2020/02/26 by Hossein Rahmani, Rahmani, Hossein, Sajjad Arshad +3
Computer Science · #Advanced Data Storage Technologies #Algorithm #Ant colony optimization algorithms #Cloud Computing and Resource Management #Computer science #Distributed #Distributed and Parallel Computing Systems #Distributed computing #FOS: Computer and information sciences #Fair-share scheduling #Mathematical optimization #Operating system #Parallel #Real-time computing #Schedule #Scheduling (production processes) #and Cluster Computing (cs.DC) #cs.DC
paper · pdf · doi:10.48550/arxiv.2003.00926
published in Nihon Shokakibyo Gakkai zasshi = The Japanese journal of gastro-enterology 119(4), 37-42 · ISCA Conference on Parallel and Distributed Computing and Communication Systems (PDCCS) Louisville, KY, USA, September 2009
arxiv created 2020/02/26 · openalex publication_date 2020/02/26 · arxiv updated 2020/03/03 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/05
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.