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Spatial Programming using Smart Messages: Design and Implementation

Spatial Programming using Smart Messages: Design and Implementation. Cristian Borcea , Chalermek Intanagonwiwat, Porlin Kang, Ulrich Kremer, and Liviu Iftode Department of Computer Science Rutgers University. Computers Go Outdoors, Embedded Everywhere in the Physical World.

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Spatial Programming using Smart Messages: Design and Implementation

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  1. Spatial Programming using Smart Messages: Design and Implementation Cristian Borcea, Chalermek Intanagonwiwat, Porlin Kang, Ulrich Kremer, and Liviu Iftode Department of Computer Science Rutgers University

  2. Computers Go Outdoors, Embedded Everywhere in the Physical World Cars collaborating for a safer and more fluid traffic Distributed object tracking over a large geographical area

  3. Traditional (Indoor) Distributed Computing • Computation is distributed for performance or fault tolerance • Relatively easy to program • Nodes are computationally equivalent • Networking is robust and has acceptable delays • Configuration is stable

  4. Outdoor Distributed Computing • Computation is physically distributed • Nodes distributed across the physical space • Location-aware computing • Hard to program • Nodes are functionally heterogeneous and potentially mobile • Ad hoc wireless networks of embedded systems • Volatile configurations

  5. Example Mobile sprinkler with temperature sensor Left Hill Right Hill Hot spot • “Water the hottest spot on the Left Hill” • Number and location of mobile sprinklers are unknown • Configuration is not stable over time • Sprinklers move • Temperature changes

  6. Traditional Distributed Computing Does Not Work Well Outdoors • End-to-end data transfers may hardly complete • Fixed address naming and routing (e.g., IP) are too rigid • Difficult to deploy new applications in existing networks • Outdoor distributed computing requires novel abstractions and programming models • How to write outdoor distributed applications? • How to deploy new applications in existing networks?

  7. Outline • Motivation • Spatial Programming (SP) Model • SP Implementation using Smart Messages • SP Application • Conclusions

  8. Traditional (Indoor) Programming • Programs access data through variables • Variables mapped to physical memory locations • Page Table and OS guarantee reference consistency • Access time has an (acceptable) upper bound Program Variable access Virtual Address Space Page Table + OS Physical Memory

  9. From Indoor to Outdoor Computing Virtual Address Space Space Region Variables Spatial References Spatial references mapped to systems embedded in the physical space Variables mapped to physical memory Reference consistency ? ? Bounded access time

  10. Spatial Programming (SP) at a Glance • Provides a virtual name space over outdoor networks of embedded systems • Embedded systems named by their locations and properties • Runtime system takes care of name resolution, reference consistency, and networking aspects

  11. Space Regions Hill = new Space({lat, long}, radius); {lat,long} radius • Virtual representation of a physical space • Similar to a virtual address space in a conventional computer system • Defined statically or dynamically

  12. Spatial References {Hill:robot[0]} Hill {Hill:robot[1]} r7 r2 {Hill:motion[0]} m5 • Defined as {space:property} pairs • Virtual names for embedded systems • Similar to variables in conventional programming • Indexes used to distinguish among similar systems in the same space region

  13. Reference Consistency • At first access, a spatial reference is mapped to an embedded system located in the specified space • Mappings maintained in per-application Mapping Table (MT) – similar to a page table • Subsequent accesses to the same spatial reference will reach the same system (using MT) as long as it is located in the same space region {space, property, index} {unique_address, location}

  14. Reference Consistency Example r2 r7 r5 Right Hill Left Hill {Left_Hill:robot[0]}.move = ON; {Left_Hill:robot[0]}.move = OFF;

  15. Space Casting r7 Right Hill Left Hill {Left_Hill:robot[0]} {Right_Hill:(Left_Hill:robot[0])}

  16. Bounding the Access Time • How to bound the time to access a spatial reference? • Systems may move, go out of space, or disappear • Solution: associate an explicit timeout with the spatial reference access try{ {Hill:robot[0], timeout}.move = ON; }catch(TimeoutException e){ // the programmer decides the next action }

  17. Spatial Programming Example Water the hottest spot on the Left Hill Mobile sprinkler with temperature sensor Left Hill Right Hill Hot spot for(i=0; i<1000; i++) try{ if ({Left_Hill:Hot[i], timeout}.temp > Max_temp) Max_temp = {Left_Hill:Hot[i], timeout}.temp; Max_id = i; }catch(TimeoutException e) break; {Left_Hill:Hot[Max_id], timeout}.water = ON;

  18. Outline • Motivation • Spatial Programming (SP) Model • SP Implementation using Smart Messages • SP Application • Conclusions

  19. Smart Messages at a Glance • Smart Message (SM) • User defined distributed application similar to a mobile agent • Executes on nodes of interest named by properties • Migrates between nodes of interest using self-routing • Self-Routing • Application-level routing executed at every node • Applications can change routing during execution • Cooperative Nodes • Execution environment (Virtual Machine) • Memory addressable by names (Tag Space) • Code cache

  20. Smart Messages Prototype • Modified version of Sun’s Java K Virtual Machine • Small memory footprint (160KB) • SM and tag space primitives implemented inside virtual machine as native methods (efficiency) • Implemented I/O tags: GPS location, neighbor discovery, image capture, light sensor, system status

  21. Spatial Programming Implementation Using Smart Messages • SP application translates into an SM • Spatial reference access translates into an SM migration to the mapped node • Embedded system properties: Tags • SM self-routes using geographical routing and content-based routing • Reference consistency • Unique addresses (stored in mapping table) are unique tags created at nodes • SM carries the mapping table

  22. SP to SM Translation: Example Left Hill Right Hill Max_temp = {Left_Hill:Hot[1], timeout}.temp; Spatial Reference Access Mapping Table {Left_Hill,Hot,1} {yU78GH5,location} ret = migrate_geo(location, timeout); if (ret == LocationUnreachable) ret = migrate_tag(yU78GH5, timeout); if ((ret == OK) && (location == Left_Hill)) return readTag(temp); else throw TimeoutException Smart Message Code

  23. SP Application: Intrusion Detection Ad hoc network: HP iPAQs with 802.11 cards and GPS devices user node monitored space light sensor camera node regular node Code Size breakdown for SM (Application + SP Library) Code Size breakdown for SP library

  24. Execution Time Breakdown

  25. Conclusions • Spatial Programming makes outdoor distributed computing simple • Volatility, mobility, configuration dynamics, ad-hoc networking are hidden from programmer • Implementation on top of Smart Messages • Easy to deploy new applications in the network • Quick adaptation to highly dynamic network configurations

  26. Thank you! http://discolab.rutgers.edu/sp/

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