基于ANT群体优化的磁盘调度算法
A Disk Scheduling Algorithm Based on ANT Colony Optimization
摘要：
音频、动画和视频属于被称为延迟敏感的一类数据，因为它们对呈现给用户的延迟敏感。此外，由于这些项目中的数据量很大，磁盘是管理它们的重要设备。为了有一个可接受的演示，磁盘请求的最后期限必须满足，并应使用实时调度方法来保证这种环境的时间要求。然而，一些磁盘调度算法已被提出，以优化调度实时磁盘请求，但改善的结果是一个挑战。本文提出了一种基于蚁群算法的磁盘调度方法。在这种方法中，ACO模型的任务，并找到最佳的序列，以尽量减少错过的任务的数量和最大的吞吐量。实验结果表明，该方法在大多数情况下，在未命中率和吞吐量方面优于其他相关方法。
英文摘要：
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.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
