Based on Lund and Shanklin’s work (1972), methods of calculating Probability of Cloud-Free Lines-of-Sight (PCFLOS), Persistence Probability of Cloud-Free Lines-of-Sight (PPCFLOS) and Recurrence Probability of Cloud-f...Based on Lund and Shanklin’s work (1972), methods of calculating Probability of Cloud-Free Lines-of-Sight (PCFLOS), Persistence Probability of Cloud-Free Lines-of-Sight (PPCFLOS) and Recurrence Probability of Cloud-free Lines-of-Sight (RPCFLOS) at given heights are presented. PCFLOS, PPCFLOS and RPCFLOS are calculated in Foshan, China by conventional observation data from 1961 to 1990. The conclusions are: (1) The higher the elevations, the smaller the PCFLOS and the larger the view angles, the larger the PCFLOS. (2) PPCFLOS and RPCFLOS decrease with the increase of elevation and the delay of time. (3) RPCFLOS is always equal to or larger than PPCFLOS at lag times.展开更多
Reconfigurable computing systems can be reconfigured at runtime and support partial reconfigurability which makes us able to execute tasks in a true multitasking manner. To manage such systems at runtime, a reconfigur...Reconfigurable computing systems can be reconfigured at runtime and support partial reconfigurability which makes us able to execute tasks in a true multitasking manner. To manage such systems at runtime, a reconfigurable operating system is needed. The main part of this operating system is resource management unit which performs on-line scheduling and placement of hardware tasks at runtime. Reconfiguration overhead is an important obstacle that limits the performance of on-line scheduling algorithms in reconfigurable computing systems and increases the overall execution time. Configuration reusing （task reusing） can decrease reconfiguration overhead considerably, particularly in periodic applications or the applications in which the probability of tasks recurrence is high. In this paper, we present a technique called reusing-based scheduling （RBS）, for on-line scheduling and placement in which configuration reusing is considered as a main characteristic in order to reduce reconfiguration overhead and decrease total execution time of the tasks. Several experiments have been conducted on the proposed algorithm. Obtained results show considerable improvement in overall execution time of the tasks.展开更多
文摘Based on Lund and Shanklin’s work (1972), methods of calculating Probability of Cloud-Free Lines-of-Sight (PCFLOS), Persistence Probability of Cloud-Free Lines-of-Sight (PPCFLOS) and Recurrence Probability of Cloud-free Lines-of-Sight (RPCFLOS) at given heights are presented. PCFLOS, PPCFLOS and RPCFLOS are calculated in Foshan, China by conventional observation data from 1961 to 1990. The conclusions are: (1) The higher the elevations, the smaller the PCFLOS and the larger the view angles, the larger the PCFLOS. (2) PPCFLOS and RPCFLOS decrease with the increase of elevation and the delay of time. (3) RPCFLOS is always equal to or larger than PPCFLOS at lag times.
基金Supported by a grant from Iran Telecommunication Research Center
文摘Reconfigurable computing systems can be reconfigured at runtime and support partial reconfigurability which makes us able to execute tasks in a true multitasking manner. To manage such systems at runtime, a reconfigurable operating system is needed. The main part of this operating system is resource management unit which performs on-line scheduling and placement of hardware tasks at runtime. Reconfiguration overhead is an important obstacle that limits the performance of on-line scheduling algorithms in reconfigurable computing systems and increases the overall execution time. Configuration reusing （task reusing） can decrease reconfiguration overhead considerably, particularly in periodic applications or the applications in which the probability of tasks recurrence is high. In this paper, we present a technique called reusing-based scheduling （RBS）, for on-line scheduling and placement in which configuration reusing is considered as a main characteristic in order to reduce reconfiguration overhead and decrease total execution time of the tasks. Several experiments have been conducted on the proposed algorithm. Obtained results show considerable improvement in overall execution time of the tasks.
