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Full-Text Articles in Computer Engineering
Multi-Population-Based Differential Evolution Algorithm For Optimization Problems, Ishani Chatterjee
Multi-Population-Based Differential Evolution Algorithm For Optimization Problems, Ishani Chatterjee
Theses
A differential evolution (DE) algorithm is an evolutionary algorithm for optimization problems over a continuous domain. To solve high dimensional global optimization problems, this work investigates the performance of differential evolution algorithms under a multi-population strategy. The original DE algorithm generates an initial set of suitable solutions. The multi-population strategy divides the set into several subsets. These subsets evolve independently and connect with each other according to the DE algorithm. This helps in preserving the diversity of the initial set. Furthermore, a comparison of combination of different mutation techniques on several optimization algorithms is studied to verify their performance. Finally, …
Preemptive Efficient Queueing For Scheduling Deadline-Bound Data Center Flows, Vinaykrishna Gopalakrishna
Preemptive Efficient Queueing For Scheduling Deadline-Bound Data Center Flows, Vinaykrishna Gopalakrishna
Theses
This thesis introduces a new deadline aware flow scheduling scheme called Preemptive Efficient Queuing (PEQ). Unlike other schemes which use policies like EDF, SJF or fair share, this scheme aims to procrastinate flows as much as they can afford to, while keeping with their deadlines. Thereby, PEQ prioritizes more urgent flows that have shorter time to procrastinate, or cushion time. Results of PEQ are compared with state-of-the-art schemes for the transport of data-center flows, such as Preemptive Distributed Quick (PDQ) and Deadline-Driven Delivery (D3). The results show that PEQ outperforms D3 and PDQ. We identify results …
Decision Tree Rule-Based Feature Selection For Imbalanced Data, Haoyue Liu
Decision Tree Rule-Based Feature Selection For Imbalanced Data, Haoyue Liu
Theses
A class imbalance problem appears in many real world applications, e.g., fault diagnosis, text categorization and fraud detection. When dealing with an imbalanced dataset, feature selection becomes an important issue. To address it, this work proposes a feature selection method that is based on a decision tree rule and weighted Gini index. The effectiveness of the proposed methods is verified by classifying a dataset from Santander Bank and two datasets from UCI machine learning repository. The results show that our methods can achieve higher Area Under the Curve (AUC) and F-measure. We also compare them with filter-based feature selection approaches, …
Source-Channel Coding For Coordination Over A Noisy Two-Node Network, Sarah A. Obead
Source-Channel Coding For Coordination Over A Noisy Two-Node Network, Sarah A. Obead
Theses
Recently, the concept of coordinating actions between distributed agents has emerged in the information theory literature. It was first introduced by Cuff in 2008 for the point-to-point case of coordination. However, Cuff’s work and the vast majority of the follow-up research are based on establishing coordination over noise-free communication links. In contrast, this thesis investigates the open problem of coordination over noisy point-to-point links. The aim of this study is to examine Shannon’s source-channel separation theorem in the context of coordination. To that end, a general joint scheme to achieve the strong notion of coordination over a discrete memoryless channel …