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Online Algorithms for Packet Scheduling
Veselý, Pavel ; Sgall, Jiří (advisor) ; Stein, Clifford (referee) ; Englert, Matthias (referee)
We study online scheduling policies for buffer management models, in which packets are arriving over time to a buffer of a network switch to be sent through its single output port. However, the bandwidth of the port is limited and some packets need to be dropped, based on their weights. The goal of the scheduler is to maximize the weighted throughput, that is, the total weight of packets transmitted. Due to the natural lack of information about future, an optimal performance cannot be achieved, we thus pursue competitive analysis and its refinements to analyze online algorithms on worst-case inputs. Specifically, in the first part of the thesis, we focus on a simple online scheduling model with unit-size packets and deadlines, called Bounded-Delay Packet Scheduling. We design an optimal φ-competitive deterministic algo- rithm for the problem, where φ ≈ 1.618 is the golden ratio. It is based on a detailed understanding of an optimal schedule of pending packets, called the plan, which may be of independent interest. We also propose a semi-online setting with lookahead that allows the algorithm to see a little bit of future, namely, packets arriving in the next few steps. We provide an algorithm with lookahead for instances in which each packet can be scheduled in at most two consecutive slots and prove lower...
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Online Bin Stretching: Algorithms and Computer Lower Bounds
Böhm, Martin ; Sgall, Jiří (advisor) ; Durr, Christoph (referee) ; Kellerer, Hans (referee)
Online Bin Stretching: Algorithms and Computer Lower Bounds Author: Martin Böhm Abstract: We investigate a problem in semi-online algorithm design, called Online Bin Stretching. The problem can be understood as an online repacking problem: the goal of the algorithm is to repack items of various sizes into m containers of identical size R > 1. The input items arrive one by one and the algorithm must assign an item to a container before the next item arrives. A specialty of this problem is that there is a specific guarantee made to the algorithm: the algorithm learns at the start of the input that there exists a packing of all input items into m containers of capacity 1. Our goal is to design algorithms for this problem which successfully pack the entire incoming sequence one by one while requiring the lowest container capacity R possible. In this thesis, we show several new results about Online Bin Stretching: First, we design an algorithm that is able to pack the entire input into m containers of capacity 1.5 regardless of what the vale of m will be. Second, we show a specialized algorithm for the setting of just 3 containers; this algorithm is able to pack into 3 bins of capacity 1.375. Finally, we design and implement an involved search algorithm which is able to find lower bounds for Online Bin...
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Online scheduling of multiprocessor jobs with preemption
Šimsa, Štěpán ; Sgall, Jiří (advisor) ; Kolman, Petr (referee)
Abstract. The thesis is devoted to the problem of online preemptive scheduling of mul- tiprocessor jobs. It gives a summary of previous work on this problem. For some special variants of the problem, especially if we restrict the sizes of jobs to one and two, new results are given, both in the terms of lower bounds and in the terms of competitive al- gorithms. A previously published lower bound is showed to be computed incorrectly and it is replaced by a correct lower bound in this thesis. An algorithm is presented for the special case of four processors and sizes of jobs one and two that is conjectured to achieve the best possible competitive ratio.
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Online algorithms for variants of bin packing
Veselý, Pavel ; Sgall, Jiří (advisor) ; Krčál, Marek (referee)
An online algorithm must make decisions immediately and irrevocably based only on a part of the input without any knowledge of the future part of the input. We introduce the competitive analysis of online algorithms, a standard worst-case analysis, and present main results of this analysis on the problem of online Bin Packing and on some of its variants. In Bin Packing, a sequence of items of size up to 1 arrives to be packed into the minimal number of unit capacity bins. Mainly, we focus on Colored Bin Packing in which items have also a color and we cannot pack two items of the same color adjacently in a bin. For Colored Bin Packing, we improve some previous results on the problem with two colors and present the first results for arbitrarily many colors. Most notably, in the important case when all items have size zero, we give an optimal 1.5-competitive algorithm. For items of arbitrary size we present a lower bound of 2.5 and a 3.5-competitive algorithm. Powered by TCPDF (www.tcpdf.org)
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