An energy consumption framework for distributed java-based systems

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 component-based perspective, which renders it well suited for a large class of today's distributed, embedded, and pervasive applications. The framework allows the engineer to estimate the software system's energy consumption at system 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. Our work to date has also highlighted a number of possible enhancements

[1]  Amin Vahdat,et al.  ECOSystem: managing energy as a first class operating system resource , 2002, ASPLOS X.

[2]  Sarfraz Khurshid,et al.  Generalized Symbolic Execution for Model Checking and Testing , 2003, TACAS.

[3]  Sébastien Lafond,et al.  An Energy Consumption Model for an Embedded Java Virtual Machine , 2006, ARCS.

[4]  Martin Nilsson,et al.  Investigating the energy consumption of a wireless network interface in an ad hoc networking environment , 2001, Proceedings IEEE INFOCOM 2001. Conference on Computer Communications. Twentieth Annual Joint Conference of the IEEE Computer and Communications Society (Cat. No.01CH37213).

[5]  Jean J. Labrosse,et al.  MicroC/OS-II: The Real Time Kernel , 1998 .

[6]  Mahmut T. Kandemir,et al.  Energy Behavior of Java Applications from the Memory Perspective , 2001, Java Virtual Machine Research and Technology Symposium.

[7]  S. Malek,et al.  An Energy Consumption Framework for Distributed Java-Based Software , 2022 .

[8]  Cheng Wang,et al.  Impact of data compression on energy consumption of wireless-networked handheld devices , 2003, 23rd International Conference on Distributed Computing Systems, 2003. Proceedings..

[9]  Sharad Malik,et al.  Power analysis of embedded software: a first step towards software power minimization , 1994, IEEE Trans. Very Large Scale Integr. Syst..

[10]  Anantha Chandrakasan,et al.  JouleTrack: a web based tool for software energy profiling , 2001, DAC '01.

[11]  Jason Flinn,et al.  Quantifying the energy consumption of a pocket computer and a Java virtual machine , 2000, SIGMETRICS '00.

[12]  Niraj K. Jha,et al.  Energy macromodeling of embedded operating systems , 2005, TECS.

[13]  Ilja Radusch,et al.  pREST: a REST-based protocol for pervasive systems , 2004, 2004 IEEE International Conference on Mobile Ad-hoc and Sensor Systems (IEEE Cat. No.04EX975).

[14]  James C. King,et al.  Symbolic execution and program testing , 1976, CACM.

[15]  Mike Tien-Chien Lee,et al.  Power analysis of a 32-bit embedded microcontroller , 1995, Proceedings of ASP-DAC'95/CHDL'95/VLSI'95 with EDA Technofair.

[16]  Suresh Singh,et al.  Energy Consumption of TCP in Ad Hoc Networks , 2004, Wirel. Networks.