论文标题
基于蚂蚁菌落优化的磁盘调度算法
A Disk Scheduling Algorithm Based on ANT Colony Optimization
论文作者
论文摘要
音频，动画和视频属于称为延迟敏感的一类数据，因为它们对向用户的延迟敏感。另外，由于此类项目中的大量数据，磁盘是管理它们的重要设备。为了进行可接受的演示，必须满足磁盘请求的截止日期，并且应使用实时调度方法来保证对这种环境的时机要求。但是，自从现在以来，已经提出了一些磁盘调度算法来优化调度实时磁盘请求，但是改进结果是一个挑战。在本文中，我们提出了一种基于蚂蚁菌落优化（ACO）方法的新磁盘调度方法。在这种方法中，ACO对任务进行建模，并找到最佳的序列，以最大程度地减少错过的任务数量并最大化吞吐量。实验结果表明，在大多数情况下，该方法的效果很好，并且在遗漏比和吞吐量方面对其他相关的方法都表现出色。
Audio, animations and video belong to a class of data known as delay sensitive because they are sensitive to delays in presentation to the users. Also, because of huge data in such items, disk is an important device in managing them. In order to have an acceptable presentation, disk requests deadlines must be met, and a real-time scheduling approach should be used to guarantee the timing requirements for such environment. However, some disk scheduling algorithms have been proposed since now to optimize scheduling real-time disk requests, but improving the results is a challenge yet. In this paper, we propose a new disk scheduling method based on Ant Colony Optimization (ACO) approach. In this approach, ACO models the tasks and finds the best sequence to minimize number of missed tasks and maximize throughput. Experimental results showed that the proposed method worked very well and excelled other related ones in terms of miss ratio and throughput in most cases.
