The Cloudy, Foggy and Misty Internet of Things -- Toward Fluid IoT Architectures
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Transcript of The Cloudy, Foggy and Misty Internet of Things -- Toward Fluid IoT Architectures
![Page 1: The Cloudy, Foggy and Misty Internet of Things -- Toward Fluid IoT Architectures](https://reader031.fdocuments.in/reader031/viewer/2022030316/5879efbb1a28ab70298b46fd/html5/thumbnails/1.jpg)
The Cloudy, Foggy and Misty Internet of Things Toward Fluid IoT Architectures
AngeloCorsaro,PhDChiefTechnologyOfficer
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This slides have been crafted by Angelo Corsaro
Any use of these slides that does include me as Author/Co-Author is plagiaryIoT Architectures’ Evolution
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This slides have been crafted by Angelo Corsaro
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The majority of IoT systems are today cloud-centric
These systems are characterised by device-to-
cloud communication and in-cloud analytics
Cloud-Centric Architectures
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Cloud-Centric IoT Platforms
The large majority of IoT platform have been built
with Cloud-Centric architectures in mind
AWS IoT
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This slides have been crafted by Angelo Corsaro
Any use of these slides that does include me as Author/Co-Author is plagiaryChallenges
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*IDC
*CISCO
CISCO estimates an average of 6.6 devices per person leading to 50B devices in
2020.
Too many Devices
IDC estimates 27.9 devices per person leading to 212B
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Industrial IoT applications such as Smart Grids , Smart
Factories, Smart Farming, Connected Vehicles and Smart
Cities are not compatible with the assumptions of Cloud
Centric Architectures
Industrial IoT
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There is sufficient bandwidth to push data to
the Cloud.
Cloud-Centric Architectures Assumption #1
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Smart Factory0.5 TB of data
produced per day
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This slides have been crafted by Angelo Corsaro
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issue. A device will (almost) always be connected to the
cloud.
Cloud-Centric Architectures Assumption #2
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Autonomous Vehicles
coordination of fast moving autonomous vehicles
intermittent connectivity
dynamic pairing of devices
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This slides have been crafted by Angelo Corsaro
Any use of these slides that does include me as Author/Co-Author is plagiaryThe latency induced by
cloud-centralised analytics and control is compatible
with the dynamic of the IoT system
Cloud-Centric Architectures Assumption #3
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Any use of these slides that does include me as Author/Co-Author is plagiaryLatency
Constraints
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The connectivity cost is negligible
Cloud-Centric Architectures Assumption #4
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Cost of connectivity is an issue in Smart Grids as the operator has to pay for the
2G/3G/4G data-link
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comfortable in exposing their data to the cloud.
Cloud-Centric Architectures Assumption #5
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Fog-Centric Architectures
fogfogfog
cloud
Fog Computing Architectures extend
elastic compute, networking and storage across the cloud through
to the edge of the network
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Fog/MEC-Centric IoT Platforms
IoT Platforms support for Fog /MEC computing is
rapidly emerging
IOx
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OpenFog Consortium
The recently established OpenFog is accelerating
and facilitating the expansion, convergence
and interoperability of Fog computing infrastructures
[source: OpenFog Whitepaper http://bit.ly/openfog-wp]
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This slides have been crafted by Angelo Corsaro
Any use of these slides that does include me as Author/Co-Author is plagiaryChallenges
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[most of] Fog centric infrastructures rely on
edge servers to provide elastic compute, store and communicate abstractions.
Yet, are incapable of exploiting resources
available on the Things
What about the Things?
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Mist-Centric Architectures
fogfogfog
cloud
mist mistmist
Mist Computing Architectures extend elastic compute, networking and
storage across the Fog through to the Things
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Any use of these slides that does include me as Author/Co-Author is plagiarycloudy…foggy…misty…
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This slides have been crafted by Angelo Corsaro
Any use of these slides that does include me as Author/Co-Author is plagiaryLet’s do some more analysis
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This slides have been crafted by Angelo Corsaro
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Mist
Fog
Cloud
Things
Fog Nodes
Cloud Servers
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Provisioning, deployment & Management
Applica
tion
Bundle
Conta
iner
VM
The unit of provisioning and deployment
supported by Cloud, Fog and Mist infrastructure
are different
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time
nownow-t
near pastpast
data flow
Data in MovementData at Rest
Data Stores Data Streams
Data Access
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Memory hierarchyEveryone gives for granted
that the memory hierarchy present in
computing systems should be transparent
Why shouldn't the same be true for data access in IoT
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AnalyticsDifferent analytics
technologies are applicable for Cloud, Fog
and Mist Computing
As a result there is no decoupling between the
algorithm and the deployment!
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Map/Reduce applicability
Most analytics framework built for cloud are based on
Map/Reduce
Map/Reduce is applicable to embarrassing parallel
computational problems. These are a small subset of
analytics required in IoT!
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This slides have been crafted by Angelo Corsaro
Any use of these slides that does include me as Author/Co-Author is plagiaryWhat’s the Answer?
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Architectural consistency and composability is key
to scale
A unifying architectural principle should be the
reference for IoT Platforms
Architectural consistency
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FLUID IOT Architecture
The Fluid IoT Architecture eliminates the
technological segregation created by Cloud, Fog and
Mist technologies and abstracts compute, storage and networking end-to-end
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FLUID IOT PlatformAllow users to express, provision and manage
computations operating over virtualised resources (e.g.
devices) and data (potentially loads of these)
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Storage Compute Networking
Data Virtualisation
Analytics
Node Monitoring & Management OS
HW
Nod
e v
irtua
lisat
ion
Verti
cal
Ser
vice
s
Preventive Maintenance
…
Applications
Plat
form
v
irtua
lisat
ion
I/O
Secu
rity
Platform Management
Traffic Management
Smart City Management
Visualisation
Secu
rity
IOT PlatformThe Fluid IoT
Platform virtualises resources end-to-end
and unifies abstractions
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FLUID IOT PlatformFluid IoT Platform will provide
uniform abstractions to provision, manage and
deploy applications
Fluid IoT will virtualise data access and unify analytics across Cloud, Fog and Mist
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Provisioning, deployment & Management
“Fluid”
Bundle
A Fluid IoT Platform provides a uniform way of
provisioning, deploying and managing bundles across computational resources that may be available on
Things, Edge Nodes of IaaS
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time
nownow-t
near pastpast
data flow
Data in MovementData at RestData Stores Data Streams
Data AccessVirtualised Data Streams
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AnalyticsA Fluid IoT platform allows
to define Analysts independently of their
deployment
This strongly leverages the Data Virtualisation
provided by the platform
“Fluid”
Analyti
c
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