An Energy Consumption Model for an Embedded Java Virtual Machine

Lafond, Sébastien; Lilius, Johan

doi:10.1007/11682127_22

Cited by 17 publications

(16 citation statements)

References 4 publications

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“…Farkas et al [3] have measured the energy consumption of the Itsy Pocket Computer and the JVM running on it. As shown in Figure 1, a JVM generally has five stages during its life cycle [12]. Farkas et al have discussed different JVMs' design trade-offs in each stage, studied their applicability to pocket computers, and measured their energy consumption.…”

Section: An Energy Consumption Framework For Distributed Java-based Smentioning

confidence: 99%

“…The energy consumed at the interpreter loop stage corresponds to the actual energy required to execute a Java application. The energy consumed by the other stages is constant regardless of the Java classes executed [12,13]. Lafond et al [12,13] have measured the energy consumption of each stage, and showed that the energy required for memory accesses usually accounts for 70% of the total energy consumed at all the stages.…”

Section: An Energy Consumption Framework For Distributed Java-based Smentioning

confidence: 99%

“…The energy consumed by the other stages is constant regardless of the Java classes executed [12,13]. Lafond et al [12,13] have measured the energy consumption of each stage, and showed that the energy required for memory accesses usually accounts for 70% of the total energy consumed at all the stages. Vijay et al [25] have also discussed the characteristics of the energy consumption by cache and main memory at the interpreter loop stage.…”

Section: An Energy Consumption Framework For Distributed Java-based Smentioning

confidence: 99%

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An energy consumption framework for distributed java-based systems

Seo

Malek

Medvidović

2007

Proceedings of the Twenty-Second IEEE/ACM International Conference on Automated Software Engineering

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In this paper we define and evaluate a framework for estimating the energy consumption of Java-based software systems. Our primary objective in devising the framework is to enable an engineer to make informed decisions when adapting a system's architecture, such that the energy consumption on hardware devices with a finite battery life is reduced, and the lifetime of the system's key software services increases. Our framework explicitly takes a componentbased perspective, which renders it well suited for a large class of today's distributed, dynamic, and mobile applications. The framework allows the engineer to estimate the software system's energy consumption at construction time and refine it at runtime. In a large number of distributed application scenarios, the framework showed very good precision on the whole, giving results that were within 5% (and often less) of the actually measured power losses incurred by executing the software. While our empirical evidence suggests that the framework is broadly applicable as-is, our work to date has highlighted a number of future enhancements.

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Section: An Energy Consumption Framework For Distributed Java-based Smentioning

confidence: 99%

Section: An Energy Consumption Framework For Distributed Java-based Smentioning

confidence: 99%

Section: An Energy Consumption Framework For Distributed Java-based Smentioning

confidence: 99%

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An energy consumption framework for distributed java-based systems

Seo

Malek

Medvidović

2007

Proceedings of the Twenty-Second IEEE/ACM International Conference on Automated Software Engineering

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“…Energy (in µJ) is deduced from a per-bytecode energy consumption model [11], i.e., a table containing for each bytecode a corresponding energy cost (aggregating CPU instructions and memory energy costs). An array of 256 floats contains the per-bytecode energy consumption which is multiplied with the internal CPU counter array to get an estimation of the action Energy consumption.…”

Section: A Profilermentioning

confidence: 99%

“…The modifications in the VM, for adding low-level counters and implementing the energy consumption model [11], i.e., the Profiler, accounts for 2 kilobytes whereas the rest of the addition implementing the Predictor represent 14 kilobytes of Java classes.…”

Section: Memory Footprint Cost Of the Weight-watchermentioning

confidence: 99%

The Weight-Watcher Service and its Lightweight Implementation

Garbinato

Guerraoui

Hulaas

et al. 2007

2007 International Conference on Embedded Computer Systems: Architectures, Modeling and Simulation

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Abstract-This paper presents the Weight-Watcher service. This service aims at providing resource consumption measurements and estimations for software executing on resourceconstrained devices. By using the Weight-Watcher, software components can continuously adapt and optimize their quality of service with respect to resource availability. The interface of the service is composed of a Profiler and a Predictor. We present an implementation that is lightweight in terms of CPU and memory. We also performed various experiments that convey (a) the tradeoff between the memory consumption of the service and the accuracy of the prediction, as well as (b) a maximum overhead of 10% on the execution speed of the VM for the Profiler to provide accurate measurements.

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Adaptive Software

Ferreira¹,

Carro²

2012

Adaptable Embedded Systems

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An Energy Consumption Model for an Embedded Java Virtual Machine

Cited by 17 publications

References 4 publications

An energy consumption framework for distributed java-based systems

An energy consumption framework for distributed java-based systems

The Weight-Watcher Service and its Lightweight Implementation

Adaptive Software

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