There is a fuzzy border between the streaming and operational requirements of managing fast data in IoT. There is also an increasingly fuzzy border between where the computation and data management activities should occur. In this webinar, Ryan Betts, CTO of VoltDB highlights the benefits and disadvantages of a unified IoT architecture and discuss how simplifying at the core allows for high throughput, streamlined scalability and data consistency.

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Arguments for a Unified IoT
Architecture

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FUZZY BORDERS
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Centralized
Edge
Streaming
/
Mechanical
Opera6onal
/
Policy

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VENDORS IN TRANSITION
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FAST DATA: GLIMPSE AT INNOVATION
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OLTP
OLAP
Streaming
VoltDB
NuoDB
Founda6onDB
SQLFire
XD
Amazon
Aurora
MemSQL
Druid
OpenTSDB
TempoIQ
ParStream
InfluxDB
PipelineDB
Storm
Spark
Streaming
Google
Dataflow
Amazon
Kinesis
Tibco
Streambase
IBM
Streams
DataTorrent

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APPLICATIONS IN FLUX
• Are the "killer apps for IoT" machine learning,
fully automated, highly distributed, driven by
collec<ve (centralized) data, by analy<cs, or
outcomes, efficiency or engagement, consumer
or industrial?
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CONTINUUM
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GENERAL SOLUTION
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SIDEBAR: A DEEP STACK
Device
Security & Policy
Communication
Fog Data Services
More Networks
Centralized Compute
Data Services
Cloud Applications
Fast (in motion)
Streaming Analytics:
real 'me summary
aggrega'on, modeling
Transaction Processing:
per-­‐event decisions using
context + history.
Big (at rest)
Exploration:
data science,
inves'ga'on of large
data sets
Reporting:
recommenda'on
matrixes, search
indexes, trend and BI

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WHAT IS FOG COMPUTING
Fog compu'ng is not a replacement for the
cloud, but rather “a distributed compu'ng
paradigm that extends cloud compu'ng closer to
the edge of the network to enable a new wave of
applica'ons and services in IoT land.
hDp://embedded-­‐compu'ng.com/25938-­‐seeing-­‐through-­‐the-­‐fog-­‐compu'ng/
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RATIONALE: PERFORMANCE REQUIREMENTS
Brain v. Octopus
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RATIONALE: DATA VELOCITY AND VOLUME
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Walmart v. Vending Machine

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RATIONALE: TIME TO MARKET
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App Store v. Space Shuttle

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CLOUD, DATA, IOT VIRTUOUS CYCLE
• IoT is a data driven application
• Data will drive cloud utilization
• IaaS low margin
• Apps drive margin
• Making the data useful drives value
• It’s not just storage. It’s operational
• The more data processed in the front end,
the more that will be stored in the cloud
CloudData
IoT

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INFORMATION TECHNOLOGY EVOLUTION
1980 1990 2000 2010
Internet - Cloud
Client-Server
Fast + Big Data – Internet of Things
2020
Internet - Cloud
Client-Server
Fast + Big Data – Internet of Things
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Fast inbound events
requests
Application with
request/response
pattern for context
Event initiated,
automated action
Forwarding of
accumulated data to
OLAP or
Applications
Events
VoltDB
C*
Triggered
Alerting
Hadoop
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EoD
Billing
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Rule
Engine
FAST DATA: INGEST, ANALYTICS, TRANSACTIONS

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Collect Explore
AnalyzeAct
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Big Data analytic results:
1. Discoveries: seasonal predictions,
scientific results, long-term
capacity planning
2. Op'miza'ons: market
segmentation, fraud heuristics,
optimal customer journey

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ACTIVITY AT THE EDGE
"...dynamic distribu'on of data processing and
analy'cs with performance-­‐cri'cal computa'on
for applica'ons/data center func'ons at the
very edge of the network”
http://ibm-iot-blog.com/whats-possible-iot/
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PATTERNS AND DECISION ENGINES
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Automated anomaly
detec'on. Model based.
Math not business logic.

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CISCO: MOVE TO EDGE TO SCALE PROCESSING
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CHALLENGES TO FOG
An addi'onal 'er of compute, storage and
networking resources distributed across many
loca'ons to enable sophis'cated applica'ons is
a complex and expensive undertaking.
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END TO END PRINCIPLE
Func'ons placed at low levels of a system may be
redundant or of liDle value when compared with the
cost of providing them. Examples: bit error recovery,
security using encryp'on, duplicate message
suppression, recovery from system crashes, and delivery
acknowledgement.
http://web.mit.edu/Saltzer/www/publications/endtoend/endtoend.pdf
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TYRANNY OF SIMPLE SCALE
• HTTP everywhere
• ATM to the desktop
• 1000 server clusters vs. engineered systems.
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INDUSTRY DOMINANCE IN CLOUD
• Fog concept driven largely by Cisco, IBM
• Which face industry pressure from cloud
builders
https://azure.microsoft.com/en-us/blog/ocp-2016-building-on-
community-driven-innovation/
https://code.facebook.com/posts/717010588413497/introducing-6-
pack-the-first-open-hardware-modular-switch/
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LOOKING FORWARD: THOUGHT EXPERIMENTS
• What’s the “CDN” for IoT – the utility apps are
pushed to for scale. Protocol based? Provisioning
based? Engineered system?
• What’s the impact of cloud providers expanding
geographies of service? What’s the floor on cloud
pricing?
• Battery vs. Bandwidth
• Industrial vs. Consumer
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DATA TAKE-AWAY: MODELS TO APPLICATIONS
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QUESTIONS?
• Use the chat window to type in your questions
Ø Download VoltDB:
• www.voltdb.com/Download
• Open source version is available on github.com
• Check out the Developer Guide to Streaming Data in the resources
section on the right side of your screen.
• Join the conversation on Twitter #VoltDBFastData
• All registrants will receive our new eBook – “Architecting for the IoT”
via email.
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