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MacroLab: a vector-based macroprogramming framework for cyber-physical systems

Published: 05 November 2008 Publication History

Abstract

We present a macroprogramming framework called MacroLab that offers a vector programming abstraction similar to Matlab for Cyber-Physical Systems (CPSs). The user writes a single program for the entire network using Matlab-like operations such as addition, find, and max. The framework executes these operations across the network in a distributed fashion, a centralized fashion, or something between the two - whichever is most efficient for the target deployment. We call this approach deployment-specific code decomposition (DSCD). MacroLab programs can be executed on mote-class hardware such as the Telos [24] motes. Our results indicate that MacroLab introduces almost no additional overhead in terms of message cost, power consumption, memory footprint, or CPU cycles over TinyOS
programs.

References

[1]
The mathworks. http://www.mathworks.com/.
[2]
J. Bachrach and J. Beal. Programming a Sensor Network as an Amorphous Medium. Technical report, MIT'06.
[3]
R.-G. Chang, T.-R. Chuang, and J.-K. Lee. Compiler optimizations for parallel sparse programs with array intrinsics of fortran 90. In ICPP'99.
[4]
Crossbow. Micaz datasheet. http://www.xbow.com/Products/Product_pdf_files/Wireless_pdf/MICAz_Datasheet.pdf.
[5]
D. E. Culler, A. Dusseau, S. C. Goldstein, A. Krishnamurthy, S. Lumetta, T. V. Eicken, and K. Yelick. Parallel programming in Split-C. In Supercomputing'93.
[6]
D. Estrin, R. Govindan, J. S. Heidemann, and S. Kumar. Next century challenges: Scalable coordination in sensor networks. In MobiCom'99.
[7]
C.-L. Fok, G. C. Roman, and C. Lu. Rapid development and exible deployment of adaptive wireless sensor network applications. In ICDCS'05.
[8]
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'03.
[9]
O. Gnawali, K.-Y. Jang, J. Paek, M. Vieira, R. Govindan, B. Greenstein, A. Joki, D. Estrin, and E. Kohler. The tenet architecture for tiered sensor networks. In SenSys'06.
[10]
R. Gummadi, O. Gnawali, and R. Govindan. Macro-programming wireless sensor networks using Kairos. In DCOSS'05.
[11]
S. Hiranandani, K. Kennedy, C. Koelbel, U. Kremer, and C.-W. Tseng. An overview of the Fortran D programming system. In LCPC'91.
[12]
G. C. Hunt and M. L. Scott. The Coign automatic distributed partitioning system. In OSDI'99.
[13]
M. Jovanovic and V. Milutinovic. An overview of reflective memory systems. IEEE Concurrency'99.
[14]
N. Kothari, R. Gummadi, T. D. Millstein, and R. Govindan. Reliable and efficient programming abstractions for wireless sensor networks. In PLDI'07.
[15]
P. Levis, S. Madden, J. Polastre, R. Szewczyk, K. Whitehouse, A. Woo, D. Gay, J. Hill, M. Welsh, E. Brewer, et al. TinyOS: An Operating System for Sensor Networks.
[16]
H. Liu, T. Roeder, K. Walsh, R. Barr, and E. G. Sirer. Design and implementation of a single system image operating system for ad hoc networks. In MobiSys'05.
[17]
L. Luo, T. Abdelzaher, T. He, and J. Stankovic. EnviroSuite: An environmentally immersive programming framework for sensor networks. TECS'06.
[18]
S. R. Madden, M. J. Franklin, J. M. Hellerstein, and W. Hong. Tinydb: an acquisitional query processing system for sensor networks. ACM Trans. Database Syst.'05.
[19]
S. R. Madden, M. J. Franklin, J. M. Hellerstein, and W. Hong. TAG: a Tiny AGgregation Service for Ad-Hoc Sensor Networks. In OSDI, December 2002.
[20]
G. Mainland, M. Welsh, and G. Morrisett. Flask: A language for data-driven sensor network programs. Technical report, Harvard'06.
[21]
R. Müller, G. Alonso, and D. Kossmann. A virtual machine for sensor networks. In EuroSys'07.
[22]
R. Newton, G. Morrisett, and M. Welsh. The regiment macroprogramming system. IPSN'07.
[23]
J. Polastre, J. Hill, and D. Culler. Versatile low power media access for wireless sensor networks. In SenSys'04.
[24]
J. Polastre, R. Szewczyk, and D. Culler. Telos: enabling ultra-low power wireless research. IPSN'05.
[25]
G. Ramalingam. Data ow frequency analysis. In PLDI'96.
[26]
H. Richardson. High performance fortran: history, overview and current developments. Technical report, Thinking Machines Corporation'96.
[27]
E. Schonberg, J. T. Schwartz, and M. Sharir. Automatic data structure selection in setl. In POPL'79.
[28]
C. Sharp, S. Schaffert, A. Woo, N. Sastry, C. Karlof, S. Sastry, and D. Culler. Design and implementation of a sensor network system for vehicle tracking and autonomous interception. In EWSN'05.
[29]
E. Tilevich and Y. Smaragdakis. J-orchestra: Automatic java application partitioning. In ECOOP'02.
[30]
M. Welsh and G. Mainland. Programming sensor networks using abstract regions. In NSDI'04.
[31]
K. Whitehouse, J. Liu, and F. Zhao. Semantic streams: a framework for composable inference over sensor data. In EWSN'06.
[32]
K. Whitehouse, C. Sharp, E. Brewer, and D. Culler. Hood: a neighborhood abstraction for sensor networks. In MobiSys'04.
[33]
K. Whitehouse, G. Tolle, J. Taneja, C. Sharp, S. Kim, J. Jeong, J. Hui, P. Dutta, and D. Culler. Marionette: using rpc for interactive development and debugging of wireless embedded networks. In IPSN'06.
[34]
Y. Yao and J. Gehrke. The cougar approach to in-network query processing in sensor networks. SIGMOD'02.

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  • (2023)Macroprogramming: Concepts, State of the Art, and Opportunities of Macroscopic Behaviour ModellingACM Computing Surveys10.1145/357935355:13s(1-37)Online publication date: 13-Jul-2023
  • (2020)Survey on Unmanned Aerial Vehicle Networks: A Cyber Physical System PerspectiveIEEE Communications Surveys & Tutorials10.1109/COMST.2019.296220722:2(1027-1070)Online publication date: Oct-2021
  • (2019)Model driven framework to enhance sensor network design cycleTransactions on Emerging Telecommunications Technologies10.1002/ett.356030:8Online publication date: 14-Aug-2019
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Published In

cover image ACM Conferences
SenSys '08: Proceedings of the 6th ACM conference on Embedded network sensor systems
November 2008
468 pages
ISBN:9781595939906
DOI:10.1145/1460412
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Publication History

Published: 05 November 2008

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Author Tags

  1. cyber-physical systems
  2. embedded networks
  3. macroprogramming
  4. programming abstractions

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Overall Acceptance Rate 174 of 867 submissions, 20%

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Cited By

View all
  • (2023)Macroprogramming: Concepts, State of the Art, and Opportunities of Macroscopic Behaviour ModellingACM Computing Surveys10.1145/357935355:13s(1-37)Online publication date: 13-Jul-2023
  • (2020)Survey on Unmanned Aerial Vehicle Networks: A Cyber Physical System PerspectiveIEEE Communications Surveys & Tutorials10.1109/COMST.2019.296220722:2(1027-1070)Online publication date: Oct-2021
  • (2019)Model driven framework to enhance sensor network design cycleTransactions on Emerging Telecommunications Technologies10.1002/ett.356030:8Online publication date: 14-Aug-2019
  • (2018)Towards an Easily Programmable IoT Framework Based on MicroservicesJournal of Software10.17706/jsw.13.2.90-10213:1(90-102)Online publication date: Feb-2018
  • (2017)Designing Swarms of Cyber-Physical SystemsProceedings of the Computing Frontiers Conference10.1145/3075564.3077628(305-312)Online publication date: 15-May-2017
  • (2017)Research and challenges of CPS10.1063/1.4992851(020034)Online publication date: 2017
  • (2016)Markov Task Network: A Framework for Service Composition under Uncertainty in Cyber-Physical SystemsSensors10.3390/s1609154216:9(1542)Online publication date: 21-Sep-2016
  • (2016)A Smart Platform for Large-Scale Cyber-Physical SystemsManagement of Cyber Physical Objects in the Future Internet of Things10.1007/978-3-319-26869-9_6(115-134)Online publication date: 30-Jan-2016
  • (2016)Motivation, Market and European PerspectiveModern Stroke Rehabilitation through e-Health-based Entertainment10.1007/978-3-319-21293-7_1(1-26)Online publication date: 2016
  • (2015)Application Development Framework for Developing Cyber-Physical SystemsCyber-Physical Systems10.1201/b19290-26(437-470)Online publication date: 13-Oct-2015
  • Show More Cited By

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