Name
Abstract | ||
|---|---|---|
The development of high-level programming environments is es- sential if wireless sensor networks are to be accessible to non- experts. In this paper, we present the Regiment system, which con- sists of a high-level language for spatiotemporal macroprogram- ming, along with a compiler that translates global programs into node-level code. In Regiment, the programmer views the network as a set of spatially-distributed data streams. The programmer can manipulate sets of these streams that may be defined by topologi- cal or geographic relationships between nodes. Regiment provides a rich set of primitives for processing data on individual streams, manipulating regions, performing aggregation over a region, and triggering new computation within the network. In this paper, we describe the design and implementation of the Regiment language and compiler. We describe the deglobaliza- tion process that compiles a network-wide representation of the program into a node-level, event-driven program. Deglobalization maps region operations onto associated spanning trees that estab- lish region membership and permit efficient in-network aggrega- tion. We evaluate Regiment in the context of a complex distributed application involving rapid detection of spatially-distributed events, such as wildfires or chemical plumes. Our results show that Reg- iment makes it possible to develop complex sensor network appli- cations at a global level. |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1145/1236360.1236422 | Information Processing in Sensor Networks |
Keywords | Field | DocType |
regiment language,deglobalization maps region operation,wireless sensor network,complex sensor network application,global level,efficient in-network aggregation,event-driven program,global program,regiment macroprogramming system,regiment system,functional macroprogramming,region membership,sensor networks,high level languages,wireless sensor networks,distributed application,computer networks,languages,sensor network,design,high level language,functional programming,high level programming,signal processing,spanning tree | Data stream mining,Programmer,Functional programming,Computer science,Deglobalization,Compiler,Real-time computing,High-level programming language,Spanning tree,Wireless sensor network,Distributed computing | Conference |
Citations | PageRank | References |
79 | 6.29 | 12 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ryan Newton | 1 | 802 | 70.80 |
| J. Gregory Morrisett | 2 | 2364 | 182.65 |
| Matt Welsh | 3 | 7657 | 599.18 |