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Breaking the Barrier of 2 for the Storage Allocation Problem

Authors Tobias Mömke , Andreas Wiese

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Author Details

Tobias Mömke
  • Saarland University, Saarland Informatics Campus, Saarbrücken, Germany
Andreas Wiese
  • Department of Industrial Engineering, Universidad de Chile, Santiago, Chile

Funding

  • Mömke, Tobias: This work was partially supported by the ERC Advanced Investigators Grant 695614 (https://powver.org), and by DFG Grant 389792660 as part of TRR 248 (https://perspicuous-computing.science).
  • Wiese, Andreas: Partially supported by FONDECYT Regular grant 1170223.

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Tobias Mömke and Andreas Wiese. Breaking the Barrier of 2 for the Storage Allocation Problem. In 47th International Colloquium on Automata, Languages, and Programming (ICALP 2020). Leibniz International Proceedings in Informatics (LIPIcs), Volume 168, pp. 86:1-86:19, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2020) https://doi.org/10.4230/LIPIcs.ICALP.2020.86

Abstract

Packing problems are an important class of optimization problems. The probably most well-known problem if this type is knapsack and many generalizations of it have been studied in the literature like Two-dimensional Geometric Knapsack (2DKP) and Unsplittable Flow on a Path (UFP). For the latter two problems, recently the first polynomial time approximation algorithms with better approximation ratios than 2 were presented [Gálvez et al., FOCS 2017][Grandoni et al., STOC 2018]. In this paper we break the barrier of 2 for the Storage Allocation Problem (SAP), a problem which combines properties of 2DKP and UFP. In SAP, we are given a path with capacitated edges and a set of tasks where each task has a start vertex, an end vertex, a size, and a profit. We seek to select the most profitable set of tasks that we can draw as non-overlapping rectangles underneath the capacity profile of the edges where the height of each rectangle equals the size of the corresponding task.
The problem SAP appears naturally in settings of allocating resources like memory, bandwidth, etc. where each request needs a contiguous portion of the resource. The best known polynomial time approximation algorithm for SAP has an approximation ratio of 2+ε [Mömke and Wiese, ICALP 2015] and no better quasi-polynomial time algorithm is known. We present a polynomial time (63/32+ε) < 1.969-approximation algorithm for the important case of uniform edge capacities and a quasi-polynomial time (1.997+ε)-approximation algorithm for non-uniform quasi-polynomially bounded edge capacities. Key to our results are building blocks consisting of stair-blocks, jammed tasks, and boxes that we use to construct profitable solutions and which allow us to compute solutions of these types efficiently. Finally, using our techniques we show that under slight resource augmentation we can obtain even approximation ratios of 3/2+ε in polynomial time and 1+ε in quasi-polynomial time, both for arbitrary edge capacities.

Subject Classification

ACM Subject Classification
  • Theory of computation → Dynamic programming
  • Theory of computation → Packing and covering problems
  • Theory of computation → Rounding techniques
Keywords
  • Approximation Algorithms
  • Resource Allocation
  • Dynamic Programming

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