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We revisit the online Unit Clustering and Unit Covering problems in higher dimensions: Given a set of n points in a metric space, that arrive one by one, Unit Clustering asks to partition the points into the minimum number of clusters (subsets) of diameter at most one; while Unit Covering asks to cover all points by the minimum number of balls of unit radius. In this paper, we work in ℝ^d using the L_∞ norm. We show that the competitive ratio of any online algorithm (deterministic orarXiv:1708.02662v3 fatcat:ilyrq4fklve23ew2ejfcjg6axy