摘要
传统的大数据并行调度算法调度的船舶数量很少,调度的精确度很差。为解决此问题,基于云计算研究了一种新的船舶大数据并行调度算法,构建了算法的计算框架,计算框架包括基础设施服务、软件服务以及平台服务3部分,探讨了调度过程,通过计算二维网络中各船舶的横纵坐标完成调度。与传统算法进行了实验对比,由实验结果可知,基于云计算的船舶大数据并行调度算法能够同时对多个船舶实施调度,调度的精确度很高。该算法具有广阔的市场发展空间,值得大力推广使用。
The traditional big data parallel scheduling algorithm has a small number of ships scheduling, and the accuracy of scheduling is very poor. In order to solve this problem, a new ship large data parallel scheduling algorithm is studied based on cloud computing, and the calculation framework of the algorithm is constructed. The calculation framework includes three parts: infrastructure services, software services and platform services. The scheduling process is discussed, and the scheduling is completed by calculating the transverse ordinates of each ship in a two-dimensional network. Compared with the traditional algorithm, the experimental results show that the ship large data parallel scheduling algorithm based on cloud computing can schedule multiple ships at the same time, and the accuracy of the scheduling is very high. The algorithm has broad market development space and is worth promoting.
出处
《舰船科学技术》
北大核心
2018年第10X期142-144,共3页
Ship Science and Technology
关键词
云计算
船舶大数据
大数据调度
并行调度
调度算法
cloud computing
large large ship data
big data scheduling
parallel scheduling
scheduling algorithm
