Programming Sensor Networks Andrew Chien CSE291 Spring 2003 May 6, 2003

CSE 291 Sensor Networks – 5/6/2003 Outline Applications Requirements Programming Challenges Technology Challenges Current Approaches New Directions

CSE 291 Sensor Networks – 5/6/2003 Applications Requirements Broad and Amorphous Tremendous breadth No single design point What are some example requirements…

CSE 291 Sensor Networks – 5/6/2003 Static Sensing Mission Examples: industrial, bridge, civil infrastructure, environmental monitoring Static Deployment of Sensor network Limited mission change, evolution Update dominated by management and failure/repair Slow adaptation, configuration acceptable Monitor and Activate in response to stimuli Capture data and process Stream to base station systems

CSE 291 Sensor Networks – 5/6/2003 Dynamic Sensing Mission Examples: disaster response, military or police search, surveillance Dynamic deployment of sensor network Rapid mission change, rapid evolution on command Update limited due to short intense missions, but reconfiguration to changing mission Fast adaptation, configuration critical Monitor and Activate in response to stimuli Capture data and process Process in network and actuate or Stream to base station systems

CSE 291 Sensor Networks – 5/6/2003 Dynamic Network Structure Examples: airborne, water born, vehicle born, zebra born sensornets »Coastal Sensor NetworksCoastal Sensor Networks Dynamic deployment of sensor network Slow mission change, evolution Rapid network structure change due to physical movement, environment change, or failures Fast adaptation, configuration critical Monitor and Activate in response to stimuli Capture data and process Process in network and actuate or Stream to base station systems

CSE 291 Sensor Networks – 5/6/2003 Sensor Network Programming Challenges Describe the distributed computation and sensing structures Manage/Tolerate the irregular and changing network structure to achieve the computational goal Reflect the accuracy / capability with which the sensor network can achieve mission Detect needs for reconfiguration and repair Enable optimization of program structure by automatic tools Enable adaptation of program structure to new configurations with automatic tools Enable gracefully degrading behavior with loss of resources and same source program Enable energy/resource conservation with techniques such as sleep/idle Others?

CSE 291 Sensor Networks – 5/6/2003 Relevant Technologies Raise the level »High Level and Declarative Programming –Tolerance to change, portability »Parallel computation –Management of Computation/Communication, Concurrency, and Distribution –Aggressive compiler control of behavior/implementation

CSE 291 Sensor Networks – 5/6/2003 Relevant Foundations Distributed Systems and FT community »Protocols, algorithms, implementation knowledge, programming techniques Embedded and RT systems community »Local tools »Managing resource requirements

CSE 291 Sensor Networks – 5/6/2003 Technology Challenges Powered and Limited power Limited interconnectivity (link, bisection), external connectivity Limited coordination Limited memory Unreliable nodes Network evolution (upgrades and failures)

CSE 291 Sensor Networks – 5/6/2003 Current Approaches C++ and Embedded SW Engineering NesC TinyDB

CSE 291 Sensor Networks – 5/6/2003 C++ & Embedded SW Engin. Cyclic executive or Priority Driven scheduler Collection of real-time tasks Manually Manage (some tools) »Concurrency and correctness »Memory constraints »Distributed application structure »Irregular sensor node distribution »Sensor network change/evolution C++

CSE 291 Sensor Networks – 5/6/2003 NesC TinyOS like interface with »Call/Event Pairs »Concurrency safety conditions »Type Checking Manually Manage »concurrency and correctness (some help) »memory constraints »distributed application structure »Irregular sensor node distribution »Sensornetwork change/evolution Cmd/ Event Cmd/ Event Cmd/ Event Cmd/ Event

CSE 291 Sensor Networks – 5/6/2003 TinyDB Relational Model (table of sensor data sources) Simple Operators Semantics for transformation / implementation of Queries »Optimize deployment and implementation for power Acquisitional Query processing »Optimize implementation and data acquisition for power Manually Manage »concurrency and correctness (some help) »memory constraints »distributed application structure (some help) »Irregular sensor node distribution (some help) »Sensornetwork change/evolution (some help) Global Queries Query Plan and Map

New Directions

CSE 291 Sensor Networks – 5/6/2003 Spatial Programming Spatial structures (processor array) in programming systems Spatial structure physical space ? »Fortran D / HPF (imperative, spatial, explicit optimization/communication management) Global Program + Partition Data, Map/Optimize

CSE 291 Sensor Networks – 5/6/2003 Collection Programming Collection structures sensor collections? »Nesl »CA/ICC++ »Object-oriented Simulation models Elements »Collection oriented naming »Collection structuring, indexing »Programmed cooperative behavior »Presumed distribution and optimization Global Program + Map/Optimize

CSE 291 Sensor Networks – 5/6/2003 Data/Communication Oriented Local program + communication models which support asynchronous interactions »Tuple Spaces (Linda) »Publish-subscribe »Bulletin Boards Data dissemination systems – content-based query systems »Peer to peer systems (gnutella, freenet, etc.); Content Filtering/ranking systems (OpenCola, others) TinyDB implementation techniques or different semantic framework? -> we won’t focus on these … …… … Point To Point Tuple Space Pub- Sub Bulletin Boards

CSE 291 Sensor Networks – 5/6/2003 Summary / Discussion Just scratched the surface on the programming problem Low-level mechanisms and relational model provide starting point Higher level models common threads »Global views »Imperative control »Explicit decoupling of expression from underlying resources »Expose distribution for compiler managed communication »Support for asynchrony Will explore over coming weeks

CSE 291 Sensor Networks – 5/6/2003