Studying energy trade offs in offloading computation/compilation in Java-enabled mobile devices

Guangyu Chen, Byung Tae Kang, Mahmut Kandemir, Narayanan Vijaykrishnan, Mary Jane Irwin, Rajarathnam Chandramouli

Research output: Contribution to journalArticlepeer-review

107 Scopus citations


Java-enabled wireless devices are preferred for various reasons. For example, users can dynamically download Java applications on demand. The dynamic download capability supports extensibility of the mobile client features and centralizes application maintenance at the server. Also, it enables service providers to customize features for the clients. In this work, we extend this client-server collaboration further by offloading some of the computations (i.e., method execution and dynamic compilation) normally performed by the mobile client to the resource-rich server in order to conserve energy consumed by the client in a wireless Java environment. In the proposed framework, the object serialization feature of Java is used to allow offloading of both method execution and bytecode-to-native code compilation to the server when executing a Java application. Our framework takes into account communication, computation, and compilation energies to decide where to compile and execute a method (locally or remotely), and how to execute it (using interpretation or just-in-time compilation with different levels of optimizations). As both computation and communication energies vary based on external conditions (such as the wireless channel state and user supplied inputs), our decision must be done dynamically when a method is invoked. Our experiments, using a set of Java applications executed on a simulation framework, reveal that the proposed techniques are very effective in conserving the energy of the mobile client.

Original languageEnglish (US)
Pages (from-to)795-809
Number of pages15
JournalIEEE Transactions on Parallel and Distributed Systems
Issue number9
StatePublished - Sep 2004

All Science Journal Classification (ASJC) codes

  • Signal Processing
  • Hardware and Architecture
  • Computational Theory and Mathematics


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