Optimized Aspect Execution Mechanisms inside Virtual Machines for Embedded Systems

Abstract

The rapidly growing mobile market has stimulated the demand for more and more complex custom applications for embedded mobile devices, for example, smart phones. To manage this complexity and, at the same time, to keep the time to market small, advanced software engineering methods have to be applied. Aspect-oriented programming (AOP) provides advanced modularization and abstraction mechanisms. The main advantages of this concept are improved maintainability, reusability, and extensibility of applications. Furthermore, dynamic AOP can be used to implement the dynamic adaptation of mobile device applications to changing contexts, like the location. However, the overhead introduced by the additional abstraction mechanisms limits the applicability to embedded mobile devices because they have limited resources (CPU, memory) compared to desktop PCs. To overcome this problem, we present a set of optimizations that significantly reduce the overhead of common AOP mechanisms and, finally, make AOP applicable for embedded mobile devices. The foundation of our work is a thorough analysis of the overhead that is typically generated by the realization of AOP mechanisms. The key idea of our approach is a deep integration of AOP mechanisms into the virtual machine. To this end, we shift mechanisms like the registration of activated aspects to the level of the JVM. Furthermore, we optimize the execution of AOP programs by introducing caching mechanisms and specialized bytecode instructions that are tailored for the execution of AOP mechanisms. Moreover, we analyze AOP-specific semantic code properties in order to develop optimizations that utilize these AOP-specific semantic information and that exploit typical AOP usage schemes. In addition to the AOP optimizations, we realize an efficient dynamic aspect deployment mechanism. We apply our optimizations to the Java-based aspect-oriented programming language ObjectTeams [HHM07] by extending the extremely small and portable JamVM [Lou] Java virtual machine. To evaluate our approach, we execute micro benchmarks, investigate the effect of our optimizations on a real-world application, and finally discuss the transferability of our optimizations to other approaches. Our evaluation shows a considerable performance gain for the aspect activation and the aspect execution of ObjectTeams. In particular, we demonstrate that our optimizations improve the performance of commonly used AOP mechanisms by up to 90%. At the same time, we reduce the code size of the adapted classes, which is also important for small devices. Finally, with our case study, namely the OTPong game application, we show that our approach is capable of significantly optimizing the execution time of real-word applications. Our main contribution is a significant reduction of the overhead of high-level AOP constructs, which is also demonstrated by the results of our experiments. The success of the optimizations provides evidence that advanced high-level abstraction techniques like AOP can be efficiently used in embedded mobile devices. Furthermore, our work shows that efficient dynamic aspect deployment can be supported on the level of the JVM. This substantially enhances the dynamic capabilities of ObjectTeams.