Accelerated adoption of IoT with In-network computing and Cloud
Mitesh Patel Group Project Manager, Head – Internet of Things (IoT) Manufacturing
Internet of Things
Network connectivity | Low latency | High availability | Low cost mobility
Everyone wants to jump on the bandwagon and this is just the beginning
2
Time
Challenges
Tolerance to disruption in service /connectivity
Internet traffic
Low
High
…Computing infrastructure is getting stretched
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 Mining Logistics
Oil Residences Retail Agriculture
Cloud computing
Manufacturing Buildings Mining Logistics
Healthcare Oil Residences Retail Agriculture
X ms
<<X ms
In-network computing & cloud computing 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-network computing will offload data center computing 5
Data Center / Cloud
Core
Multi-Service Edge
Embedded Systems and Sensors
Centralized Intelligence
Network Fabric
End Point Intelligence
Easing network demand will create space for more devices 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 D
evic
e M
anag
emen
t Se
rvic
es
Up link
Down link
Application n
Application 2
Application 1
Virtualization
In-network computing devices will be highly virtualized 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 Home Smart 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
Smart grids have lot to offer but there are challenges
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
Smart grids: New breed of clients ( 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-network computing can address Smart grids needs 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 Plant Plant 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-network computing can reduce network complexity for Smart Factory
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, without the prior permission of Infosys Limited and/ or any named intellectual property rights holders under this document.
Thank You
Top Related