Bipartite matching markets pair agents on one side of a market with agents, items, or contracts on the opposing side. Prior work addresses online bipartite matching markets, where agents arrive over time and are dynamically matched to a known set of disposable resources. In this paper, we propose a new model, Online Matching with (offline) Reusable Resources under Known Adversarial Distributions
(OMRRKAD), in which resources on the offline side are reusable instead of disposable; that is, once matched, resources become available again at some point in the future. We show that our model is tractable by presenting an LPbased adaptive algorithm that achieves an online competitive ratio of 1/2  epsilon for any given epsilon > 0. We also show that no nonadaptive algorithm can achieve a ratio of 1/2 + o(1) based on the same benchmark LP. Through a datadriven analysis on a massive openlyavailable dataset, we show our model is robust enough to capture the application of taxi dispatching services and ridesharing systems. We also present heuristics that perform well in practice.
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Online and Offline Algorithms for Circuit Switch Scheduling
Motivated by the use of high speed circuit switches in large scale data centers, we consider the problem of circuit switch scheduling. In this problem we are given demands between pairs of servers and the goal is to schedule at every time step a matching between the servers while maximizing the total satisfied demand over time. The crux of this scheduling problem is that once one shifts from one matching to a different one a fixed delay delta is incurred during which no data can be transmitted. For the offline version of the problem we present a (1(1/e)epsilon) approximation ratio (for any constant epsilon >0). Since the natural linear programming relaxation for the problem has an unbounded integrality gap, we adopt a hybrid approach that combines the combinatorial greedy with randomized rounding of a different suitable linear program. For the online version of the problem we present a (bicriteria) ((e1)/(2e1)epsilon)competitive ratio (for any constant epsilon >0 ) that exceeds time by an additive factor of O(delta/epsilon). We note that no unicriteria online algorithm is possible. Surprisingly, we obtain the result by reducing the online version to the offline one.
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 Award ID(s):
 1717947
 NSFPAR ID:
 10178887
 Date Published:
 Journal Name:
 Leibniz international proceedings in informatics
 Volume:
 150
 ISSN:
 18688969
 Page Range / eLocation ID:
 27:127:14
 Format(s):
 Medium: X
 Sponsoring Org:
 National Science Foundation
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