1. Challenge: Legacy and IOT Integration with - Scalability
- Synchronicity
Introducing: The Abstracted Network
The Abstracted Network is discussed. Its applications in two seemingly disparate Industry Segments is explored.

2. Challenge: Different needs for Legacy and IoT
Billions of legacy controllers, appliances, actuators, and sensors. Integration of legacy protocols and supporting deterministic latencies etc.
Enterprises also want to extend SDN-like capabilities to edge Silos must be integrated and addressable within framework
Emerging IoT applications will involve trillions of new devices. Some, too dumb, cheap and copious to manage via traditional means
IP can’t be the lingua franca for all. New Protocols will evolve Many devices lack memory, processor – and unmanageable
Challenges
How to keep performance predictable?
How to keep systems scalable ?

3. Challenge: Scalability and Synchronicity
Performance – must solve O(n2) problem
Proposed: Logical tree, virtual mesh network is O (n)
Management – extending Enterprise tools via SDN Proposed: M2M communications need Device/Protocol Abstractions.
Scope – can’t address every device individually
Proposed: Dumb devices, smarter aggregators/propagators
Value – most data is redundant or uninteresting
Proposed: Time Sensitive Publish/discover/subscribe architecture
Control Loop Latencies for round trip (device to Cloud) Proposed: Uncouple local response loops from enterprise-wide round-trip

4. Traditional Networks Separate

5. Abstracted Network Emulates Separate Networks

6. Abstracted Network Connects Old and New IOT Devices
“Chirp”, legacy protocols
Integrators
(Big Data)
Devices
Propagator Nodes

7. Database Creates all Network Relationships
Manage:
Latency
Multicast
Control Loops
Protocol Translation

8. Challenge: Scalability cannot be O(n2)
From SLIC-RTI-Barcelona

9. Data Driven Architectures Scale O(n)
From SLIC-RTI-Barcelona

10. Propagator Mesh Network
Scalable Tree Based Abstracted Architecture
Filter
Gateway
Integrator Function
Propagator Mesh Network
End Devices
Chirp Data Streams
“Small” Data Flows
“Big Data” Analysis

11. Synchronicity: Machine Controllers in Propagators
Local Machine controllers orchestrate sensor, actuator interactions

12. (Autonomous) Applications Running on Mesh Node
Mesh Tables maintain these “ports”
.. Clients connected to “Ports” ..

13. (Autonomous) Applications Running on Mesh Node
Mesh Tables maintain these “ports”
.. Clients connected to “Ports”
.. Applications resident in Network
M2M Virtual Network
Normal Operation
No Internet Connectivity

14. (Autonomous) Applications Running on Mesh Node
NMS Displays Machine Status History
Mesh Tables maintain these “ports”
.. Clients connected to “Ports”
.. Applications resident in Network
.. Intermittent Cloud Applications
Machine Status Updates
M2M Virtual Network
Periodic Supervisory Control

15. Propagator Node (Edge Router)
Managing Latency Sensitive M2M Pub/Sub Messaging
Propagator Node (Edge Router)
Packets to-and-from end devices
“Shuttles” to/from different integrator functions
Chirps unloaded/ reloaded
Shuttles to/from different destinations
Application: Real Time Publishing of applications/devices data flows to Subscribers/Applications
. Pub/Sub framework with periodic, timed, “shuttle” service between publishers/subscriber apps.
.. Applications ingress and egress ports monitored by supervisory audit/management subscribers.

16. SPAWAR Autonomous Network Example

17. Sharp Smart Enterprise Network Example

18. Objectives of Autonomous Network Test Bed

19. Links and References
The Abstracted Network
Chirp Networks
Rethinking the Internet of Things (APress Publications)