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Accelerated adoption of IoT
with In-network computing and Cloud
Mitesh Patel
Group Project Manager, Head – Internet of Things (IoT)
Manufacturing
InternetofThings
Network connectivity | Low latency | High availability | Low cost mobility
Everyonewantstojumponthebandwagon
andthisisjustthebeginning
2
Time
Challenges
Tolerance to disruption in
service /connectivity
Internet traffic
Low
High
…Computinginfrastructureisgettingstretched
Volume
Variety
Velocity
3
Real time Apps
Big Data Apps
UX ….
In-network
computing device
Compute Storage
Network
Healthcare
Devices
Edge network
Internet
Data Center
In- network computing
Manufacturing Buildings MiningLogistics
OilResidencesRetailAgriculture
Cloud computing
Manufacturing Buildings MiningLogistics
HealthcareOilResidencesRetailAgriculture
X ms
<<X ms
In-networkcomputing&cloudcomputing
4
• Compute near the edge of the
network / close to actual devices
• Smaller, less powerful devices can do
complex jobs
• Opportunity to convert compute
intensive application to internet
services
• Storage capability at the edge along
with computing makes it a self
sustained ecosystem reducing
external dependencies
Data Center
Network Core
Edge of the
network
In-networkcomputingwilloffloaddatacentercomputing
5
Data Center / Cloud
Core
Multi-Service Edge
Embedded Systems
and Sensors
Centralized
Intelligence
Network
Fabric
End Point
Intelligence
Easingnetworkdemandwillcreatespaceformoredevices
6
• Reduced traffic volume in higher
layers of the network
• Improved latency response
• Reduce availability stress on primary
data center
• Network load shaping lot easier
• Resilient network, no single point
failure except for last leg of network
• Build alternate paths
• Foundation for SDN (Software
Defined Networks)
Advantages:
• Network as a virtualized
service
• Extremely light edge /
application devices
• End devices can leverage
compute, storage, network as a
service
• Multiple service provider
tenants on a single device
Networking services
Wired / wireless front end
Compute
Storage
Real time OS
Real time
Applications
Device
Management
Services
Up
link
Down link
Application n
Application 2
Application 1
Virtualization
In-networkcomputingdeviceswillbehighlyvirtualized
7
In-network computing can be leveraged for several applications
Predictive Maintenance
Enable New Knowledge
Agriculture
Energy Saving
Transportation and
Connected Vehicles
Smart City
Intelligent Buildings
Enhance Safety and
Security
Healthcare
Industrial Automation
Smart HomeSmart Grid
8
In-network computing will increase IoT Adoption
Focus will shift from
device capability to
network capability
Multi tenant devices for
out of box industry specific
solutions will be possible
Enhanced network
security as ingest points
become smarter
Foundation for SDN
(Software Defined
Networks) implementation
Smarter, smaller &
cheaper end devices as
they leverage In-network
computing
Enable communication
without dependency on
core systems, will create
more natural ways of
communication
Systems tolerant to
disruption in connectivity
9
Expectations from technology
• High availability & low latency
networks, even with large consumer
base
• Long term technology
• Infrastructure to enable regulatory
compliance
• Tamper proof & IT security
Peak Clipping Conversation Load Building
Valley Filling Flexible Load
Shape
Load Shifting
Smartgridshavelottoofferbuttherearechallenges
Demand management is key for energy companies
10
Renewable energy is changing the grid dynamics with
more and more end users becoming power producers
(Client = Consumers + Producers). Further
proliferation in renewable energy sources will cause
accelerated change in this phenomenon
Renewable power needs to be handled differently, its
dependency on external / environmental factors,
consumption, generation, storage will generate a
demand for computing infrastructure to manage such
users / producers. In-network computing has the
ability to address this
Smartgrids:Newbreedofclients(consumers+producers)
11
• Connectivity, communication, and computation with
low latency
• Ability to deploy knowledge & algorithm based
solution and upgrade it on the fly in the field
• Client = consumer + producers, will make
contracting, billing complex and will require close
loop and advanced monitoring of distribution
• Real time analytics to match demand and supply will
be key success factor for distribution companies to
succeed
In-networkcomputingcanaddressSmartgridsneeds
12
In-network computing can simplify Smart Factory
implementation
Un-attended Production Cell
CNC
Machine
QC
center
In
~
.
Industrial Network
Make -> Check -> Go
Availability & Capability based
dynamic Job routing
Smart Factory Shop floor
• PLC / DCS / SCADA
• Safety systems
• Process control
• Motion control
• Telemetry
• End user selectable prioritization of network
traffic
• Intense computing application like condition
monitoring can compute & store data locally / on
edge devices
• Ready to use generic template based on specific
domains deployable on edge devices
• Resource and energy consumption monitoring
and control
• Ability to offer out of box features
13
Ethernet / Wireless
Enterprise Network
Business PlantPlant Control Network
• Event processing
• Time synchronization & triggering
• Segregation of priority traffic like
safety, compute and act locally
• Workflow & control system
• Mission critical applications
Ethernet / Wireless single
network connectivity for all
needs
• Motion control
• Quality & operations
• Safety
• Condition monitoring
• Workflow
In-networkcomputing canreducenetworkcomplexityfor
SmartFactory
14
© 2014 Infosys Limited, Bangalore, India. All Rights Reserved. Infosys believes the information in this document is accurate as of its publication date; such information is subject to change
without notice. Infosys acknowledges the proprietary rights of other companies to the trademarks, product names and such other intellectual property rights mentioned in this document. Except
as expressly permitted, neither this documentation nor any part of it may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, electronic, mechanical, printing,
photocopying, recording or otherwise, withoutthe prior permissionof Infosys Limitedand/ or any named intellectual property rights holders under this document.
Thank You

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Accelerated adoption of Internet of Things (IoT) with In-network computing and Cloud

  • 1. Accelerated adoption of IoT with In-network computing and Cloud Mitesh Patel Group Project Manager, Head – Internet of Things (IoT) Manufacturing
  • 2. InternetofThings Network connectivity | Low latency | High availability | Low cost mobility Everyonewantstojumponthebandwagon andthisisjustthebeginning 2
  • 3. Time Challenges Tolerance to disruption in service /connectivity Internet traffic Low High …Computinginfrastructureisgettingstretched Volume Variety Velocity 3
  • 4. Real time Apps Big Data Apps UX …. In-network computing device Compute Storage Network Healthcare Devices Edge network Internet Data Center In- network computing Manufacturing Buildings MiningLogistics OilResidencesRetailAgriculture Cloud computing Manufacturing Buildings MiningLogistics HealthcareOilResidencesRetailAgriculture X ms <<X ms In-networkcomputing&cloudcomputing 4
  • 5. • Compute near the edge of the network / close to actual devices • Smaller, less powerful devices can do complex jobs • Opportunity to convert compute intensive application to internet services • Storage capability at the edge along with computing makes it a self sustained ecosystem reducing external dependencies Data Center Network Core Edge of the network In-networkcomputingwilloffloaddatacentercomputing 5
  • 6. Data Center / Cloud Core Multi-Service Edge Embedded Systems and Sensors Centralized Intelligence Network Fabric End Point Intelligence Easingnetworkdemandwillcreatespaceformoredevices 6 • Reduced traffic volume in higher layers of the network • Improved latency response • Reduce availability stress on primary data center • Network load shaping lot easier • Resilient network, no single point failure except for last leg of network • Build alternate paths • Foundation for SDN (Software Defined Networks)
  • 7. Advantages: • Network as a virtualized service • Extremely light edge / application devices • End devices can leverage compute, storage, network as a service • Multiple service provider tenants on a single device Networking services Wired / wireless front end Compute Storage Real time OS Real time Applications Device Management Services Up link Down link Application n Application 2 Application 1 Virtualization In-networkcomputingdeviceswillbehighlyvirtualized 7
  • 8. In-network computing can be leveraged for several applications Predictive Maintenance Enable New Knowledge Agriculture Energy Saving Transportation and Connected Vehicles Smart City Intelligent Buildings Enhance Safety and Security Healthcare Industrial Automation Smart HomeSmart Grid 8
  • 9. In-network computing will increase IoT Adoption Focus will shift from device capability to network capability Multi tenant devices for out of box industry specific solutions will be possible Enhanced network security as ingest points become smarter Foundation for SDN (Software Defined Networks) implementation Smarter, smaller & cheaper end devices as they leverage In-network computing Enable communication without dependency on core systems, will create more natural ways of communication Systems tolerant to disruption in connectivity 9
  • 10. Expectations from technology • High availability & low latency networks, even with large consumer base • Long term technology • Infrastructure to enable regulatory compliance • Tamper proof & IT security Peak Clipping Conversation Load Building Valley Filling Flexible Load Shape Load Shifting Smartgridshavelottoofferbuttherearechallenges Demand management is key for energy companies 10
  • 11. Renewable energy is changing the grid dynamics with more and more end users becoming power producers (Client = Consumers + Producers). Further proliferation in renewable energy sources will cause accelerated change in this phenomenon Renewable power needs to be handled differently, its dependency on external / environmental factors, consumption, generation, storage will generate a demand for computing infrastructure to manage such users / producers. In-network computing has the ability to address this Smartgrids:Newbreedofclients(consumers+producers) 11
  • 12. • Connectivity, communication, and computation with low latency • Ability to deploy knowledge & algorithm based solution and upgrade it on the fly in the field • Client = consumer + producers, will make contracting, billing complex and will require close loop and advanced monitoring of distribution • Real time analytics to match demand and supply will be key success factor for distribution companies to succeed In-networkcomputingcanaddressSmartgridsneeds 12
  • 13. In-network computing can simplify Smart Factory implementation Un-attended Production Cell CNC Machine QC center In ~ . Industrial Network Make -> Check -> Go Availability & Capability based dynamic Job routing Smart Factory Shop floor • PLC / DCS / SCADA • Safety systems • Process control • Motion control • Telemetry • End user selectable prioritization of network traffic • Intense computing application like condition monitoring can compute & store data locally / on edge devices • Ready to use generic template based on specific domains deployable on edge devices • Resource and energy consumption monitoring and control • Ability to offer out of box features 13
  • 14. Ethernet / Wireless Enterprise Network Business PlantPlant Control Network • Event processing • Time synchronization & triggering • Segregation of priority traffic like safety, compute and act locally • Workflow & control system • Mission critical applications Ethernet / Wireless single network connectivity for all needs • Motion control • Quality & operations • Safety • Condition monitoring • Workflow In-networkcomputing canreducenetworkcomplexityfor SmartFactory 14
  • 15. © 2014 Infosys Limited, Bangalore, India. All Rights Reserved. Infosys believes the information in this document is accurate as of its publication date; such information is subject to change without notice. Infosys acknowledges the proprietary rights of other companies to the trademarks, product names and such other intellectual property rights mentioned in this document. Except as expressly permitted, neither this documentation nor any part of it may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, electronic, mechanical, printing, photocopying, recording or otherwise, withoutthe prior permissionof Infosys Limitedand/ or any named intellectual property rights holders under this document. Thank You