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Seminarium ZOK: Jarosław Byrka o Online Algorithms for Multi-Level Aggregation  

W dniu 13 października 2015 (wtorek, godz. 10:15-12:00, sala 310) na seminarium Zakładu Optymalizacji Kombinatorycznej Jarosław Byrka przedstawi wyniki na temat Online Algorithms for Multi-Level Aggregation.

Streszczenie

In the Multi-Level Aggregation Problem (MLAP), requests arrive at the nodes of an edge-weighted tree T . A service is defined as a subtree X of T that contains its root. This subtree X services all requests that are pending in the nodes of X, and the cost of this service is equal to the total weight of X. Each request also incurs waiting cost between its arrival and service times. The objective is to minimize the total waiting cost of all requests plus the cost of all service sub-trees. MLAP is a generalization of some well-studied optimization problems; for example, for trees of depth 1, MLAP is equivalent to the TCP Acknowledgement Problem, while for trees of depth 2, it is equivalent to the Joint Replenishment Problem. In earlier literature, the waiting cost functions are often assumed to be linear; we denote this special case by MLAP-L. The model with deadlines, denoted MLAP-D, has also been studied.

Our main result is an online algorithm with competitive ratio O(D^4 2^D), where D is the depth of T. This is the first non-trivial competitiveness bound on trees of depth three or more, not only for MLAP but also for MLAP-D and MLAP-L. Previously constant-competitive algorithms were known only for D = 1, 2. We then consider the restricted case of MLAP when the tree is a path, for which we give a lower bound of 4 on the competitive ratio, that applies even to MLAP-D and MLAP-L. For MLAP-D, we give a matching upper bound. In addition, we study the Single-Phase MLAP, a variant of MLAP in which all requests are revealed at time 0 and they expire at some time, not known to the online algorithm. The Single-Phase MLAP is a crucial tool in lower-bound proofs for MLAP. For the Single-Phase MLAP we give an online algorithm with optimal competitive ratio 4.

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