs, scale-free networks, …
• This week: Computer networks and healthcare
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Outline
 Motivational example
 Information flow
 Networks and awareness
 How networking technology helps with healthcare
 Detour: sensor networks
 Science of networks
 Epidemic prediction/control
 Big Idea …
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University of Toronto – Fall 2015
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Traditional Uses of Networks in Healthcare
 Communication
 Phone
 Video
 Teleconferencing
…
 Data transfer
 Fax
 E-mail
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Motivational Example: Rural Telemedicine
 Need:
 15M blind in India
 70% of blindness treatable
 7% in rural areas get care
 Aravind Eye Hospitals
 Tamil Nadu, India
 5 hospitals
 But too far for most to walk
 Goals:
 50 rural vision centers
 Diagnosis and prevention
SII 199 - Computer Networks and Society
University of Toronto – Fall 2015
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WiFi Routers
 What are WiFi routers?
 What’s their range?
 How much do they cost?
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WiFi for Rural Connectivity
 Can we use WiFi for rural connectivity?
✔ Cost


Partly because of unlicensed spectrum
Question: What is spectrum?
✗ Range


Question: What are the limiting factors?
Question: Can we fix the range limitation?
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New World Record – 382 Kms
Pico El Aguila, Venezuela
Elev: 4200 meters
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AirJaldi Rural WiFi ISP
•
•
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•
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•
•
Hybrid: closed mesh for backhaul
SII 199 - Computer Networks and Society
North India
Tibetan Community
WiLD links + APs
Links are 10–40 km long
Achieve 4–5 Mb/s per link
VoIP + Internet
10,000 users
Routers used: (a) Linksys WRT54GL,
(b) PC Engines Wrap Boards,
Costs: (a) $50, (b) $140
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Real Impact




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Over 130,000 patients so far
Centers are cash-flow positive
Over 20,000 patients have recovered sight
Growing to 50 centers covering 2.5M people
Hoping to replicate in Lumbini, Nepal
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University of Toronto – Fall 2015
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Remote Diagnosis
 Connect patients with health care resources using the
Internet
 Facilitate diagnosis, follow up, …
 Not a perfect tool
 Can lead to incorrect diagnosis
 Yet, it works in some situations
 Internet can also help with follow up and consulting
sessions that do not require physical presence
 Even in more advanced regions
SII 199 - Computer Networks and Society
University of Toronto – Fall 2015
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Remote Diagnosis
 Use network (the Internet) as a medium to help with
diagnosis
 Not a perfect tool
 Can lead to incorrect diagnosis
 Might work in some situations
 Internet can also help with follow up and consulting
sessions that do not require physical presence
 Even in more advanced regions
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University of Toronto – Fall 2015
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Outline
 Motivational example
 Information flow
 Networks and awareness
 How networking technology helps with healthcare
 Detour: sensor networks
 Science of networks
 Epidemic prediction/control
 Big Idea …
SII 199 - Computer Networks and Society
University of Toronto – Fall 2015
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Medical Information Flow
 Many sources of information
 Patient history
 Lab records





Electrocardiogram (EGG or EKG)
CAT scan
Magnetic resonance imaging (MRI)
Ultrasound
Digital X rays
 Doctor’s diagnosis, prescription, …
 Traditionally
 Go back to the same doctor, or
 Transfer the data
Computer networks can help here.
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Electronic Health Record (EHR) System
 Collect all information related to a patient in digital
format
 Universal access
 Doctor’s can access this data from anywhere
 More information  better decisions
 Less space to store
 Faster access
 Quick sharing/transfer
 Reduced possibility of some errors
 Easy to access and verify
 Great resource for research
 Data is extremely valuable in medical research
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Possible Concerns
 Requires many resources
 EHR system


Setup
Maintenance
 Network
 Doctor time to collect data
 Might introduce new types of errors
 Example?
 Privacy issues
 Who has access?
 Hackers, …
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Awareness
 Networks can help with raising awareness in healthcare
 Many resources available on the Web
 Information for specialists:


Medical journals, papers
PubMed, …
 Information for all


Symptoms, available treatments, side effects, …
WebMD, BabyCenter, …
 We have great search engines: Google, Bing, …
 Online forums and support groups
One should be careful about these resources.
 No need to be physically close
Not all are trustworthy.
 Low cost (time and money)
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University of Toronto – Fall 2015
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Outline
 Motivational example
 Information flow
 Networks and awareness
 How networking technology helps with healthcare
 Detour: sensor networks
 Science of networks
 Epidemic prediction/control
 Big Idea …
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University of Toronto – Fall 2015
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How Technology Made This Possible?
 Large and reliable storage
 Store high volumes of data at very low cost
 Small probability of error (or loss)
 High speed networks
 Make access possible
 To store and retrieve
 No need to store locally
 Large scale information management systems
 It is not just a pile of data
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New Forms of Data Collection
 Many medical devices today collect data in digital
format
 Networks can transfer and collect these data

Further analysis in EHR systems
 We can also collect data using non-traditional devices
 Sensor networks
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Sensor Networks
 Tiny electronic devices
 Equipped with a sensor to collect
 Temperature, humidity, …
 Use a wireless network to transfer data to a basestation
 Used to collect various forms of data with
applications in
 Wildlife, environment, military, health care, …
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Sensor Networks
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Sensor Networks – Connectivity
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Sensor Networks – Routing
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Sending Data to the Base Station
 What if nodes move constantly?
 For example in a highly dynamic environment
 We might not be able to find a path to send data to
the base station
 Even if we find a path, by the time we want to send
data it nodes might have moved.
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Volcano Routing Scheme (VRS)
 Basic idea: nodes locally
balance their load
 Send packets to your
neighbors …
 If you have more packets
than they do
 Idea comes from a
volcano
 Lava flows towards the
sea (low altitude)
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University of Toronto – Fall 2015
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Volcano Routing Scheme
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Multi-Flow Volcano Routing
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Outline
 Motivational example
 Information flow
 Networks and awareness
 How networking technology helps with healthcare
 Detour: sensor networks
 Science of networks
 Epidemic prediction/control
 Big Idea …
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University of Toronto – Fall 2015
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Science of Networks: Epidemics
 We can use the science of networks to predicting and
control epidemics
 Propagation of viruses similar to …
 Diffusion of information in social network
 In random networks
 Either the entire network is infected, or
 It dies out
 Depends on spreading rate
 Above a threshold  all nodes will be infected
 Below that threshold  spread will die out
 In scale-free networks however
 No epidemic threshold
 Steady state of small persistence rate
SII 199 - Computer Networks and Society
University of Toronto – Fall 2015
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Outline
 Motivational example
 Information flow
 Networks and awareness
 How networking technology helps with healthcare
 Detour: sensor networks
 Science of networks
 Epidemic prediction/control
 Big Idea …
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University of Toronto – Fall 2015
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The Big Idea …
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University of Toronto – Fall 2015
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Discussion
 Extremely valuable dataset
 What is the incentive of people to help?
 Can we create similar incentives in other situations?
 How reliable is the results gained from this system?
 Can doctors rely on the results?
 Do we need extra checks?
 Can we integrate a system like this with today’s online
social networks?
 Facebook maybe?
 What are the pros and cons?
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Summary and Discussion
 Computer networks are extremely useful in
healthcare
 Help with information flow
 Data collection
 Data management
…
 Assuming extremely fast networks, high capacity
storage, …
 What other areas can you think of?
 What are the technologies we need to work on today?
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University of Toronto – Fall 2015
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