article

TinyVM: an energy-efficient execution infrastructure for sensor networks

Authors:

Bernd Burgstaller,

Bernhard ScholzAuthors Info & Claims

Software—Practice & Experience, Volume 42, Issue 10

Pages 1193 - 1209

https://doi.org/10.1002/spe.1123

Published: 01 October 2012 Publication History

Abstract

Energy-efficient implementation techniques for virtual machines (VMs) have received little attention yet: conventional wisdom claims that VMs have a diametrical effect on energy consumption, and VM-based applications are therefore short-lived. In this paper, we argue that bytecode interpretation is affordable if we synthesize VMs specifically for energy efficiency. We present TinyVM, an execution infrastructure that seamlessly integrates with C and nesC/TinyOS-based programming environments. TinyVM achieves high code density through the use of compressed bytecode as the primary program representation. Compressed bytecode allows rapid application deployment with low communication overhead. TinyVM executes compressed bytecode in place, which eliminates the need for a decompression stage and thereby reduces memory consumption on sensor nodes. Our infrastructure automates the creation of energy-efficient application-specific VMs. Applications are partitioned in machine code, bytecode, and VM instruction set extensions. Partitioning is manually controlled and/or fully guided by a discrete optimization problem that produces a partitioning with lowest energy consumption for a given program size limit. We provide experimental results for sensor network benchmarks and for selected applications on various CPU architectures including Atmega128-based motes and the ARM-based Intel iMote2. TinyVM has been released under the GNU General Public License. Copyright © 2011 John Wiley & Sons, Ltd.

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Cited By

Vikash Mishra LVarma S(2021)Middleware Technologies for Smart Wireless Sensor Networks towards Internet of Things: A Comparative ReviewWireless Personal Communications: An International Journal10.1007/s11277-020-07748-7116:3(1539-1574)Online publication date: 1-Feb-2021
https://dl.acm.org/doi/10.1007/s11277-020-07748-7
Reijers NShih C(2019)Improved Ahead-of-time Compilation of Stack-based JVM Bytecode on Resource-constrained DevicesACM Transactions on Sensor Networks10.1145/334117015:3(1-44)Online publication date: 13-Aug-2019
https://dl.acm.org/doi/10.1145/3341170
Giri ADutta SNeogy SDahal KPervez ZHamdan HBoubiche DKlett F(2017)Internet of things (IoT)Proceedings of the 1st International Conference on Internet of Things and Machine Learning10.1145/3109761.3109768(1-12)Online publication date: 17-Oct-2017
https://dl.acm.org/doi/10.1145/3109761.3109768

Index Terms

TinyVM: an energy-efficient execution infrastructure for sensor networks
1. Software and its engineering
  1. Software notations and tools
    1. Development frameworks and environments

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Reviews

Reviewer: William M. Waite

TinyVM has a typical stack architecture, but in this paper, no details of its instruction set or register structure are given. Rather, the authors present a complex infrastructure for creating energy-efficient execution images on a variety of hardware. Their basic idea is to decompose a program into components, each of which is implemented in one of three ways: as byte code for TinyVM, as a domain-specific extension of TinyVM, or as native code for the underlying machine. Each implementation technique has advantages and disadvantages with respect to speed, space, and energy consumption. The trick is to find the best combination according to some predefined criteria. The paper begins with a discussion of the compilation environment that allows a program to be split, with each part processed appropriately, and the results to be combined. The authors then consider the problem of performing the split automatically. They prove that this multi-objective problem is nondeterministic polynomial-time (NP) hard, but provide an approximation algorithm. Results from the approximation algorithm are then presented and discussed, and related work reviewed. I found the paper interesting, particularly the range of technology that the authors used to build their infrastructure. The explanations of the infrastructure are clear, but to get some of the subtleties, I found it necessary to look into the paper's extensive references. Nevertheless, the material is accessible to anyone with a rudimentary understanding of compiler construction. Online Computing Reviews Service

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cover image Software

Software Volume 42, Issue 10

October 2012

119 pages

ISSN:0038-0644

EISSN:1097-024X

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John Wiley & Sons, Inc.

United States

Publication History

Published: 01 October 2012

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Cited By

Vikash Mishra LVarma S(2021)Middleware Technologies for Smart Wireless Sensor Networks towards Internet of Things: A Comparative ReviewWireless Personal Communications: An International Journal10.1007/s11277-020-07748-7116:3(1539-1574)Online publication date: 1-Feb-2021
https://dl.acm.org/doi/10.1007/s11277-020-07748-7
Reijers NShih C(2019)Improved Ahead-of-time Compilation of Stack-based JVM Bytecode on Resource-constrained DevicesACM Transactions on Sensor Networks10.1145/334117015:3(1-44)Online publication date: 13-Aug-2019
https://dl.acm.org/doi/10.1145/3341170
Giri ADutta SNeogy SDahal KPervez ZHamdan HBoubiche DKlett F(2017)Internet of things (IoT)Proceedings of the 1st International Conference on Internet of Things and Machine Learning10.1145/3109761.3109768(1-12)Online publication date: 17-Oct-2017
https://dl.acm.org/doi/10.1145/3109761.3109768

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