As a technique to help achieve high performance in parallel and distributed heterogeneous computing systems, task scheduling has attracted considerable interest. In this paper, we propose an effective Cuckoo Search algorithm based on Gaussian random walk and Adaptive discovery probability which combined with a cost-to-time ratio Modification strategy (GACSM), to address task scheduling on heterogeneous multiprocessor systems using Dynamic Voltage and Frequency Scaling (DVFS). First, to overcome the shortcomings of poor performance in exploitation of the cuckoo search algorithm, we use chaos variables to initialize populations to maintain the population diversity, a Gaussian random walk strategy to balance the exploration and exploitation capabilities of the algorithm, and an adaptive discovery probability strategy to improve population diversity. Then, we apply the improved Cuckoo Search (CS) algorithm to assign tasks to resources, and a widely used downward rank heuristic strategy to find the corresponding scheduling sequence. Finally, we apply a cost-to-time ratio improvement strategy to further improve the performance of the improved CS algorithm. Extensive experiments are conducted to evaluate the effectiveness and efficiency of our method. The results validate our approach and show its superiority in comparison with the state-of-the-art methods. INDEX TERMS Task scheduling, DVFS, cuckoo search algorithm, heterogeneous multiprocessor system.
Charged hadron identification in the Compressed Baryonic Matter experiment (CBM) is realized via the Time-of-Flight method [1]. For this purpose the CBM-ToF collaboration designed a Time-of-Flight wall composed of Multi-gap Resistive Plate Chambers (MRPCs). Due to the high interaction rate in CBM of 10 MHz the key challenge is the development of high rate MRPCs above 25 kHz/cm 2 which become possible after the development of low resistive glass with extremely good quality. In this article we present the actual conceptual design of the ToF-wall which is subdivided in three parts namely the outer wall, the inner wall and the forward zone that are discussed in detail. KEYWORDS: Particle identification methods; Detector design and construction technologies and materials; Resistive-plate chambers; Instrumentation and methods for time-of-flight (TOF) spectroscopy
A new approach based on cuckoo search algorithm is presented to solve numerical integration problem. Cuckoo search algorithm is used to optimize the node points on the integral range in order to get a more precise result. This method can not only compute usual definite for any functions, but also calculate singular integral and oscillatory integral. The simulation results show that the cuckoo search algorithm for solving numerical integration has higher precision.
Keywords-Cuckoo search algorithm; definite integral; numerical integration; inequality point segmentation978-1-4799-8730-6/15/$31.00
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