The Abstracted Network for Industrial Internet- Slides

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Taking cues from Nature, MeshDynamics is extending concepts outlined in the book “Rethinking the Internet of Things” to address challenges in supporting robust, real time, secure, scalable, subscribable messaging for our OEM licensees and their applications in Military and Industrial Internet (IIOT). Unclassified Section of Presentation. http://www.slideshare.net/DaCostaFrancis/the-abstracted-network-for-industrial-internet

Internet

The Abstracted Network
Applications of the Abstracted Network:
Disruption Tolerant Networks (Military)
Smart Networks (Enterprise)
Sharing Resources and Leveraging Open Source
Enterprise Class Messaging with Open Standards
Understanding Latency Requirements for Applications
Develop OEM Specialized Strategies and Templates for:
Internet of Things
Application-to-Application Networking
Real time Machine to Machine Communications
Low Cost IC Chips for IOT Chirp Devices
Shared Resource for Autonomous Network OEM Applications © 2002-2016 MeshDynamics. All Rights Reserved. 2
Traditional Networks Separate

Shared Resource for Autonomous Network OEM Applications © 2002-2016 MeshDynamics. All Rights Reserved. 3
Abstracted Network Emulates Separate Networks
Shared Resource for Autonomous Network OEM Applications © 2002-2016 MeshDynamics. All Rights Reserved. 4
Database Creates all Network Relationships
Manage:
•Latency
•Multicast
•Control Loops
•Protocol Translation

Shared Resource for Autonomous Network OEM Applications © 2002-2016 MeshDynamics. All Rights Reserved. 5
The Abstracted Network
Applications of the Abstracted Network:
Disruption Tolerant Networks (Military)
Smart Networks (Enterprise)
Sharing Resources and Leveraging Open Source
Enterprise Class Messaging with Open Standards
Understanding Latency Requirements for Applications
Develop OEM Specialized Strategies and Templates for:
Internet of Things
Application-to-Application Networking
Real time Machine to Machine Communications
Low Cost IC Chips for IOT Chirp Devices
Shared Resource for Autonomous Network OEM Applications © 2002-2016 MeshDynamics. All Rights Reserved. 6
Disruption Tolerance Maintains Connections
X
Nodes may move, disappear,
change ‐‐ network stays up

Shared Resource for Autonomous Network OEM Applications © 2002-2016 MeshDynamics. All Rights Reserved. 7
Disruption Tolerance Maintains Operation
X
Even if network lost completely,
local operations continue
X
Applications agent maintains
functions
Shared Resource for Autonomous Network OEM Applications © 2002-2016 MeshDynamics. All Rights Reserved. 8
Software Defined Networking
Enterprise control of
legacy applications
Publish/Discover/
Subscribe
Abstracted Network Offers Enterprise Tools Everywhere

Shared Resource for Autonomous Network OEM Applications © 2002-2016 MeshDynamics. All Rights Reserved. 9
Propagator NodesDevices
Integrators
(Big Data)
“Chirp”, legacy
protocols
Abstracted Network Connects Old and New IOT Devices
Shared Resource for Autonomous Network OEM Applications © 2002-2016 MeshDynamics. All Rights Reserved. 10
Sharp Smart Network Example

Shared Resource for Autonomous Network OEM Applications © 2002-2016 MeshDynamics. All Rights Reserved. 11
SPAWAR Autonomous Network Example
Shared Resource for Autonomous Network OEM Applications © 2002-2016 MeshDynamics. All Rights Reserved. 12
Intel Expects Alternatives to IP in the IOT

Shared Resource for Autonomous Network OEM Applications © 2002-2016 MeshDynamics. All Rights Reserved. 13
Intel Supporting MeshDynamics Propagator Model
Shared Resource for Autonomous Network OEM Applications © 2002-2016 MeshDynamics. All Rights Reserved. 14
Applications Running inside Propagator Network

Shared Resource for Autonomous Network OEM Applications © 2002-2016 MeshDynamics. All Rights Reserved. 15
(Autonomous) Applications Running on Mesh Node
Mesh Tables maintain these “ports”
.. Clients connected to “Ports”
..
Shared Resource for Autonomous Network OEM Applications © 2002-2016 MeshDynamics. All Rights Reserved. 16
(Autonomous) Applications Running on Mesh Node
M2M Virtual Network
Normal Operation
No Internet Connectivity
Mesh Tables maintain these “ports”
.. Clients connected to “Ports”
.. Applications resident in Network

Shared Resource for Autonomous Network OEM Applications © 2002-2016 MeshDynamics. All Rights Reserved. 17
NMS Displays Machine Status History
M2M Virtual Network
MachineStatusUpdates
(Autonomous) Applications Running on Mesh Node
Periodic Supervisory Control
Mesh Tables maintain these “ports”
.. Clients connected to “Ports”
.. Applications resident in Network
.. Intermittent Cloud Applications
Shared Resource for Autonomous Network OEM Applications © 2002-2016 MeshDynamics. All Rights Reserved. 18
The Abstracted Network
Applications of the Abstracted Network:
Disruption Tolerant Networks (Military)
Smart Networks (Enterprise)
Sharing Resources and Leveraging Open Source
Enterprise Class Messaging with Open Standards
Understanding Latency Requirements for Applications
Develop OEM Specialized Strategies and Templates for:
Internet of Things
Application-to-Application Networking
Real time Machine to Machine Communications
Low Cost IC Chips for IOT Chirp Devices

Shared Resource for Autonomous Network OEM Applications © 2002-2016 MeshDynamics. All Rights Reserved. 19
Objectives of Autonomous Network Test Bed
Shared Resource for Autonomous Network OEM Applications © 2002-2016 MeshDynamics. All Rights Reserved. 20
Managing Network Latency (Tree Topology)

Shared Resource for Autonomous Network OEM Applications © 2002-2016 MeshDynamics. All Rights Reserved. 21
Expected Arrival Time
Task Resource Allocation Period
Arrival Stack
Task Stack
Managing Application Latency (Task Scheduling)
Shared Resource for Autonomous Network OEM Applications © 2002-2016 MeshDynamics. All Rights Reserved. 22
Packets to-and-from end devices
Shuttles to/from
different destinations
Propagator Node (Edge Router)
“Shuttles” to/from
different integrator
functions
Chirps
unloaded/
reloaded
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.
Managing Real Time Enterprise Pub/Sub Messaging

Shared Resource for Autonomous Network OEM Applications © 2002-2016 MeshDynamics. All Rights Reserved. 23
BEACONING PERIOD
MAX : ~9.08 ms (16+16 SLOTS)
MIN : ~2.26 ms (4+4 SLOTS)
@ 55 mbps
CAP QTDMA
~40 ms SUPER FRAME
SPATIALLY RE-USED TDMA
~23 ms
CSMA/CA or EDCA ~15ms
Managing Latency at the 802.11 MAC Radio Level
Shared Resource for Autonomous Network OEM Applications © 2002-2016 MeshDynamics. All Rights Reserved. 24
Assume
1. we use QTDMA and CSM/RSCM.
2. Queues unloaded/loaded on 10 ms hard real time clock
3. Allocations are made within each Class of Service COS.
4. Within each COS there is a QOS to sort within COS Queue.
Then
1.Reconstruct Super Frame to order Sort inside Super Frame
2.In side super frame of any size, always 10 ms intervals
3.In example below 40 ms -> 4 10 ms intervals.
CAP TDMA
SPATIALLY RE-USED TDMA ~23 msCSMA/CA or EDCA ~15ms
BEACONING PERIOD
MAX : ~9.08 ms (16+16 SLOTS)
MIN : ~2.26 ms (4+4 SLOTS)
@ 55 mbps

Every 20 ms
Every 10 ms

Quasi-TDMA within IEEE 802.11 Protocols

Shared Resource for Autonomous Network OEM Applications © 2002-2016 MeshDynamics. All Rights Reserved. 25
QTDMA DURATION QTDMA DURATION QTDMA DURATION
Timed Concatenation State Machine (QTDMA)
Shared Resource for Autonomous Network OEM Applications © 2002-2016 MeshDynamics. All Rights Reserved. 26
Timed Concatenation State Machine (QTDMA)

Shared Resource for Autonomous Network OEM Applications © 2002-2016 MeshDynamics. All Rights Reserved. 27
The Abstracted Network
Applications of the Abstracted Network:
Disruption Tolerant Networks (Military)
Smart Networks (Enterprise)
Sharing Resources and Leveraging Open Source
Enterprise Class Messaging with Open Standards
Understanding Latency Requirements for Applications
Develop OEM Specialized Strategies and Templates for:
Internet of Things
Application-to-Application Networking
Real time Machine to Machine Communications
Low Cost IC Chips for IOT Chirp Devices

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The only systems on earth that have ever scaled to the size & scope of the Internet of things are natural systems: pollen distribution, ant colonies, redwoods, and so on. This proposal outlines how Massive IoT may be achieved by rethinking last mile connectivity. Today’s last mile is crippled by proprietary transport protocols, not sustainable. EdgeCloud thinking focused on smarts at the radio end to manage collision avoidance by segmenting collision domains in RF space (channel diversity) and time (time reservation slots). Current IoT Radios have to be “smart” because they use phones and computers as carrier pigeons to connect. These devices, intended for humans are rechargeable and thus not energy constrained. They can afford power hungry communication protocols. In order to communicate, the IoT edge devices must then also confirm to protocols and RF channels supported – or provide private networks. Conversely, in Cloud->Edge thinking, we let Clouds manage ant-like reprogrammable intelligence – purpose driven, minimal processing and thus low power usage and cheap. A 433 MHz wireless modem costs $0.10. A WiFi and Bluetooth wireless chipset costs $20. Also CSMA/CA protocols are inherently inefficient and insecure without “heavy” encryption on top of a heavy protocol. An IP header is 40 bytes vs. 1-2 bytes for Chirp headers. Chirp protocols and their minimal hardware cleanly cut through all Gordian knots in Fig. above. The Edge can be small dumb cheap and copious. Think sensor grids for forest fires, air and ocean pollution..Key Points addressed in this presentation relate to “CloudEdge” thinking. A. Global-Scale “Edge” challenges are: simplicity, cost, energy & (as always) security. B. Chirpers don’t need heavy OSI stack -> minimal power and cost for connectivity. C. Software Driven Mesh for the Edge -> Moves Chirping Edge Intelligence to Cloud. D. Trusted walled gardens become globally relevant through our imprinted chipsets. E. Massive IoT – burgeons with Cloud messaging and AI  Globally Relevant Solutions.Please see Chirp_Primer - intended as a prelude for these slides - for more. Thank you for your consideration. Your feedback is welcomed. Francis daCosta Jan 2024.

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Small, Dumb, ¬¬Cheap, and Copious – the Future of the Internet of Things, Abstract Over the next decade, billions of interconnected devices will be monitoring and responding to transportation systems, factories, farms, forests, utilities, soil and weather conditions, oceans, and other resources. The unique characteristic that the majority of these otherwise incredibly diverse Internet of Things (IOT) devices will share is that they will be too small, too dumb, too cheap, and too copious to use traditional networking protocols such as IPv6. For the same reasons, this tidal wave of IOT devices cannot be controlled by existing operational techniques and tools. Instead, lessons from Nature’s massive scale will guide a new architecture for the IOT. Taking cues from Nature, and in collaboration with our OEM licensees, MeshDynamics is extending concepts outlined in the book “Rethinking the Internet of Things” to real-world problems of supporting “smart: secure and scalable” IOT Machine-to-Machine (M2M) communities at the edge. Simple devices, speaking simply Today companies view the IOT as an extension of current networking protocols and practices. But those on the front lines of the Industrial Internet of Things are seeing problems already: “While much of the ink spilled today is about evolutionary improvements using modern IT technologies to address traditional operational technology concerns, the real business impact will be to expand our horizon of addressable concerns. Traditional operational technology has focused on process correctness and safety; traditional IT has focused on time to market and, as a recent concern, security. Both disciplines have developed in a world of relative scarcity, with perhaps hundreds of devices interconnected to perform specific tasks. The future, however, points toward billions of devices and tasks that change by the millisecond under autonomous control, and are so distributed they cannot be tracked by any individual. Our existing processes for ensuring safety, security and management break down when faced with such scale. Stimulating the redevelopment of our technologies for this new world is a focal point for the Industrial Internet Consortium.”

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MeshDynamics has enhanced its industry-leading MD4000 third generation WiFi wireless mesh nodes with new features offering better performance and reliability in mobile or mixed fixed/mobile environments. The new software, called Persistent 3rd-Generation Mesh (P3M) is intended for dynamic military, transportation, and public safety applications, as well as in critical applications such as mine safety. In recent tests, the company demonstrated persistent high-throughput and low-delay and low-jitter networking as mobile wireless mesh nodes connected automatically with other mobile and fixed wireless mesh nodes. As some elements of the network moved out of WiFi range from other nodes, they automatically formed into separate independent networks, allowing communication to continue. When brought back into range, these network elements seamlessly reconnected with the rest of the network. All of this occurred without any operator intervention or reconfiguration and the process takes place in a fraction of a second. MeshDynamics MD4000 nodes are already being used in tactical battlefield environments to transmit video, voice, and sensor data between moving armored vehicles. The new P3M features now allow for smaller groups that become separated from the main formation or column to maintain the same high performance among themselves while isolated, and then automatically rejoin the larger force when they again come into range. The P3M features have also been proven in demanding underground mining environments, where possible cave-ins and other disasters may lead to a section of the network becoming isolated from the main portion of the network. With P3M technology, miners in the isolated sections may still communicate with one another, providing persistent Voice-over-IP and location capabilities and potentially speeding rescue. Third-generation wireless mesh networking has always delivered higher performance in rooted environments than does traditional wireless mesh technology. This is primarily achieved through imposing a logical Structured MeshTM topology on the mesh network, with uplink and downlink paths minimizing turnaround and multiple radios optimizing performance. Typically, the "uplink" and "downlink" determinations have been made by the nodes themselves at network start-up, based on the location of the fixed fiber or copper connection to the Internet or enterprise backbone. But the new P3M technology allows the nodes to structure the network dynamically, even if there is no fixed connection anywhere in the network or if the fixed connection is lost. Patent-pending route-finding algorithms permit the nodes to establish the optimal topology rapidly and to reconfigure quickly as nodes move in relation to one another and any fixed points. This allows for persistent high-performance networking, regardless of the topology formed by the mobile nodes.

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MeshDynamics

MeshDynamics provides the network infrastructure to make a fully distributed IP surveillance system possible for cameras, video servers, storage clusters, custom applications and remote viewing to be located in any location. The Department of Homeland Security (DHS) and SPAWAR engineers selected MeshDynamics Wi-Fi mesh nodes to provide remote video surveillance for stationary and vehicle mounted cameras along the US national border. IP cameras are connected to the MeshDynamics MD4000 mesh nodes transmitting high resolution real time video over the mesh network to the base station video monitors. Live video feeds from the IP based cameras is also available via the MeshDynamics mesh network to patrol vehicles with wireless access. Mobile nodes mounted in security forces vehicles join the network dynamically and while in motion. Service radios in the vehicles provide connectivity for staff in vehicles and operating nearby. In similar applications, UK, Israeli and Canadian defense agencies have also selected MeshDynamics for wireless video surveillance applications in those countries

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The presentation of the talk "Solid Pods Vs Personal Knowledge Graphs: Similarities and Differences" that was given by the PhD researcher Eleni Ilkou, in the 2nd Solid Symposium. Abstract: Solid Pods and Personal Knowledge Graphs are pioneering constructs within the Semantic Web community, each offering unique avenues for empowering individuals in the digital realm. Solid Pods stand as decentralized bastions of data control which grant users unprecedented authority over their digital presence, ensuring ownership, privacy and portability of personal data. Personal Knowledge Graphs infuse personal data and activity with contextual relevance, facilitating the synthesis and discovery of knowledge. This presentation aims to briefly reflect on the main similarities and differences among the Solid Pods and Personal Knowledge Graphs.

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