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Linear Programming Based Resource Management for Heterogeneous Computing SystemsAl-Azzoni, Issam 05 1900 (has links)
An emerging trend in computing is to use distributed heterogeneous computing (HC) systems to execute a set of tasks. Cluster computer systems, grids, and Desktop Grids are three popular kinds of HC systems. An important component of an HC system is its resource management system (RMS). The main responsibility of an RMS is assigning resources to tasks in order to satisfy certain performance requirements. For cluster computer systems, we propose a new mapping heuristic which requires less state information than current heuristics. For Desktop Grids, we propose a new scheduling policy that exploits knowledge of the effective computing power delivered by the machines and the distribution of their fault times in order to improve performance. Finally, for grids, we propose a new decentralized load balancing policy which dramatically cuts down the communication overhead incurred in state information update. The proposed resource management policies utilize the solution to a linear programming problem (LP) which maximizes the system capacity. Our simulation experiments show that these policies perform very competitively, especially in highly
heterogeneous systems. / Thesis / Doctor of Philosophy (PhD)
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Linearization-Based Strategies for Optimal Scheduling of a Hydroelectric Power Plant Under Uncertainty / Linearization-Based Scheduling of Hydropower SystemsTikk, Alexander January 2019 (has links)
This thesis examines the optimal scheduling of a hydroelectric power plant with cascaded reservoirs each with multiple generating units under uncertainty after testing three linearization methods. These linearization methods are Successive Linear Programming, Piecewise Linear Approximations, and a Hybrid of the two together. There are two goals of this work. The first goal of this work aims to replace the nonconvex mixed-integer nonlinear program (MINLP) with a computationally efficient linearized mixed-integer linear program (MILP) that will be capable of finding a high quality solution, preferably the global optimum. The second goal is to implement a stochastic approach on the linearized method in a pseudo-rolling horizon method which keeps the ending time step fixed. Overall, the Hybrid method proved to be a viable replacement and performs well in the pseudo-rolling horizon tests. / Thesis / Master of Applied Science (MASc)
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