Multiobjective Optimization Approach for a Portable Development of Reconfigurable Real-Time Systems: From Specification to Implementation
提出一种多目标优化方法MO2R2S，用于开发可重构实时系统，在满足实时约束下优化响应时间、内存分配和能耗，并通过实验验证了显著效果。
This paper deals with the reconfigurable real-time systems that should be adapted to their environment under real-time constraints. The reconfiguration allows moving from one implementation to another by adding/removing/modifying parameters of real-time software tasks which should meet related deadlines. Implementing those systems as threads generates a complex system code due to the large number of threads, which may lead to a reconfiguration time overhead as well as the energy consumption and the memory allocation increase. Thus this paper proposes a multiobjective optimization approach for reconfigurable systems called MO <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> R <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> S for the development of a reconfigurable real-time system. Given a specification, the proposed approach aims to produce an optimal design while ensuring the system feasibility. We focus on three optimization criteria: 1) response time; 2) memory allocation; and 3) energy consumption. To address the portability issue, the optimal design is then transformed to an abstract code that may in turn be transformed to a concrete code which is specific to a procedural programming (i.e., POSIX) or an object-oriented language (i.e., RT-Java). The MO <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> R <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> S approach allows reducing the number of threads by minimizing the redundancy between the implementation sets. By an experimental study, such optimization permits to decrease the memory allocation by 28.89%, the energy consumption by 40.2%, and the response time by 61.32%.