Automatic application object migration in sensor networks

Object migration in wireless sensor networks has the potential to reduce energy consumption for a wireless sensor network mesh. Automated migration reduces the need for the programmer to perform manual static analysis to find an efficient layout solution. Instead, the system can self-optimise and adjust to changing conditions. This paper describes an automated, transparent object migration system for wireless sensor networks, implemented on a micro Java virtual machine. The migration system moves objects at runtime around the sensor mesh to reduce communication overheads. The movement of objects is transparent to the application developer. Automated transparent object migration is a core component of Hydra, a distributed operating system for wireless sensor networks that is currently under development. Performance of the system under a complex performance test scenario using a real-world dataset of seismic events is described. The results show that under both simple and complex conditions the migration technique can result in lower data traffic and consequently lower overall energy cost

Using Java for distributed computing in the Gaia satellite data processing

In recent years Java has matured to a stable easy-to-use language with the flexibility of an interpreter (for reflection etc.) but the performance and type checking of a compiled language. When we started using Java for astronomical applications around 1999 they were the first of their kind in astronomy. Now a great deal of astronomy software is written in Java as are many business applications. We discuss the current environment and trends concerning the language and present an actual example of scientific use of Java for high-performance distributed computing: ESA's mission Gaia. The Gaia scanning satellite will perform a galactic census of about 1000 million objects in our galaxy. The Gaia community has chosen to write its processing software in Java. We explore the manifold reasons for choosing Java for this large science collaboration. Gaia processing is numerically complex but highly distributable, some parts being embarrassingly parallel. We describe the Gaia processing architecture and its realisation in Java. We delve into the astrometric solution which is the most advanced and most complex part of the processing. The Gaia simulator is also written in Java and is the most mature code in the system. This has been successfully running since about 2005 on the supercomputer "Marenostrum" in Barcelona. We relate experiences of using Java on a large shared machine. Finally we discuss Java, including some of its problems, for scientific computing.Comment: Experimental Astronomy, August 201

Evaluating the Impact of Java Virtual Machines on Energy Consumption

International audienceBackground. The Java Virtual Machine (JVM) platforms have known multiple evolutions along the last decades to enhance both the performance they exhibit and the features they offer. With regards to energy consumption, few studies have investigated the energy consumption of code and data structures. Yet, we keep missing an evaluation of the energy efficiency of existing JVM platforms and an identification of the configurations that minimize the energy consumption of software hosted on the JVM. Aims. The purpose of this paper is to investigate the variations in energy consumption between different JVM distributions and parameters to help developers configuring the least consuming environment for their Java application. Method. We thus assess the energy consumption of some of the most popular and supported JVM platforms using 12 Java benchmarks that explore different performance objectives. Moreover, we investigate the impact of the different JVM parameters and configurations on the energy consumption of software. Results. Our results show that some JVM platforms can exhibit up to 100% more energy consumption. JVM configurations can also play a substantial role to reduce the energy consumption during the software execution. Interestingly, the default configuration of the garbage collector was energy efficient in only 50% of our experiments. Conclusion. Finally, we provide an OSS tool, named J-Referral that recommends an energy-efficient JVM distribution and configuration for any Java application