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On Cloud Assisted, Restricted, and Resource Constrained Scheduling / submitted by Simon Pukrop ; [Reviewers Prof. Dr. Friedhelm Meyer auf der Heide; Paderborn University, Prof. Dr. Klaus Jansen; Kiel University]. Paderborn, 2023
Inhalt
1 Introduction
1.1 What is Scheduling, and Why Bother?
1.2 On Problems, Languages, and Efficient Encodings
1.3 P vs. NP and NP-Hardness
1.4 Approximation Algorithms and Schemes
1.5 Formal Scheduling Notation
1.6 Contents of this Thesis
2 Server Cloud Scheduling
2.1 Introduction
2.1.1 Problem Definition
2.1.2 Our Results
2.1.3 Related Work
2.2 Chains and Fully Parallel Task Graphs
2.2.1 Hardness
2.2.2 Algorithms
2.3 The Extended Chain Model (SCS e)
2.3.1 A Preliminary Problem: Single Machine Weighted Number of Tardy Jobs
2.3.2 Strong NP-Hardness of Scheduling Extended Chains
2.3.3 A (2+)-approximation (Makespan) on the Extended Chain
2.3.4 Cases with FPTAS
2.4 Constant Cardinality Source and Sink Dividing Cut (SCS )
2.4.1 Dynamic Programming for SCS
2.4.2 Scaling and Rounding the Dynamic Program
2.5 Strong NP-Hardness
2.5.1 No Delays and Two Sizes
2.5.2 Unit Size and Unit Delay (SCS 1)
2.5.3 Inapproximability of the General Case
2.6 Algorithms for SCS 1 and Instances Without Delays
2.6.1 A 3-Approximation (Makespan) for SCS 1
2.6.2 A 1+2-Approximation (Cost) for SCS 1 with Resource Augmentation
2.6.3 A 2-Approximation (Makespan) on Identical Machines and no Delays
2.7 Generalizations of Server Cloud Scheduling
2.7.1 Changes in the Definitions
2.7.2 Revisiting SCS e
2.7.3 Revisiting SCS
2.8 Approximating the Pareto Front
2.9 Future Work
3 Restricted Assignment Interval
3.1 Introduction
3.1.1 Problem Definition
3.1.2 Relation Between the Models and the State of the Art
3.1.3 Our Results
3.1.4 Further Related Work
3.2 A (2-124)-Approximation
3.2.1 Preliminaries.
3.2.2 Linear Program.
3.2.3 Integrality Gap of the Linear Program
3.2.4 The Rounding Algorithm.
3.3 A Summary of Our Complexity Results
3.3.1 Three Resources
3.3.2 Two Resources
3.3.3 Interval Restrictions
3.4 Future Work
4 Many Shared Resources
4.1 Introduction
4.1.1 Problem Definition
4.1.2 State of the Art and Motivation
4.1.3 Our Results
4.1.4 Further Related Work
4.1.5 Preliminaries
4.2 A 5/3-approximation
4.3 A 3/2-approximation
4.3.1 Algorithm for Instances without Huge Jobs
4.3.2 Algorithm for the General Case
4.4 A Summary of Our Work on Approximation Schemes
4.5 Inapproximability Results
4.6 Future Work
Bibliography
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