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This paper investigates sequencing policies for file reading requests inlinear storage devices, such as magnetic tapes. Tapes are the technology ofchoice for long-term storage in data centers due to their low cost andreliability. However, their physical structure imposes challenges to dataretrieval operations reflected in classic optimization and operations researchproblems. In this work, we provide a theoretical and numerical performanceanalysis of low-complexity algorithms under deterministic, stochastic, andonline settings, which are key in practice due to their interpretability andthe large scale of existing data services. In the deterministic setting, weshow that traditional policies, such as first-in first-out (FIFO), havearbitrarily poor performance, and we develop and investigate newconstant-factor approximations. For the stochastic setting, we present a fullypolynomial-time approximation scheme that weighs files based on their accessfrequencies. Finally, we investigate an online extension and propose a newalgorithm with constant competitive-factor guarantees. Our numerical analysison synthetic and real-world data suggest that the proposed algorithms maysignificantly outperform policies currently adopted in practice with respect toaverage reading times.

On Approximate Sequencing Policies for Linear Storage Devices