More Related Content Similar to Arguments for a Unified IoT Architecture (20) Arguments for a Unified IoT Architecture4. page© 2016 VoltDB
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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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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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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3
2
1
2
3
4
EoD
Billing
4
Rule
Engine
FAST DATA: INGEST, ANALYTICS, TRANSACTIONS
16. page© 2016 VoltDB
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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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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QUESTIONS?
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