Describes an architecture for doing distributed computing in the Internet of Things (IoT) and integrates it with the larger Internet.

1. ™
Fog Lifter
Bill Worzel
CEO, Fog Lifter
Advisor, Kwaai Oak
billw@fog-lifter.com bill@kwaaioak.com

2. Imagine that this is the biggest
supercomputer in the world...

3. ...and this is how you control it

4. How We Use The
Internet Now
Like drinking the
sea through a
straw

5. Combinatorics
• The IoT creates an impossible task: Finding,
collecting and analyzing data in real time
from a large number of devices
• There are n! ways to combine n devices.

6. IoT Device Growth
• It is estimated that there were 12B devices
shipped in 2013 and that there will be at
least 40B devices in 2025

7. Growth of Computing
Power
• Moore’s law states that computing power
increases in speed by a factor of 2 every 2
years

8. Combinatorics Beats
Moore’s Law

9. What This Means
• Even with huge data centers and Moore’s
Law, analytics can’t locate, gather, and
analyze the volume of data that’s coming

10. Fog Computing
• Fog Computing pushes computing out to the
edge of the Internet, such as in cars that analyze
what’s happening around them

11. Fog Lifter: Compute
Locally,Analyze Globally
• Organizes local, dynamic, distributed
computing
• Designed for intermittent connectivity
• Processes data locally and makes results
available globally
• Data that reaches data centers will be
processed multiple times (vertically
distributed analytics)

12. Fog Lifter Platform
• Functional Relational Programming
• F-code compiler and evaluator
• Relational rules and constraint checker
• P2P architecture at the Edge
• Work Flow Description
• Data Registry
• Security and Privacy

13. F-Code Is Portable Code
For Fog Computing
• A type of p-code: Functional code that can be
executed on any platform, like Java or Python
• Why functional code? It enables parallel
processing in the Fog
• Each expression can be independently
evaluated with no change in result

14. F-Code Uses Combinators
• S, K, I, B, C,Y
• S f g x –> f x (g x) // distributes expression x into
expressions f an g
• K f g –> f // selects f from f g expression
• I x –> x // Identity
• B f g x –> f (g x) // re-distribute evaluation
• C f g x –> f x g // re-order evaluation
• Y x –> x (Y x) // recursion

15. F-code Compiler
• Can compile any pure functional language
program into F-code
• Programs are compiled to combinator
expressions
• Expressions can be distributed across
devices and results safely recombined
Y (B (S (C B ? (= 0)) 1) (B (S *) (C B (C - 1))))

16. Relational Programming
• Integrating data from many sources
requires careful coding
• Functional Relational Programming (FRP)
uses relational algebra to constrain
unintended complexity of functions
• Reduces chance of errors
• FRP already in use in large scale analytics

17. Peer-to-Peer Connectivity
• Supports dynamic environment since edge
devices come and go
• Devices share data and computation
• Results can be part of larger computation
Tex
t
E2E1 E3
E4E5

18. Work Flow Design
• Maps data flow and computation across the
Internet in order to leverage parallel processing
• Data centers will analyze results of edge
computing rather transferring terabytes of data
Enterprise DataWorkflows with Cascading O’Reilly (2013)

19. Data Registry
• Provides semantic description of the data
• Also contains data dictionary
• Provides information about computed
results and optionally raw data
• Conforms to relational model

20. Security and Privacy
• Data and results must be
secure from hacking by building
in heavy encryption
• Control of data must reside
with owner of the data or basic
trust is missing
• Permission must be an act of
commission, not omission

21. When Is Fog Lifter
Most Useful?
• When analyzing high volume of data from
many different sources
• When local result is needed quickly from
surrounding environment
• When there is intermittent or low-
bandwidth connectivity
• When the same computations are used for
multiple purposes

22. Example: Smart Traffic
Car
Car Car Car
CarCarCar
CarCar
Cars plot route
from interactive
algorithm
Smart
Road
Smart
Road
Smart
Road
Smart
Road
Roads track
car flow
Traffic control
integrates routes
and flow
City planners
design infrastructure
changes
Car

23. Example: Local Smart Grid
Aggregates data to predict power demand based on conditions such
as weather, current demand, sources, and past behavior. This allows
development of local power coop with dynamic load balancing using
local storage and interfacing with smart grid.
Smart House
PV eCar Controls
Smart House
PV eCar Controls
Smart House
PV eCar Controls
Smart Grid

24. Example: Shopping
Smart
Phone
Smart
Phone
Smart
Phone
Smart
Phone
Smart
Phone
Shopping Mall
Store1
Store2
Store3
Store4
• Picture processing is distributed among phones
• Stores send images of similar products
• Results and locations are displayed
• Stores track product queries, improving inventory control

25. Example: Home
Healthcare
•Integrate health
factors over time
•Generate health
metric
•Upload results of
analysis to health
record
•Alert user and MD
of health problems
Heart
Rate
Glucose
Vascular
Health
Blood
Pressure
Exercise
Thera-
peutics

26. Example: Farming
Vertical Aggregation
Farm Field Sensors
eg salinization
Farm Equipment
eg tractor
Data Harvesters
eg aerostats
Farm Data Center
Farm Coop Farm 1 Farm 2 Farm 3 Farm 4
Region Crop Insurance Markets
Equipment
Suppliers/Hire
Local Distribution/
CSAs

27. Example: Farming
Horizontal Aggregation
Water Usage
Patterns
Weather/Field
Dynamics
Pest Dynamics Yield Projections
Water Use Planning Ag Market Analysis
Insurance
Companies
NGOs

28. Fog Lifter Summary
• For Lifter changes the Fog from a collection
of devices to a dynamic computing system
• FRP provides a common language with error
control
• Work flow design maps computation using
locations described by Registry
• Security and Privacy controls increases safety
and confidence of users

29. The Sea Comes To Shore
Fog Lifter allows the Internet to
become part of all data centers

30. Fog Lifter
• The first components of Fog Lifter will be
available in 2015
• For more information, contact Bill Worzel at
billw@fog-lifter.com or call 734-276-9333
™