Space-Constrained Interval Selection

We study streaming algorithms for the interval selection problem: finding a maximum cardinality subset of disjoint intervals on the line. A deterministic 2-approximation streaming algorithm for this problem is developed, together with an algorithm for the special case of proper intervals, achieving improved approximation ratio of 3/2. We complement these upper bounds by proving that they are essentially the best possible in the streaming setting: It is shown that an approximation ratio of 2 − ε (or 3/2 − ε for proper intervals) cannot be achieved unless the space is linear in the input size. In passing, we also answer an open question of Adler and Azar (J. Scheduling 2003) regarding the space complexity of constant-competitive randomized preemptive online algorithms for the same problem.

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