Algorithms for online data management problems considering the storage capacities. (July 2022)

• Record Type: Journal Article
• Authors: Han, Lu; Jiang, Yanjun; Wu, Chenchen
• Is Part Of: Computers & electrical engineering. Volume 101(2022)
• Publication Date: 2022-07
• Subjects: Data management -- Online facility location -- Capacities -- Competitive ratio -- Dual-fitting; Computer engineering -- Periodicals; Electrical engineering -- Periodicals; Electrical engineering -- Data processing -- Periodicals; Ordinateurs -- Conception et construction -- Périodiques; Électrotechnique -- Périodiques; Électrotechnique -- Informatique -- Périodiques; Computer engineering; Electrical engineering; Electrical engineering -- Data processing; Periodicals; Electronic journals; 621.302854
• DOI: 10.1016/j.compeleceng.2022.107843
• Languages: English
• ISSNs: 0045-7906

Abstract

Abstract: A mind-boggling amount of data will be generated every day. It is natural to consider clustering the data and putting each cluster into some place for storing. In reality, the arrival time of the data is unknown in advance and new data keep joining appropriate cluster upon arrival. This scenario can be captured as the online facility location problem. Usually, the places for storing the data have limited capacities. Therefore, the online capacitated facility location problem (O-CFLP) is proposed. Designing algorithms with bounded competitive ratios for the O-CFLP is impossible. This fact stimulates us to study special cases of the O-CFLP. We pay attention on the online soft capacitated facility location problem and its prize-collecting version, and we design dual-fitting competitive algorithms for them. Graphical abstract: Highlights: Propose the online soft capacitated facility location problem (O-SCFLP). Design a dual-fitting competitive algorithm for the O-SCFLP. Extend the algorithm for the O-SCFLP to its prize-collecting version.