ICP Architecture: Execution and Control Bostjan Kaluza, Damjan Kuznar, Erik Dovgan, Jernej Zupancic, and Matjaz Gams Jozef Stefan Institute, Slovenia

Outline I. Introduction – Principles and argumentation – Idea – Relation to TNO architecture II. Analysis – Use cases – Agent types – Responsibilities – Agent deployment III. Design – Next steps

Principles and Motivation Properties of smart cities Smart Cities, I. Celino, S. Kotoulas (eds.), IEEE Internet Computing, November/December 2013: – Effectively process networked city information – Information to authorities, business, citizens, optimizing energy and water production or consumption, traffic management, public safety, emergency response – Multifaceted and cross-domain challenges, inherently interdisciplinary – Reason on spatial, temporal and contextual aspects of data – Life-cycle of data, integrating heterogeneous sources – Ubiquitous, pervasive, AmI, agents, AI – IBM Smarter Planet initiative, Siemens Sustainable Cities, Oracle IT platform City services, Microsoft CityNext platform

Principles and Motivation/ Design Principles of designing large distributed systems – Need to balance: simplicity, scalability, performance, reliability, generality, features – Before doing anything, consult people having experience with designing large distributed systems (Belifemine; JSI) Software design topics – Design concepts: abstraction, refinement … – Design considerations: compatibility, fault-tolerance … – Modeling language: flowchart, UML, SysML, … – Design patterns: reuse of patterns, modules … – Usage: documentation, prototypes Practical: choose design methodology, forms, languages … – Execute: Definition, analysis, design, implementation, test

Motivation / our approach Agent technologies best for smart cities /ACCUS – Agent: autonomous SW component, providing interoperable interface to an arbitraty system, persuading its agenda for a client – Autonomous, social, reactive, proactive, mobile, truthful, benevolent Our proposal – Agent design methodology – Prototype on a smart house / current – OSGi, JADE, JADEX – Two parts very compact (!) core working every-day tasks fast and reliable (limited size and functionality; general and flexible) complex advanced modules providing „thinking“ (negotiating, optimizing, learning; large, heterogenous, complex, not fully reliable, scientific and operational challenges)

Idea Operational and control levels: ICP Backbone – Runtime environment (management, communication, …) – Focused on execution – Responsive behavior (via service calls, notifications) ICP Mind – Proactive behavior – Learning, optimization, control

ACCUS Plug-ins ACCUS Integration and Coordination Platform Application Smart Lighting Event detection Application Service Cross Domain ACCUS architecture Application Info Broker & coordination Control Broker & coordination Java VM ACCUS ICP Core ACCUS ICP Extensions ACCUS Applications Service Repository Service Repository Hardware OSGi OS ACCUS Data Store ACCUS Data Store Work Flow Engine Application Server Application Server Semantic mapping Ontology DB Presence detection Location detection Location detection Policy management Management Subsystem Monitoring Subsystem Monitoring Policy DB Policy DB Security Identity & access management Identity & access management Service Broker ACCUS API Subsystem adaptor Subsystem Service Application Server Application Server Data management Service Bus Calamity detection Service … Rule engine Rule engine Data analytics Data analytics Traffic monitor Traffic monitor Generic service … ACCUS Service Plug-ins = Standard software = ACCUS specific software Subsystems = case specific software ICP Backbone ICP Mind

Infrastructure vs. Control View Two-dimensional view Infrastructure Execution and Control ICP Backbone Execution Responsive behavior ICP Mind Planning Proactive behavior ACCUS ICP Core Generic   ACCUS ICP Extensions Accus specific  ACCUS Plugins City specific 

II. ANALYSIS Use cases Agent types Responsibilities Agent deployment

Sample ICP Backbone Use Case : Emergency Management

Sample ICP Mind Use Case: Multiagent negotiations

Agent (Service*) Types: ICP Backbone Communication Service management – Service life-cycle Rule engine – Executing queries Workflow engine – Executing emergency response Security *service = basic reactive agent

Agent types: ICP Mind Subsystem coordinators, city coordinator – Belief-Desire-Intention agents – Proactive, follow their goals – Organizational structure – (decision making, negotiations) Support agents – Optimization Stochastic optimization Game theory (Nash equilibriums, multiagent negotiations) – Learning Anomaly detection Surrogate modeling (simulator synthesis) – Data analytics – Adaptive control schemes

Organizational Structure (partial) Communicatio n Service management Rule engine Work flow engine Security Subsystem 1 services Subsystem 2 services Transducer 1 Transducer 2 Subsystem 1 Subsystem 2 Data analytics agent Learning agent Optimization agent Subsystem 1 coordinator agent Subsystem 2 coordinator agent City coordinator agent Adaptive control schemes Mind Backbone … Coordinators Support

Responsibilities: Lighting coordinator Receives lighting schedules from authorized agents Retrieves information on weather, traffic conditions, pedestrians, cyclists etc Receives new algorithms for computing lamp brightness Presents information on lamp conditions, power consumption, brightness levels etc Uses support agents (Nash equilibria agent, stochastic optimization agent) to compute better – (sub)optimal settings for operation Uses support agents to specify workflow in case of emergency or anomaly detection Negotiates with other subsystem coordinator agents Listens to the City coordinator agent

Deployment Information ICP Backbone: OSGi ICP Mind: Jade, Jadex ARTEMIS-2013 JADE OSGi JAVA OS HARDWARE Data base APP server ICP MIND ICP BACKBONE

ACCUS Plug-ins ACCUS Integration and Coordination Platform Application Smart Lighting Event detection Service Cross Domain Control architecture Application ACCUS Applications ACCUS Data Store ACCUS Data Store Work Flow Engine Semantic mapping Ontology DB Presence detection Location detection Location detection Policy management Subsystem Monitoring Subsystem Monitoring Policy DB Policy DB Security Identity & access management Identity & access management Service Broker ACCUS API Subsystem adaptor Subsystem Services Data management Service Bus Calamity detection Rule engine Rule engine Data analytics Data analytics Traffic monitor Traffic monitor Generic service … ACCUS Service Plug-ins Subsystems Management Stochastic optimization agent Info Broker & coordination Control Broker & coordination Nash equilibrium agent Anomaly detection agent Multi-agent negotiation Surrogate modeling Workflow specification City coordinator agent Subsystem coordinator agent Mind Backbone

Wrapper Deployment: Integration with ICP Transducer (when modifying code is not possible) – Separate process that implements API and communicates with outside system – Each application specifies input/output in the agent language Wrapper (when modifying code is possible) – API envelope Code rewrite (programmed in line with agents paradigm) – Part of ICP, our components Legacy resource Legacy code Rewrite Transducer ACL

Further Work: Architecture Design Interaction specification Protocol definition Message templates Agent user interaction Internal agent behavior Defining ontology