a computational space for the web of things
DESCRIPTION
The expansion of the World Wide Web to include information that is generated by physical devices with embedded sensing and actuation capabilities entails a surge of high-frequency real-time data that is mostly published without further processing in its raw form. To derive "smart" decisions from this data and thus use it to enable a "smart world" requires the distilling of more abstract, higher-level knowledge from it. We propose the concept of a computational marketplace as a framework to enable the analysis and aggregation of real-time data. Here, multiple tiers of hyperlinked algorithms from different providers interact to refi ne data within computational graphs, which are linked structures of cascaded processing steps. In the associated paper, S. Mayer and D. Karam, A Computational Space for the Web of Things, we present an analysis of the key constraints on such a framework and provide a corresponding implementation as well as results from evaluations in an experimental use case scenario.TRANSCRIPT
A Computational Space for the Web of Things 3rd International Workshop on the Web of Things (WoT 2012), Newcastle, UK
Simon Mayer, Distributed Systems Group, ETH Zurich, [email protected]
David S. Karam, Chair of Scientific Computing, TU Munich, [email protected]
Motivation / Background
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Earthquake and Tsunami on March 11, 2011
Nuclear meltdown in three reactors of the Fukushima NPP
Releases of radioactive materials
www.pref.fukushima.jp
US federal occupational limit: 0.5 μSv/h
Motivation / Background
“Wind from Fukushima” App Mashing of radiation and wind data
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Cheap Geiger
counters
Radiation data
streams
Motivation / Background
Apps like “Wind from Fukushima” allow to mashup this data to provide a service
What happens with the refined data? 4 WoT 2012: 3rd International Workshop on the Web of Things 7/13/2012
Commodity Hardware
Information Markets
Motivation / Background
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Commodity Hardware
Information Markets
Computational
Markets
Crowd-sourced information creation
Information sharing and aggregation
Information processing, refinement, and analysis
Motivation / Background
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Commodity Hardware
Information Markets
Computational
Markets
Crowd-sourced information creation
Information sharing and aggregation
Information processing, refinement, and analysis
Cosm, Sen.Se, Twitter, FB Graph API, ...
Smartphones, Smart Consumer Products, Electricity Meters, ...
computational marketplace
Algorithms should be linked together in an open and extensible fashion to enable multi-tier computations in a construct that we call a
Constraints on a Computational Marketplace
Clients need to be able to find computations on the
marketplace and select appropriate computations to achieve their goal
The marketplace should provide meta-information about algorithms and thus help to optimize traversal
Mechanisms required for security and billing
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Constraints on a Computational Marketplace
Clients need to be able to find computations on the
marketplace and select appropriate computations to achieve their goal
The marketplace should provide meta-information about algorithms and thus help to optimize traversal
Mechanisms required for security and billing
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Interface Discovery
Marketplace API exposes paths
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GET marketplace/node_arrhythmia
{
“service” : “www.arrhythmia_detection.net”
“forward_paths” : {
“emergency” : “node_dispatch”,
“default” : “node_start_arrhythmia”
}
}
Interface Discovery
Marketplace API exposes paths
“Graph Crawler” maps computational graph Basically an ordinary search machine…
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Crawler
GET marketplace/node_arrhythmia
{
“service” : “www.arrhythmia_detection.net”
“forward_paths” : {
“emergency” : “node_dispatch”,
“default” : “node_start_arrhythmia”
}
}
Constraints on a Computational Marketplace
Clients need to be able to find computations on the
marketplace and select appropriate computations to achieve their goal
The marketplace should provide meta-information about algorithms and thus help to optimize traversal
Mechanisms required for security and billing
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Path Traversal Guidance
Humans do it...
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Path Traversal Guidance
Machines can, too!
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Path Traversal Guidance using Path Deciders
Application-specific (here: Arrhythmia Detection)
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Path Traversal Guidance will work if...
Machines can understand and interpret path names Long shot, but could work... Definitely future work!
Path descriptions (e.g., “emergency”) are fixed/meaningful Easy!
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Constraints on a Computational Marketplace
Clients need to be able to find computations on the
marketplace and select appropriate computations to achieve their goal
The marketplace should provide meta-information about algorithms and thus help to optimize traversal
Mechanisms required for security and billing
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Computational Paths Optimization
Optimize traversal according to application needs
Multi-dimensional cost metrics: time, money, quality,...
Marketplace offers this information, but does not decide on
routes → Generic path deciders
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Computational Paths Optimization using Path Deciders
Generic (here: Lowest time cost path)
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Constraints on a Computational Marketplace
Clients need to be able to find computations on the
marketplace and select appropriate computations to achieve their goal
The marketplace should provide meta-information about algorithms and thus help to optimize traversal
Mechanisms required for security and billing
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Security and Billing
Authentication, authorization, and billing schemes to
restrict access to computational resources
Don’t create a centralized repository for login data: trust problems, security problems, scaling problems...
Instead use third-party schemes (OAuth 2.0!) and inline this functionality as a linked computational node!
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Demo 1: Arrhythmia Patient Scenario
Four separate computational mashups Arrhythmia Arrhythmia probability from heartbeat data Ambulance Optimal ambulance dispatch Traffic Predicts traffic from location of people and cars and weather data from yahoo/google predict
Composite mashup: Weather + Traffic + Ambulance +
Arrhythmia OAuth-based authentication for prediction API
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Demo 2: Marketplace Exchange
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Time cost-based traversal optimization of multiple clients Uses generic time-cost-based path decider...
Three arrhythmia detectors: 𝐶𝐶𝐶𝐶𝑖 = 𝑑 + 𝑘 ∗ #𝑐𝑐𝑐𝑐𝑐𝐶𝐶𝑖
Demo 2: Marketplace Exchange
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Time cost-based traversal optimization of multiple clients Uses generic time-cost-based path decider...
Three arrhythmia detectors: 𝐶𝐶𝐶𝐶𝑖 = 𝑑 + 𝑘 ∗ #𝑐𝑐𝑐𝑐𝑐𝐶𝐶𝑖
Conclusion
Concept of computational marketplace
Constraints for scalable, fault-tolerant, and change-tolerant
N-tiered computational model
Proof of concept marketplace implementation + scenarios
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Acknowledgements
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