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Technology Trends Sensors/actuators entering human habitats
32 million homes have security sensors 5 million homes have X10 devices Estimated 20 million ZigBee devices by EOY
We will need: To program them To debug them Privacy preservation Data stream processing
Macro-programming
for i = 1:100val = node[i].light.read();date = node[i].time();if val < 50
printf(“Error!”);else
hashtable.put(i,[val,date]);endpda.display(val);
end
RPC (marionette):
node
pda
node/server
pda/server
node
4
Macroprogramming
for i = 1:100val = node[i].light.read();date = node[i].time();if val < 50
printf(“Error!”);else
hashtable.put(i,[val,date]);endpda.display(val);
end
node
pda
node/server
pda/server
node
Automatic Decomposition:
Macroprogramming
for i = 1:100val = node[i].light.read();date = node[i].time();if val < 50
printf(“Error!”);else
hashtable.put(i,[val,date]);endpda.display(val);
end
node
pda
server
server
node
Automatic Decomposition:
6
Macroprogramming
for i = 1:100val = node[i].light.read();date = node[i].time();if val < 50
printf(“Error!”);else
hashtable.put(i,[val,date]);endpda.display(val);
end
node
pda
server
server
node
QoS Satisfaction: L < 350:
7
Macroprogramming
for i = 1:100val = node[i].light.read();date = node[i].time();if val > 50
printf(“Error!”);else
hashtable.put(i,[val,date]);endpda.display(val);
end
node
pda
server
server
node
QoS Satisfaction: L < 350:
8
Macroprogramming
for i = 1:100val = node[i].light.read();date = node[i].time();if val > 50
hashtable.put(i,[val,date]); else
printf(“Error!”);endpda.display(val);
end
node
pda
server
server
node
QoS Satisfaction: L < 350:
9
Macroprogramming
for i = 1:100val = node[i].light.read();date = node[i].time();if val > 50
hashtable.put(i,[val,date]); else
printf(“Error!”);endpda.display(val);
end
node
pda
pda
node
node
QoS Satisfaction: L < 350:
10
Macroprogramming
for i = 1:100val = node[i].light.read();date = node[i].time();if val > 50
hashtable.put(i,[val,date]); else
printf(“Error!”);endpda.display(val);
end
node
pda
pda
node
node
QoS Satisfaction: L < 350:
Macroprogramming
for i = 1:100val = node[i].light.read();date = node[i].time();if val < 50
printf(“Error!”);else
hashtable.put(i,[val,date]);endpda.display(val);
end
node
pda
server
server
node
QoS Satisfaction: L < 350:
Privacy Preservation
Home or away Awake or asleep Bathroom usage Kitchen usage Showering, toileting,
washing Cooking hot food or
preparing cold food
Preserving Privacy
),()|,(
),(
)()|,(),|(
)(),|(
FTPDFTP
FTP
DpDFTPFTDp
DPFTDP
Complete Privacy:
Bayes’ Rule:
Requirement For Privacy:
Counter Attacks Periodic Transmissions
Assumes tolerable latency bound L
Does not work with real-time or high bandwidth requirements
Consumes bandwidth Consumes power
Random Delays Exploit L with lower power
& bandwidth requirements Still assumes L
Counter Attacks Mask fingerprints in
hardware by varying features for each transmission Arms race scenario,
unable to predict features used by an adversary
Not supportable by current hardware
Does not affect inference of sleep and home occupancy variables
Counter Attacks Increasing Packet loss
ratio by: Reducing transmission
power Introducing RF
attenuators
Data Sharing Personal sensors are prevalent
Homes Cars Phones Shoes, etc
Goal: create infrastructure for sharing data & creating value
Shopkeepers publish data #people in front of store #people coming into store Credit card purchase info,
etc Entrepreneurs provide
service Effect of weather, concerts,
etc on business Effect of advertising How to increase conversion
rates, etc Plus…
Overall activity downtown Value of commercial real
estate Effect of vehicular traffic on
businesses, etc.
Search Search is key to data sharing PageRank
StreamRank mines the WWSW and creates links between data streams Correlation Ownership Browsing, etc