Toward Distributed Declarative Control of Networked Cyber-Physical Systems (NCPS)

1. Toward Distributed Declarative Controlof Networked Cyber-Physical Systems (NCPS) Mark-Oliver Stehr, Minyoung Kim, and Carolyn Talcott Website: http://ncps.csl.sri.com Accepting International Fellows for 2011 !

2. Key Points • Partially ordered knowledge-sharing model for loosely coupled distributed computing • Distributed logic for declarative control • Simulation case study: Collaborating team of mobile robots • Implementation of application framework for NCP

3. Partially Ordered Knowledge Sharing New Loosely Coupled Distributed Computing Model • Inspired by our earlier work on delay-/disruption-tolerant networking (DTN) • Minimal assumptions on network connectivity (can be very unreliable) • Works with dynamic topologies, network partitions, and mobile nodes • Designed for heterogeneous nodes andheterogeneous networking technologies • Partial order allows the network toreplace obsolete or subsumed knowledge • Global consistency is not enforced(impossible in disruptive environments) • Avoids strong non-implementable primitives, e.g. transactions • Locally each cyber-node uses an event-based model with local time • Each cyber-node can have attached cyber-physical devices

4. Distributed Declarative Control Key Problem • Traditional logics are not designed for distributed reasoning • Logics are traditionally closed systems, i.e. not interactive Requirements/Assumptions • Need to consider the NCPS as a single asset • Logical theory/specification is available to all nodes • Nodes contribute resources according to their capabilities Knowledge is transparently shared • Knowledge = Facts + Goals • Facts can represent observations • Goals can represent control objectives Distributed logical framework • Integrates forward and backward reasoning • Partial order is essential part of the distributed logic

5. Predicates for Distributed Surveillance Different Flavors of Predicates • Cyber-facts and cyber-goals serve as interface to environment (user, devices) • Ordinary facts/goals are used internally by the theory

6. Sample Theory for Distributed Surveillance

7. Sample Theory for Distributed Surveillance Interpretation • O1: New observations replace old observations • O2: New control goals replace old goals • O3 & O4: Solved goals (i.e. facts) replace unsolved subgoals

8. Sample Execution Visualization of a Distributed Execution • Reasoning can occur anywhere in the network

9. Cyber-Application Framework Architecture • Cyber-framework implements partially ordered knowledge-sharing model • Logical framework is implemented as a cyber-application • Can coexist and interoperate with conventional code

10. Cyber-Application Framework Implementation • Applications cannot distinguish between simulation and reality • model-based simulation/analysis mode • real-world deployment/execution mode

11. System Implementation • Simulation vs. Real-world for Physical/Network Layer • Neighbor Discovery • Knowledge Dissemination Protocols • Multi-threaded Execution and Simulation

12. 1. Network/Physical Layer Core Idea • Applications cannot distinguish between simulation and reality • model-based simulation/analysis mode • real-world deployment/execution mode Simulation World • SimNode, SimDevice • Comm. among cyber-nodes via • DTN simulator with abstract mobility • Stage multi-robot simulator with wireless network model Real World • RealNode, RealDevice • Comm. among cyber-hosts via UDP • Time synchronization • Cyber-framework supports a mechanism that allows • same application code to be used for simulation and deployment.

13. 2. Neighbor Discovery Core Idea • To disseminate knowledge via opportunistic links, each cyber-engine needs to keep track of its immediate neighborhood • Neighbor list is refreshed between cyber-engines in periodic manner Implementation • Hello knowledge is posted periodically between cyber-engines (broadcast) • Hello knowledge includes: • Public/private IP address, hop count, engine ID, expiration time • It is possible to be explicitly define other engine’s address (unicast) • Multi-hop discovery is supported by forwarding hello knowledge until user-defined maximum hop count reached • Multi-hop discovery allows some nodes to operate as discovery facilitators (registry-like service) • Cyber-framework manages up-to-date neighborhood information to disseminate knowledge via opportunistic links.

14. 3. Knowledge Dissemination Protocol Optimized Deterministic Flooding • Disseminates knowledge to all neighbors that are not (known to be) aware of the particular unit of knowledge (but only once) C B A • Probabilistic Reflection • Single message protocol • Window of opportunity can be small • Minimal assumptions on network • Links can be unidirectional or bidirectional • Error rate can be high • Only needs eventual weak connectivity • Periodically, for each knowledge item k and for each outgoing link: • If potential receiver is not known to be aware of k it will be sent out • Otherwise k it is sent out with a non-zero probability defined by a reflection parameter divided by number of outgoing links k k k k k k • The knowledge dissemination layer will replace and discard all instances of inferior knowledge based on partial order semantics.

15. 4. Multi-threaded Execution Core Idea • Local computation is triggered by processing an event from event queue • Event queue exists per cyber-engine (process) • The performance can be improved by parallel processing of events Implementations • Fine-grained parallel execution • Each cyber-node with its own event queue • A single shared event with a thread pool • Coarse-grained parallel execution • Multiple cooperating cyber-engines • Can be used at different levels • On a single host (local communication) • Hosts on the same subnet (broadcast) • Beyond subnets (unicast) • Cyber-framework supports various configurations for parallel execution as well as their arbitrary combinations.

16. Conclusions Contributions • Truly distributed logical framework • Cyber-predicates enable interaction with the physical world • Facts and goals treated on an equal footing • Covers entire spectrum between autonomy and cooperation • Tested with abstract mobility model and Stage multi-robot simulator Related Work • Declarative Networking (P2, DTN, XG) • Modular Robotics (Regiment, Meld) • Fractionated Software/Systems Future Work • Reasoning performance improvements • Integration with distributed dynamic optimization • Exploring other applications, e.g. cooperative flight control inUAV testbed consisting of 10 UAVs and additional ground nodes