Building the Internet of Things
Early learnings from architecting solutions focused on predictive maintenance
Authors
Martijn Hoogendoorn, Architect, Applied Incubation, Microsoft
Mark Kottke, Architect, Applied Incubation, Microsoft
Intended audience
This white paper is aimed at technical decision makers, solution architects, and developers.
Abstract
This white paper provides a comprehensive overview of lessons learned from the authors' experiences in implementing large scale customer projects that target predictive maintenance as a space in IoT. It frames various elements and considerations of importance within the Internet of Things, highlighting tradeoffs, opportunities and grounding the implementation activities using a reference architecture and an associated comprehensive cost model.
Acknowledgments
The authors would like to thank the following people, who contributed to, reviewed, and helped improve this white paper.
Contributors
Marc Mercuri, Principal Program Manager, Azure Customer Advisory Team, Microsoft
Clemens Vasters, Principal Program Manager, Azure Application Platform, Microsoft
Reviewers
Arno Harteveld, Architect, Client Solutions, Microsoft
Carolina Piavis, Director Business Programs, Applied Incubation, Microsoft
Ray Stephenson, Director, Applied Incubation, Microsoft
Mani Subramanian, Senior SDET, Patterns & Practices, Microsoft
Version
1.2
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Table of contents
Executive summary 4
IoT and predictive maintenance 5
a.The Internet of Things 5
Business value 7
Megatrends 7
Technology enablers 9
Standardization efforts 10
b.Predictive maintenance 10
Predictive maintenance scenarios 11
c.Healthcare 11
d.Automotive 11
e.Manufacturing 12
Architectural considerations 13
Interaction patterns 14
Connectivity pathways 15
Connectivity network types 16
f.Protocol choices 18
Transport-layer protocol choices 18
Transport-layer protocol security 20
Application-layer protocol choices 20
g.Security 22
Virtual Private Networks 23
Compliance 23
h.Device communication patterns 25
NAT-based device network 25
IPv6 direct-addressing device network 26
NAT-based, PAN device network 27
Generic concerns with direct addressing 27
Service-assisted communication 27
i.Designing for scale 30
Communication and ingestion 31
Data storage scalability 31
j.Device registration 32
k.Acquiring data 32
Message size and format 32
Message types 33
Message priority 33
Conditional messaging 34
Contextual messaging 34
Message batching 34
Bandwidth and scale 34
l.Storing information 35
Storing data on the device 35
Transforming data 35
Location 35
Longevity, format, and cost 36
m.Processing information 36
Alarm processing 36
Complex-event processing 36
Big Data analysis 37
Machine learning 37
Data enhancement 38
n.Publishing insights 38
Audience 38
Publishing format 39
Cost modeling and estimation 40
o.A common architecture for IoT 40
Event Hubs 40
Architectural details 40
2.The provisioning service that takes in information on authorized devices, creates its configuration, and stores access keys. 41
3.Devices that interact using either AMQP or HTTP towards Service Bus directly, or a component called the Custom Protocol Gateway Host, which hosts adapters for other protocols, such as MQTT and CoAP. 41
4.Telemetry requests that are distributed by the router, using adapters to communicate with downstream storage and processing engines. 41
5.Commands send to devices through the use of the notification/command router that is internally surfaced through the Command API host. 41
a.Capacity modeling 43
b.Cost estimation 44
Ingress path cost using Event Hubs 44
Egress path cost 47
Management cost 50
c.System processing cost 52
d.Cost estimate calculation 52
Important topics not yet covered 53
e.Networks with automatic handover and fallbacks 53
f.The need for the commoditization of devices 53
g.The creation and use of information marketplaces 53
h.Management solutions 53
i.The redefinition of SLAs 54
j.Integration simplicity 54
Conclusions 55
How Microsoft can help you succeed 56
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