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