Ambiance

Åmbiance Project Autonomous Systems Group University of Luxembourg Open Systems Lab University of Illinois at Urbana-Champaign Reza Razavi (PI) University of Luxembourg reza.razavi@uni.lu Laboratoire d’Informatique de Paris 6 – CNRS Université Pierre et Marie Curie Kirill Mechitov, Sameer Sundresh and Gul Agha University of Illinois at Urbana-Champaign {mechitov, sundresh, agha}@cs.uiuc.edu Jean-Francois Perrot Université Pierre et Marie Curie jean-francois.perrot@lip6.fr Wireless Sensor Networks (WSNs) WSN Programming Benefits: State of the Art • Programming tools focused on efficiency • Low-level, C-based programming language (nesC) • Lightweight, component-based OS (TinyOS) How can we program this system? • Fine-grained sensing • Easy deployment, no infrastructure required • Enable new class of applications uQuery Engine Query 1: determine ambient temperature and wind conditions Challenges: Query 2: Detect and locate deer moving through the region • Resource constraints (memory, bandwidth, energy) • Large-scale coordination • Combine the problems of networking, signal processing, real-time and embedded computing Macroprogramming WSNs Response to Query 1: temp=65ºF wind: SE, 3mph • Regiment, Semantic Streams, spreadsheet programming • Do not meet requirements for uQuery Engines event Requirements for uQuery Engines • Targeted at end-users, not programmers • Dynamic: deploy and change behavior at run-time • Support concurrency inherent to ambient systems • Multiplicity of end-users • Supports real-time programming, sensing, concurrency • Applications are compiled together with the OS Adapted from: [Boulis, 2005] Response to Query 2: Deer at (10,35) moving NW at 5mph Application Example: Break Beam Detector We want to detect an object passing through a break beam sensor, on request: • Wait for a request message from the user • Perform the requested action Note the following issues with the code below. • Static: • Specification and linking of components at compile time • All components are compiled into a single image deployed on the sensor • Low-level: • Programmer is responsible for managing: timing, communication, • Execute detectBeamEvent() primitive • Keep checking the sensor until a change in status is detected • Send the result of detection back to the user Connecting together a large number of small computers with sensing and actuating capabilities, to collectively and costeffectively solve problems, based on real-time data. Mica2-Dot and Telos motes http://research.sun.com/ The user (programmer) is responsible for choosing the right OS and network components, and assembling them along with the specific application logic into an executable program. memory management, error handling • No separation of concerns: • OS and network programming elements are inextricably linked with business logic programming elements // Communication: receive requests for execution and send results void sendPacket(uint8_t *buf, uint8_t n) __attribute__((C,spontaneous)) { memcpy(msgbuf.data, buf, n); msglen = n; if (call SendMsg.send(TOS_BCAST_ADDR, msglen, &msgbuf) == SUCCESS) sendPending = 1; } uint8_t isSendPending() __attribute__((C,spontaneous)) { return sendPending; } event result_t SendMsg.sendDone(TOS_MsgPtr mp, result_t success) { if (!success) call Timer.start(TIMER_ONE_SHOT, 200); else { call Leds.redToggle(); sendPending = 0; } return SUCCESS; } event TOS_MsgPtr ReceiveMsg.receive(TOS_MsgPtr mp) { TOS_Msg m; call Leds.greenToggle(); if ((uint8_t)mp->data[0] == 20) { m.data = deref(detectShadow()); sendPacket((uint8_t *)m.data, strlen(m.data)); } return mp; } event result_t Timer.fired() { return call SendMsg.send(TOS_BCAST_ADDR, msglen, &msgbuf); } /* Detect break beam event application (code excerpt) */ configuration Example {} implementation { // list of application components components Main, ExampleM, LedsC, GenericComm, TimerC, Photo, CC1000ControlM; // statically link all components Main.StdControl -> GenericComm; Main.StdControl -> TimerC; Main.StdControl -> Photo; Main.StdControl -> ExampleM; ExampleM.SendMsg -> GenericComm.SendMsg[10]; ExampleM.ReceiveMsg -> GenericComm.ReceiveMsg[10]; ExampleM.CC1000Control -> CC1000ControlM; ExampleM.Timer -> TimerC.Timer[unique("Timer")]; ExampleM.Leds -> LedsC; ExampleM.PADC-> Photo; } module ExampleM { /* … */ } implementation { TOS_Msg msgbuf; uint8_t msglen, sendPending; volatile uint8_t ioPending; uint16_t ioData; /* … */ // primitive function #20: detect beam event (using photo sensor) uint16_t detectBeamEvent(); /* … */ // I/O: convert split phase non-blocking I/O to blocking I/O uint16_t IO(uint16_t a, uint16_t b) __attribute__((C,spontaneous)) { while (ioPending) yield(); if (a == 20) { call PADC.getData(); ioPending=1; } while (ioPending) yield(); return ioData; } async event result_t PADC.dataReady(uint16_t data) { ioPending=0; ioData=data; return SUCCESS; } // Implementation of detectBeamEvent primitive uint16_t detectBeamEvent() { int i; uint16_t data, avg = 0; ledSet(0); for (i = 0; i < 10; i++) avg += IO(2, 0); avg /= 10; while ((data = IO(2, 0)) > avg - 15) yield(); ledSet(7); return list(2, newWord(20), newWord(data)); } } Ambiance: Adaptive Object Model-based Platform for Macroprogramming Sensor Networks Standard AOM Architecture AOM is a meta-data interpreter Open Issues with AOMs Meta-data interpreter Read access Meta-data corresponds to data that specifies the Programs’: • Object-model (Structure and Behavior) • Windows, Menus, Configuration Panel, … • Saved as configuration data OO Language Obj ect Pr ogr am m er Agent Domain entity types Properties • Have not been applied to WSNs • Lack of standard techniques for Adaptive service provision meta-data repository Rules • WSN dynamic code generation • Supporting concurrency • Supporting separation of high-level control from the execution • Run-time optimization Associations Events Write access Exper t Beam Event Det ect or Extended AOM Architecture for Macroprogramming WSNs Knowledge level • Comprises: Step Step Operational level • Comprises a set of mobile agents • The agents: Fetch Load Code • Conceptual ontology • Behavioral ontology • Framework for specifying queries as a composition of services through mediation of concepts Knowledge level • Are defined dynamically • Execute concurrently • within the WSN, and • on a single node Adapt Adapt Ada pt a t ion cycle • Assumptions: • Completeness of the service ontology • Acknowledgeability of the users in the domain covered by the ontologies • Low-level data, such as the sensor id, may be provided by users (in the process of being relaxed) • Based on a formal model of computation Active object Intercession Passive object Introspection • In order to be verifiable • Actors Operational level • Keeps track of static and dynamic metadata. Dynamically-composed uQuery (ambient service) Query Interpretation and Execution Query Representation Example Dart: Query Representation Framework 0..* Context Process Conscious Product 1 Behavior Structure of queries • Finite directed acyclic graph • Recursive -dependents 1 1 1 * 0..1 Task 0..* • Reflective • Same set of concepts reused to extend the system Step * 1..1 Behavior 2 3 1..1 0..* 0..* -holds 0..1 Conceptual Ontology 0..1 Grid 1..1 -contributes Ontology Concept List -type 0..1 0..* Procedure 0..1 -computation method Construct 0..* -instantiates Primitive Control Structure 1..1 0..* Result 0..* Contract ActorNet Primitive -spec Argument -policy -produces 0..1 -requires * 1 Execution Strategy Association Generalization Behavioral Ontology Signature Aggregation 1..1 Plot Histogram 1 Semantics of queries • Parallel evaluation of contributions • Limited to their dependencies • Different execution semantics * • Late • value binding • method binding 4 5 12 Vehicle Histogram Entry Do <T2> Create Histogram Entry Step T1: Compute Histogram Entry 6 9 10 11 Pulse Pair 3 Mobile Object Vehicle Average Pulse Pairs Estimate Motion Classify Vehicle Concept Construct 8 8 Pulse Pair 1 Pulse Pair 2 Sort Edges Sort Edges 7 7 Pulse 1 Detect Beam Event The Core Design of Dart: A Reusable and Extendible (Global) Behavior Representation Framework Task Main • Same set of concepts reused to extend the system 0..1 0..* Histogram For a Period of <2 weeks> Do <T1> Structure 1 13 Histogram Entry Collection • Steps may hierarchically point to tasks -holds -content -organization 1 Contributes Relation 7 Pulse 2 Pulse 3 Detect Beam Event Detect Beam Event T2: Identify Vehicle Liz’s query Liz’s Query: compute histogram of vehicle arrival times for a period of two weeks Source: [Whitehouse, Liu, Zhao 2006] Collaborators: Christoph Dony Université Montpellier-II LIRMM, France Noury Bouraqadi Computer Science Research Team. Ecole des Mines de Douai BioMedical Informatics ERCIM Working Group Ralph Johnson, Software Architecture Group University of Illinois at Urbana-Champaign Vincent Ginot Mobidyc Project French National Institute for Agricultural Research Alain Cardon Université Pierre et Marie Curie Primitive Processing Algorithm ActorNet: Implementation of the Operational Level At the operational level, queries are executed by ActorNet 2 • A system of mobile, concurrently executing agents called actors • Actor code is dynamically generated by the meta-level • ActorNet language is extended with new keywords and services providing the means to link the meta-level and the operational level of the Ambiance platform Actor id 1 Meta Actor Actor in text form Actor Deployment Interface multithreaded server providing socket connections for concurrently deploying and executing actors Wakeup + reception Output object 3 4 Registration + sleep Actor id Messaging Interface ActorNet platforms are deployed on sensor nodes or PCs • Provide resource management, scheduling, communication, migration, sensing and actuation, etc., for actors. ActorNet Agent code for a call to the Detect Beam Primitive ( (lambda (migrate) ; actor behavior (seq ; migrate to destination (node 200, meta-actor id 111) (migrate 200 111) Break Beam Detector Example ; migrate to source (node 100) and report result (par (extmsg 111 (migrate 100 ; perform application logic: ; detectBeamEvent() primitive (#20) ; which takes no arguments (nil) (prim 20 nil) ))) For the break beam detector, the meta-level will generate the code for an actor of the Detect Beam step. • An ActorNet agent template is provided by the execution strategy • The Detect Beam meta-actor computes and fills in: • the destination sensor id (for migration) • meta-actor id (for communication) • the primitive to be executed (for application-specific functionality) • the arguments to the primitive (for control) )) ; migrate subroutine (lambda (adrs val) (callcc (lambda (cc) (send (list adrs cc (list quote val))))) ) ) How does Ambiance satisfy the requirements of uQuery Engines? The Ambiance platform supports: • Using a WSN to serve concurrent users • Dynamic, end-user-driven service specification • Complex queries, comprising sensing and actuation By extending the AOM model to mobile agent computing Query 1: determine ambient temperature and wind conditions While meeting WSN constraints: • Embedded, concurrent, distributed computing • On highly resource-limited hardware components • Work with a dynamic set of sensing resources Query 2: Detect and locate deer moving through the region Response to Query 1: temp=65ºF wind: SE, 3mph event The two-level approach to architecting uQuery Engines allows separating: • query representation and reasoning concerns, from • those of their effective execution on divers runtime platforms Adapted from: [Boulis, 2005] Response to Query 2: Deer at (10,35) moving NW at 5mph Hooks are provided for quality attributes, such as: • Security: automated supervision for security checks • Auditability: who has been involved in what • Non-repudiability: who has initiated which action Reusability and extendibility of: • The Ambiance Platform • Its query representation framework • through model-to-code transformation. Using a mobile agent system as the query execution environment provides: • dynamicity and concurrency of macroprogramming, while enabling • load balancing and other optimizations required by the WSN environment Separation of business logic primitives from the core of the mobile agent system, facilitates addition of new domain-specific primitives Web-based uQuery Engine User Interface Uses: Seaside framework (http://www.seaside.st/) and Squeak (http://www.squeak.org/)