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SPARQLMotion for Distributed Network Ops

SPARQLMotion for Distributed Network Ops. 2009 Semantic Technology Conference TopQuadrant User’s Group. John Carson, Lockheed Martin john.t.carson@lmco.com. Problem: Dynamic Network Topology. Problem: Military networks are Dynamic, Heterogeneous, and Open .

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SPARQLMotion for Distributed Network Ops

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  1. SPARQLMotion for Distributed Network Ops 2009 Semantic Technology Conference TopQuadrant User’s Group John Carson, Lockheed Martin john.t.carson@lmco.com

  2. Problem: Dynamic Network Topology Problem: Military networks are Dynamic, Heterogeneous, and Open Challenge: Discover the Emergent Capability within a given network. Local Net Local Net Local Net Result: Increased network Agility under change

  3. Adaptive Service Networks 1) Assets yet to be developed 2) Needs to be discovered 3) Concepts of Operations to evolve Network Enabled Operations requires declarative modeling Semantics permit real-time interoperability

  4. Future of Networking • Trend away from the formal enterprise (integrated systems) toward unstructured peers (ad hoc systems) • Little hierarchy or structure, systems-of-systems • Away from blueprints, away from formal requirements Houston: a city without zoning “the form of a city is not defined in advance by specifying requirements; rather, a city emerges and changes over time though the loosely coordinated and regulated actions of many individuals.” -- Greg Goth Need for lightweight scripting that supports interoperability

  5. Task Networks • Out of scheduling (Operations Research) • Rather than script the behavior, capture the task relationships • Decomposition yields … • - role based • - policy driven http://manyeyes.alphaworks.ibm.com • This presentation does not address the algorithmic control aspects, but rather the transaction models that support distributed control

  6. Motivating Example • Cyber-Physical Systems • Information (ground in app) • Hardware (ground in device) • Heterogeneous Ontologies • Distributed Computing

  7. Robots If Robot A sees Red Ball, remove (else leave it alone)

  8. Demonstrations

  9. Conclusions • SPARQLMotion builds on SPARQL • Query language (Data Access) • Rule language (Manipulation) • Open semantics (Grammar) • Add in Physical groundings (sensors and effectors) • Actionable when coupled with SPIN • The benefit of this approach • Operational redundancy, point of failure is spread out • Model-driven approach captures task Network • Heterogeneous Peers interoperate through policy scripts A declarative way to script interaction between heterogeneous peers

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