• 中国精品科技期刊
  • CCF推荐A类中文期刊
  • 计算领域高质量科技期刊T1类
Advanced Search
Wang Baojin, Li Mingshu, Wang Zhigang. The Priority Mapping Problem in Static Real-Time Middleware[J]. Journal of Computer Research and Development, 2006, 43(4): 722-728.
Citation: Wang Baojin, Li Mingshu, Wang Zhigang. The Priority Mapping Problem in Static Real-Time Middleware[J]. Journal of Computer Research and Development, 2006, 43(4): 722-728.

The Priority Mapping Problem in Static Real-Time Middleware

More Information
  • Published Date: April 14, 2006
  • The deadline monotonic (DM) priority assignment scheme and distributed priority ceiling resource access protocol (DPCP) work well with real-time CORBA. In practice, a potentially large number of global unique priorities must be mapped to the restricted number of local priorities provided by the operating systems. Most operating systems use first-in-first-out (FIFO) scheduling within the same priority. So, a high global priority task could be blocked by lower global priority tasks ahead of it in the local priority FIFO queue. This causes priority inversion and affects the schedulability of tasks with higher global priority. In addition, the optimal priority assignment requires a search of exponential complexity. This is the priority mapping problem. To solve it, necessary and sufficient conditions are presented for analyzing the schedulability of a task which global priority has been mapped to a local priority. The decreasing global priority mapping (DGPM) algorithm is also provided. It can schedule a task and global critical section (GCS) set that is schedulable under any other direct priority mapping algorithms. DGPM can overlap tasks (map two or more tasks to the same local priority) while not allowing the system to become non-schedulable, or prove that the system is no-schedulable after overlapping. The conditions and algorithm are used in the projects.
  • Related Articles

    [1]Wu Jianhui, Zhang Jing, Li Renfa, Liu Zhaohua. A Multi-Subpopulation PSO Immune Algorithm and Its Application on Function Optimization[J]. Journal of Computer Research and Development, 2012, 49(9): 1883-1898.
    [2]Wang Bin. A Discrete Particle Swarm Optimization-based Algorithm for Polygonal Approximation of Digital Curves[J]. Journal of Computer Research and Development, 2010, 47(11): 1886-1892.
    [3]Jie Jing, Zeng Jianchao, Han Chongzhao. Self-Organized Particle Swarm Optimization Based on Feedback Control of Diversity[J]. Journal of Computer Research and Development, 2008, 45(3): 464-471.
    [4]Hu Jianxiu and Zeng Jianchao. A Two-Order Particle Swarm Optimization Model[J]. Journal of Computer Research and Development, 2007, 44(11): 1825-1831.
    [5]Ma Ming, Zhou Chunguang, Zhang Libiao, Ma Jie. Fuzzy Neural Network Optimization by a Multi-Objective Particle Swarm Optimization Algorithm[J]. Journal of Computer Research and Development, 2006, 43(12): 2104-2109.
    [6]Cui Zhihua and Zeng Jianchao. Modified Particle Swarm Optimization Based on Differential Model[J]. Journal of Computer Research and Development, 2006, 43(4): 646-653.
    [7]Zeng Jianchao and Cui Zhihua. A New Unified Model of Particle Swarm Optimization and Its Theoretical Analysis[J]. Journal of Computer Research and Development, 2006, 43(1): 96-100.
    [8]Dou Quansheng, Zhou Chunguang, Xu Zhongyu, Pan Guanyu. Swarm-Core Evolutionary Particle Swarm Optimization in Dynamic Optimization Environments[J]. Journal of Computer Research and Development, 2006, 43(1): 89-95.
    [9]Liu Anfeng, Chen Zhigang, Long Guoping, and Zeng Zhiwen. A Resource Optimizing Scheduling Algorithm of Differentiated Service of Double Minimum Balance in Web Clusters[J]. Journal of Computer Research and Development, 2005, 42(11): 1969-1976.
    [10]Chen Hongzhou, Gu Guochang, and Kang Wangxing. A Sentient Particle Swarm Optimization[J]. Journal of Computer Research and Development, 2005, 42(8): 1299-1305.

Catalog

    Article views (621) PDF downloads (392) Cited by()

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return