Scalaness/nesT: type specialized staged programming for sensor networks
Abstract
Programming wireless embedded networks is challenging due to severe limitations on processing speed, memory, and bandwidth. Staged programming can help bridge the gap between high level code refinement techniques and efficient device level programs by allowing a first stage program to specialize device level code. Here we introduce a two stage programming system for wireless sensor networks. The first stage program is written in our extended dialect of Scala, called Scalaness, where components written in our type safe dialect of nesC, called nesT, are composed and specialized. Scalaness programs can dynamically construct TinyOS-compliant nesT device images that can be deployed to motes. A key result, called cross-stage type safety, shows that successful static type checking of a Scalaness program means no type errors will arise either during programmatic composition and specialization of WSN code, or later on the WSN itself. Scalaness has been implemented through direct modification of the Scala compiler. Implementation of a staged public-key cryptography calculation shows the sensor memory footprint can be significantly reduced by staging.
References
[1]
D. Ancona and E. Zucca. A calculus of module systems. Journal of functional programming, 11:91--132, 2002.
[2]
L. Cardelli. Program fragments, linking, and modularization. In POPL, pages 266--277, 1997.
[3]
L. Cardelli and P. Wegner. On understanding types, data abstraction, and polymorphism. ACM Comput. Surv., 17(4):471--523, 1985.
[4]
P. Chapin and C. Skalka. SpartanRPC: Secure WSN middleware for cooperating domains. In MASS, November 2010.
[5]
P. Chapin and C. Skalka. Spartan RPC. Technical report, University of Vermont, 2013. Submitted. http://www.cs.uvm.edu/~skalka/skalka-pubs/ chapin-skalka-spartanrpctr.pdf.
[6]
E. Cheong. Actor-Oriented Programming for Wireless Sensor Networks. PhD thesis, University of California, Berkeley, 2007.
[7]
A. Chlipala. Ur: Statically-typed metaprogramming with type-level record computation. In PLDI, 2010.
[8]
C. Consel, L. Hornof, R. Marlet, G. Muller, S. Thibault, E.-N. Volanschi, J. Lawall, and J. Noyé. Tempo: specializing systems applications and beyond. ACM Comput. Surv., 1998.
[9]
P. K. Dutta, J. W. Hui, D. C. Chu, and D. E. Culler. Securing the deluge network programming system. In IPSN, pages 326--333, 2006.
[10]
M. Flatt and M. Felleisen. Units: Cool modules for HOT languages. In PLDI, 1998.
[11]
J. Frolik and C. Skalka. Snowcloud: A complete system for snow hydrology research. In RealWSN, 2013.
[12]
D. Gay, P. Levis, R. von Behren, M. Welsh, E. Brewer, and D. Culler. The nesC language: A holistic approach to networked embedded systems. In PLDI, 2003.
[13]
G. Ghelli and B. Pierce. Bounded existentials and minimal typing. Theoretical Computer Science, 193(1-2):75--96, 1998.
[14]
D. Gregor, J. Järvi, J. G. Siek, G. D. Reis, B. Stroustrup, and A. Lumsdaine. Concepts: Linguistic support for generic programming in C++. In OOPSLA, 2006.
[15]
K. Hammond and G. Michaelson. Hume: A domain-specific language for real-time embedded systems. In GPCE, pages 37--56. Springer- Verlag, 2003.
[16]
J. Hill, R. Szewczyk, A. Woo, S. Hollar, D. E. Culler, and K. S. J. Pister. System architecture directions for networked sensors. In ASPLAS, pages 93--104, 2000.
[17]
A. Igarashi, B. C. Pierce, and P. Wadler. Featherweight Java. ACM Trans. Program. Lang. Syst., 23(3):396--450, 2001.
[18]
N. Li and J. C. Mitchell. RT: A role-based trust-management framework. In Proceedings of the 3rd DARPA Information Survivability Conference and Exposition, pages 201--212, 2003.
[19]
A. Liu and P. Ning. Tinyecc: A configurable library for elliptic curve cryptography in wireless sensor networks. In IPSN, pages 245--256, 2008.
[20]
Y. Liu, C. Skalka, and S. Smith. Type-specialized staged programming with process separation. HOSC, pages 341--385, 2011.
[21]
D. MacQueen. Modules for Standard ML. In Proceedings of ACM Conference on Lisp and Functional Programming, 1984.
[22]
S. Madden, M. J. Franklin, J. M. Hellerstein, and W. Hong. TAG: a Tiny AGgregation service for ad-hoc sensor networks. SIGOPS Oper. Syst. Rev., 36(SI):131--146, 2002.
[23]
G. Mainland. Explicitly heterogeneous metaprogramming with MetaHaskell. In ICFP, 2012.
[24]
G. Mainland, G. Morrisett, and M. Welsh. Flask: staged functional programming for sensor networks. In ICFP, 2008.
[25]
J. Mitchell, S. Meldal, and N. Madhav. An extension of standard ML modules with subtyping and inheritance. In POPL, 1991.
[26]
C. D. Moeser, M. Walker, C. Skalka, and J. Frolik. Application of a wireless sensor network for distributed snow water equivalence estimation. In Western Snow Conference, 2011.
[27]
T. Molhave and L. H. Petersen. Assignment Featherweight Java. Master's thesis, University of Aarhus, 2005.
[28]
L. Mottola and G. P. Picco. Programming wireless sensor networks. ACM Computing Surveys, 2011.
[29]
G. C. Necula, S. McPeak, and W. Weimer. CCured: type-safe retrofitting of legacy code. In POPL, 2002.
[30]
M. Odersky, L. Spoon, and B. Venners. Programming in Scala, second edition. Artima, Inc, 2011.
[31]
T. Rompf and M. Odersky. Lightweight modular staging: a pragmatic approach to runtime code generation and compiled DSLs. In GPCE, pages 127--136, 2010.
[32]
W. Taha. Resource-aware programming. In ICESS, pages 38--43, 2004.
[33]
W. Taha and T. Sheard. Multi-stage programming with explicit annotations. In PEPM, pages 203--217, 1997. ISBN 0-89791-917-3.
[34]
R. Willett, A. Martin, and R. Nowak. Backcasting: adaptive sampling for sensor networks. In IPSN, pages 124--133, 2004.
Index Terms
- Scalaness/nesT: type specialized staged programming for sensor networks
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Published In
March 2014
181 pages
ISSN:0362-1340
EISSN:1558-1160
DOI:10.1145/2637365
- Editors:
- Mark W. Bailey,
- Jaakko Järvi,
- Christian Kästner
October 2013198 pages
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Publication History
Published: 27 October 2013
Published in SIGPLAN Volume 49, Issue 3
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