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Algorithms for online data management problems considering the storage capacities
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AI
DOI：10.1016/j.compeleceng.2022.107843.png)
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Abstract
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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.
Keywords:
Data management
Online facility location
Capacities
Competitive ratio
Dual-fitting
Journal
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