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ECE 590/COMPSI 590
Special Topics: Edge Computing
Lecture date:
Wednesday August 29th, 2018
IoT Meets the Cloud:
The Origins of Edge Computing
Last Class: Introduction to Edge
• Edge computing
Advantages: latency, bandwidth, privacy
Different devices
Different degree of application centralization
• Research themes
2
Barcelona PoC Deployment
3A New Era for Cities with Fog Computing, Yannuzzii et al
Edge Computing at Chick-fil-A (1/2)
4
July 2018
Edge Computing at Chick-fil-A (2/2)
5
This Class
• Path towards the edge: Cloud computing
• Path towards the edge: Internet of Things
• Modern multi-tier architectures
6
Edge: IoT Meets the Cloud
7
The Pendulum
8
The Cloud: Applications and Providers
• Amazon Web Services,
Microsoft Azure, Google Cloud,
IBM Cloud
• Virtual machines, of different
grades
• An endless, always updating
list of specialized services
9
Cloud Centralization: AWS Example
10
Cloud Centralization:
Microsoft Azure Example
11
The Cloud: Massive Operation (1/2)
12
The Cloud: Massive Operation (2/2)
13
The Cloud: Shared Substrate
• Shared servers
• Shared cores
• Shared network
14
Cloud: Some of the Properties
• Geographically centralized
• Massive, scalable
• Managed, physically secure
• Shared
• Cloud outages are uncommon
• … but task latency variations are the norm
• …
15
Side Note: Cloud as an Enabler of
Vibrant Web Ecosystem
• Spurred innovation
• Perhaps, edge doing
the same for the IoT?
16
Edge Precursors: CDNs (1/3)
• Content Delivery Networks
Akamai, AWS CloudFront, Fastly
• Original “edge nodes”
17
Edge Precursors: CDNs (2/3)
• Content Delivery Networks - static content replication
• Fewer points than in edge computing settings
 E.g., Akamai: ~200,000, AWS CloudFront: 100 POPs
18
Edge Precursors: CDNs (3/3)
• Interesting new development (2017): using CDNs to
customize web server responses via Lambda@Edge
• Possible research project: extending CDN mechanisms
to edge computing
19
Edge Precursors: Peer-to-Peer
• P2P: Napster, Kazaa,
Bitcoin
• File sharing
• Focused on
decentralization
mechanisms above all
20
Related Area, for Some Edge Research:
Distributed Workloads on the Cloud
• … and in multi-core systems
• Homogenous substrates
• Non-responsive operations
21
• Research projects on edge analytics need to be specific
about the differences in their settings and traditional ones
Intellectual Heritage: Distributed Clouds
22
Edge: IoT Meets the Cloud
23
This Class
• Path towards the edge: Cloud computing
• Path towards the edge: Internet of Things
• Modern multi-tier architectures
24
History: IoT
• Devices  smart devices  connected devices
Thanks, Moore’s Law!
25
For Example, Towards IoT:
Evolution of a Smart Watch
• CES 2016
26
Side Note: By Now, Modern Cars Are
All Electronics
27
Side Note: Progress in the IoT is
Limited by Energy Storage
• No Moore’s Law for batteries
28
IoT Properties (1/3)
• Tightly constrained design space
Often specialized for the application
Proliferation of protocols and vendor-specific
solutions
29
IoT Properties (2/3)
• Low computing capacity
E.g., laptop: 2.4 GHz, Raspberry Pi: 1.2 GHz, Arduino
Due: 0.084 GHz, Amazon Dash Button: 0.016 GHz
• Minimized/reduced energy consumption
• Difficult to secure
• …
30
Edge Precursors:
Mobile Ad Hoc and Sensor Networks
• Focused on sensing
31
Sensor Network Example: ZebraNet
• Early 2000s
32
Sensor Network Example: RoombaNet
33
Sensor Networks:
Focused on Multi-hop Connectivity
34
Industry Approach:
3-Tier Architectures Instead of Multihopping
• Sensors → gateway → cloud
35
Edge and Sensor Networks:
Differences
• Research projects on resource discovery and peer
assistance in edge need to be explicit about the
differences in their settings and traditional ones 36
• No consideration of the cloud
• No multi-point decision-making
This Class
• Path towards the edge: Cloud computing
• Path towards the edge: Internet of Things
• Modern and envisioned multi-tier
architectures
37
Barcelona PoC Deployment
38A New Era for Cities with Fog Computing, Yannuzzii et al
Multi-tier Architectures
39
40
Smart city fog deployment: buildings, neighborhoods, regions
connected with each other
Example Use Case: Securing Air Travel
• Multiple locations need to work
together
• Cameras important part of the
system
 1 Tb/day/camera
• Immediate action needed
• Applications deployed: risk
scoring, vehicle capture, baggage
capture Airport terminal provisioned with a hierarchy of fog
nodes
Current Platforms: AWS Greengrass
42
Released June 2017
Edge Properties
• Decision-making, actuation
• Data manipulations and transformations
• Heterogeneity
• Hierarchy
Cloud is involved in the system
• …
43
Class Recap
• Origins of the edge, on the cloud side:
CDNs, P2P systems
• Origins of the edge, on the IoT side
Sensor networks
• Properties of edge systems
44
ECE 590/COMPSI 590
Special Topics: Edge Computing
Lecture date:
Wednesday August 29th, 2018
IoT Meets the Cloud:
The Origins of Edge Computing

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ECE 590 Lecture on Origins of Edge Computing

  • 1. ECE 590/COMPSI 590 Special Topics: Edge Computing Lecture date: Wednesday August 29th, 2018 IoT Meets the Cloud: The Origins of Edge Computing
  • 2. Last Class: Introduction to Edge • Edge computing Advantages: latency, bandwidth, privacy Different devices Different degree of application centralization • Research themes 2
  • 3. Barcelona PoC Deployment 3A New Era for Cities with Fog Computing, Yannuzzii et al
  • 4. Edge Computing at Chick-fil-A (1/2) 4 July 2018
  • 5. Edge Computing at Chick-fil-A (2/2) 5
  • 6. This Class • Path towards the edge: Cloud computing • Path towards the edge: Internet of Things • Modern multi-tier architectures 6
  • 7. Edge: IoT Meets the Cloud 7
  • 9. The Cloud: Applications and Providers • Amazon Web Services, Microsoft Azure, Google Cloud, IBM Cloud • Virtual machines, of different grades • An endless, always updating list of specialized services 9
  • 12. The Cloud: Massive Operation (1/2) 12
  • 13. The Cloud: Massive Operation (2/2) 13
  • 14. The Cloud: Shared Substrate • Shared servers • Shared cores • Shared network 14
  • 15. Cloud: Some of the Properties • Geographically centralized • Massive, scalable • Managed, physically secure • Shared • Cloud outages are uncommon • … but task latency variations are the norm • … 15
  • 16. Side Note: Cloud as an Enabler of Vibrant Web Ecosystem • Spurred innovation • Perhaps, edge doing the same for the IoT? 16
  • 17. Edge Precursors: CDNs (1/3) • Content Delivery Networks Akamai, AWS CloudFront, Fastly • Original “edge nodes” 17
  • 18. Edge Precursors: CDNs (2/3) • Content Delivery Networks - static content replication • Fewer points than in edge computing settings  E.g., Akamai: ~200,000, AWS CloudFront: 100 POPs 18
  • 19. Edge Precursors: CDNs (3/3) • Interesting new development (2017): using CDNs to customize web server responses via Lambda@Edge • Possible research project: extending CDN mechanisms to edge computing 19
  • 20. Edge Precursors: Peer-to-Peer • P2P: Napster, Kazaa, Bitcoin • File sharing • Focused on decentralization mechanisms above all 20
  • 21. Related Area, for Some Edge Research: Distributed Workloads on the Cloud • … and in multi-core systems • Homogenous substrates • Non-responsive operations 21 • Research projects on edge analytics need to be specific about the differences in their settings and traditional ones
  • 23. Edge: IoT Meets the Cloud 23
  • 24. This Class • Path towards the edge: Cloud computing • Path towards the edge: Internet of Things • Modern multi-tier architectures 24
  • 25. History: IoT • Devices  smart devices  connected devices Thanks, Moore’s Law! 25
  • 26. For Example, Towards IoT: Evolution of a Smart Watch • CES 2016 26
  • 27. Side Note: By Now, Modern Cars Are All Electronics 27
  • 28. Side Note: Progress in the IoT is Limited by Energy Storage • No Moore’s Law for batteries 28
  • 29. IoT Properties (1/3) • Tightly constrained design space Often specialized for the application Proliferation of protocols and vendor-specific solutions 29
  • 30. IoT Properties (2/3) • Low computing capacity E.g., laptop: 2.4 GHz, Raspberry Pi: 1.2 GHz, Arduino Due: 0.084 GHz, Amazon Dash Button: 0.016 GHz • Minimized/reduced energy consumption • Difficult to secure • … 30
  • 31. Edge Precursors: Mobile Ad Hoc and Sensor Networks • Focused on sensing 31
  • 32. Sensor Network Example: ZebraNet • Early 2000s 32
  • 33. Sensor Network Example: RoombaNet 33
  • 34. Sensor Networks: Focused on Multi-hop Connectivity 34
  • 35. Industry Approach: 3-Tier Architectures Instead of Multihopping • Sensors → gateway → cloud 35
  • 36. Edge and Sensor Networks: Differences • Research projects on resource discovery and peer assistance in edge need to be explicit about the differences in their settings and traditional ones 36 • No consideration of the cloud • No multi-point decision-making
  • 37. This Class • Path towards the edge: Cloud computing • Path towards the edge: Internet of Things • Modern and envisioned multi-tier architectures 37
  • 38. Barcelona PoC Deployment 38A New Era for Cities with Fog Computing, Yannuzzii et al
  • 40. 40 Smart city fog deployment: buildings, neighborhoods, regions connected with each other
  • 41. Example Use Case: Securing Air Travel • Multiple locations need to work together • Cameras important part of the system  1 Tb/day/camera • Immediate action needed • Applications deployed: risk scoring, vehicle capture, baggage capture Airport terminal provisioned with a hierarchy of fog nodes
  • 42. Current Platforms: AWS Greengrass 42 Released June 2017
  • 43. Edge Properties • Decision-making, actuation • Data manipulations and transformations • Heterogeneity • Hierarchy Cloud is involved in the system • … 43
  • 44. Class Recap • Origins of the edge, on the cloud side: CDNs, P2P systems • Origins of the edge, on the IoT side Sensor networks • Properties of edge systems 44
  • 45. ECE 590/COMPSI 590 Special Topics: Edge Computing Lecture date: Wednesday August 29th, 2018 IoT Meets the Cloud: The Origins of Edge Computing