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A branch-and-cut approach to examining the maximum density guarantee for pinwheel schedulability of low-dimensional vectors

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Abstract

Given an n-dimensional integer vector \(\mathbf {v} = (v_1, v_2, \ldots , v_n)\) with \(v_1 \le v_2 \le \cdots \le v_n\), a pinwheel schedule for \(\mathbf {v}\) is an infinite symbol sequence \(S_1 S_2 S_3 \cdots\), which satisfies that \(S_j \in \{ 1, 2, \ldots , n \}, \forall j \in \mathbb {Z}^{+}\) and every \(i \in \{ 1, 2, \ldots , n \}\) occurs at least once in every \(v_i\) consecutive symbols \(S_{j + 1} S_{j + 2} \cdots S_{j + v_i}, \forall j \in \mathbb {Z}^{+} \cup \{ 0 \}\). If \(\mathbf {v}\) has a pinwheel schedule then \(\mathbf {v}\) is called (pinwheel) schedulable. The density of \(\mathbf {v}\) is defined as \(d(\mathbf {v}) = \sum _{i = 1}^{n} \frac{1}{v_i}\). Chan and Chin (Algorithmica 9(5):425–462, 1993) made a conjecture that every vector \(\mathbf {v}\) with \(d(\mathbf {v}) \le \frac{5}{6}\) is schedulable. In this paper, we check the conjecture from the perspective of low-dimensional vectors, including 3-, 4- and 5-dimensional ones. We first find some simple but important properties of schedulable vectors, and then propose two comparing rules according to these properties. Also, we define a vector-space tree to represent all k-dimensional vectors, for any given integer \(k \ge 2\). Under the framework of the vector-space tree, we use the comparing rules to develop a Branch-and-Cut Approach to examining the schedulability of all k-dimensional vectors. As a result, we prove that the maximum density guarantee for the pinwheel schedulability of low-dimensional vectors is \(\frac{5}{6}\), which partially supports Chan and Chin’s conjecture.

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Correspondence to Wei Ding.

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A preliminary version of this paper appeared in the Proceedings of the 13th International Conference on Algorithmic Aspects of Information and Management (AAIM’19) Ding (2019).

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Ding, W. A branch-and-cut approach to examining the maximum density guarantee for pinwheel schedulability of low-dimensional vectors. Real-Time Syst 56, 293–314 (2020). https://doi.org/10.1007/s11241-020-09349-w

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