Middleware for Wireless Sensor Networks Présenté par Andrei

Middleware for Wireless Sensor Networks Présenté par Andrei Marculescu 1

Plan • • Middleware for WSN Overview of current approaches Classification 2

Middleware – definition (1) • Context : – Distributed systems • Goal : – Help manage complexity and heterogeneity • Location : – Layer between the OS and the application program • OS vs Middleware : – OS makes a hardware useable – Middleware makes a distributed system programmable 3

Middleware – services view (1) • Middleware can be classified in terms of the services provided to applications 4

Middleware – services view (2) • Type of services – Presentation Services • Graphics, forms, printing services – Computation Services • Sorting, math services, time services – Information Services • Directories, log management, shared data – Communication Services • Messaging, procedure calls – Control Services • Transaction, thread management, job scheduling – System Services • Event notification, software installation, authentication 5

Middleware – abstraction view (1) • Distributed Tuples – Shared tuple space – Processes post and read tuples • Unaware of each other’s identities • Examples – Distributed relational databases – Linda (Yale University) – Jini (Sun) + Information, Control 6

Middleware – abstraction view (2) • Remote Procedure Call (RFC 1831) – Possibility to invoke a procedure whose body is accros a network • Example – Sun’s RPC + Communication 7

Middleware – abstraction view (3) • Message-oriented middleware – Message passing and/or queuing • Synchronous vs asynchronous – Facilitates communication between distributed applications • Example – IBM’s Web. Sphere MQ + Communication 8

Middleware – abstraction view (4) • Distributed Object Middleware – Remote object, whose methods can be invoked like local methods • Examples – CORBA (Common Object Request Broker Architecture) – Java RMI (Remote Method Invocation) –. NET (Remote) + Communication (Computation) Þ Control, Information, System 9 ? Presentation (. NET)

Middleware – abstraction view (5) • Service Oriented Middleware – Services become a programming abstraction • Semantically described – Existing services are available through Service directories – New services are available through dynamic service composition • Examples – Web Services (WSDL) + Information, Communication, Computation 10

Middleware – abstraction view (6) • Agent Oriented Middleware – Agents are the programming abstraction – Keywords • Autonomy • Flexibility • Code Mobility • Examples – JADE + All (complex, dynamic systems) 11

Middleware - conclusions • Existing approaches are adapted to distributed systems • Middlewares tend to provide more and more services – Universal tools – Heavy environments • Exceptions exist : CORBA for embedded systems – Agents are used only for a restricted class of problems 12

Plan • • Middleware for WSN Overview of current approaches Classification 13

Middleware for WSN (1) • • • Data-centric querying and processing Localized algorithms Limited resources Dynamic network Application knowledge 14

Middleware for WSN (2) • New programming abstractions – Cluster-based • Resource-aware software – Adaptive • Application-aware middleware – Quality of service • Lightweight software – More tightly coupled to the OS ? 15

Plan • • Middleware for WSN Overview of current approaches Classification 16

Current Approaches • Impala • Maté • Querying – Tiny. DB – SQTL • Sensor Querying and Tasking Language • Generic Role Assignment 17

Impala – overview (1) • Designed for Zebra. Net project – mobile sensor network – deployment, management and communications problems • Zebra. Net HW – – – 32 KHz – 8 MHz CPU => 9. 6 – 19. 32 m. W 8 MHz GPS receiver => 568 m. W 8 MHz radio xmit => 780 m. W 8 MHz radio rcv => 312 m. W 1 – 8 MB non-volatile storage 18

Impala – overview (2) • Classical approach – Service oriented • Deployment (on-the-fly software updates) • Thread management (application switching) • Event-filtering • Novel approach – Resource-aware, application knowledge • Adaptative – OS-middleware hybrid 19

Impala – system architecture 20

Impala – adaptability • Routing protocols switching – History-based – Flooding 21

Current Approaches • Impala • Maté • Querying – Tiny. DB – SQTL • Sensor Querying and Tasking Language • Generic Role Assignment 22

Maté - overview • VM approach – Bytecode interpreter on top of Tiny. OS • Fixed-size instructions (1 byte) • Fixed-size code capsules – 24 instructions – Identifying and version information – A program can contain several capsules • Operand stack and return address stack – Highly optimized resource management • Memory management • Network management 23

Maté – execution model Code capsules Execution contexts Shared variable 24

Maté – instruction set • Assembly language style • Built-in high-level functions – send instruction • Default routing protocol : send • Possible extensions : sendr – code broadcast : forw – Logging : log / logr – Shared variable access : gets / sets – Sensing 25

Maté – example 26

Current Approaches • Impala • Maté • Querying – Tiny. DB – SQTL • Sensor Querying and Tasking Language • Generic Role Assignment 27

Tiny. DB - overview • High-level querying – Well-known declarative language – Hides the network • One virtual table with nodes as rows • Every node attribute represents a column – Tiny. SQL language • No neighborhood management – Global spanning tree for queries – Requests are flooded to all nodes Scalability, efficiency ? 28

Tiny. DB - example SELECT AVERAGE(temp) FROM SENSORS WHERE TEMP > 20 TRIGGER ACTION Set. Snd(512) EPOCH DURATION 512 Single table Trigger sound During query Repeat query every 512 ms 29

SQTL - overview • Distributed querying design – Queries are injected into the network – Some queries need coordination – Queries are processed locally by sensor nodes • Distributed tasking capabilities – Collaborative work • Moving vehicle detection 30

SQTL - overview • Meta-language for messages – SQTL Wrapper • New querying and tasking language – SQLT • Sensor execution environment – SEE 31

SQLT Wrapper (1) • Message => (action (: param value)+) Language independent 32

SQLT Wrapper (2) • Example (execute : sender FRONTEND : receiver (: group NODE(1) : criteria TRUE) : application-id 123 : language SQTL : content ( // SQLT code here ) ) 33

SQTL language (1) • Lightweight object oriented language • Event handling primitives (upon) • Communication primitives (tell, receive) • Sensor access primitives (get. Temp. Sensor()) 34

SQTL language (2) • Example : SELECT Max(get. Temperature()) FROM ALL_NODES 35

SEE • Message demultiplexing • Concurrent execution of several applications 36

Current Approaches • Impala • Maté • Querying – Tiny. DB – SQTL • Sensor Querying and Tasking Language • Generic Role Assignment 37

Generic Role Assignment (GRA) • Self-organizing network – Nodes • Evaluate their status • Agree on their roles assignment in the network – Developer • Implement role specifications 38

GRA – status evaluation • Based on a property directory (cache) • One directory on each node 39

GRA – role specification • Every nodes have a copy of the same role specification • Role examples – ON / OFF (turning off redundant nodes) – CLUSTERHEAD / GATEWAY / SLAVE (improving data delivery with clustering) – SOURCE / DATA AGGREGATOR / SINK (data aggregation) • A role specification is a list of role-rule pairs ON : : { temp-sensor == true && battery >= threshold && count(2 hops) { role == ON && dist(super. pos, pos) <= sensing-range } <= 1 } OFF : : else 40

GRA – role assignment • Role assignment algorithm – Triggered by property changes – Evaluates rules in the rule specification – If a rule evaluate to true, the associated role is assigned 41

Plan • • Middleware for WSN Overview of current approaches Classification 42

Classification (1) • New important programming abstraction – Cluster based • Distributed VM • Service Oriented Maté VM Tiny. DB SQTL GRA Cluster based Hood SO Impala 43

Classification (2) • Two levels of middleware – « external » • Global Internet view – Identify services provided by a sensor network – « internal » • Programmer’s view – Identify abstractions that facilitate network programming • Ex. Tiny. DB tries to merge these two levels 44

Questions ? 45

Bibliographie P. A. Bernstein. Middleware: a model for distributed system services. Communications of the ACM, 39(2): 86 -98, 1996 K. Römer, O. Kasten, F. Mattern, "Middleware challenges for wireless sensor networks", Mobile Computing and Communications Review, vol. 6, no. 2, 2002 T. Liu and M. Martonosi. Impala: A Middleware System for Managing Autonomic, Parallel Sensor Systems. In ACM SIGPLAN Symp. on Principles and Practice of Parallel Programming (PPo. PP), June 2003 P. Levis and D. Culler. Mate: A Tiny Virtual Machine for Sensor Networks. In Proceedings of the 10 th International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS-X), Oct. 2002 C. Jaikaeo, C. Srisathapornphat, and C. -C. Shen, "Querying and Tasking in Sensor Networks, " SPIE's 14 th Annual Int'l. Symp. Aerospace/Defense Sensing, Simulation, and Control, Orlando, FL, Apr. 2000 Frank, C. and Römer, K. 2005. Algorithms for generic role assignment in wireless sensor networks. In Proceedings of the 3 rd international Conference on Embedded Networked Sensor Systems (San Diego, California, USA, November 02 - 04, 2005). Sen. Sys '05. ACM Press, New York, NY, 230 -242. Terfloth, K. , Schiller, J. : "Driving Forces behind Middleware Concepts for Wireless Sensor Networks". Submitted - under review, April 2005 Kamin Whitehouse, Cory Sharp, Eric Brewer, and David Culler. Hood: a neighborhood abstraction for sensor networks. In Mobi. SYS '04: Proceedings of the 2 nd international conference on Mobile systems, applications, and services, pages 99 --110. ACM Press, 2004 46