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LSU Doctoral Dissertations

Computer Sciences

Fairness

Publication Year

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Full-Text Articles in Physical Sciences and Mathematics

Predictive Modeling Of Asynchronous Event Sequence Data, Jin Shang May 2020

Predictive Modeling Of Asynchronous Event Sequence Data, Jin Shang

LSU Doctoral Dissertations

Large volumes of temporal event data, such as online check-ins and electronic records of hospital admissions, are becoming increasingly available in a wide variety of applications including healthcare analytics, smart cities, and social network analysis. Those temporal events are often asynchronous, interdependent, and exhibiting self-exciting properties. For example, in the patient's diagnosis events, the elevated risk exists for a patient that has been recently at risk. Machine learning that leverages event sequence data can improve the prediction accuracy of future events and provide valuable services. For example, in e-commerce and network traffic diagnosis, the analysis of user activities can be …


Fairness And Approximation In Multi-Version Transactional Memory., Basem Ibrahim Assiri Jan 2016

Fairness And Approximation In Multi-Version Transactional Memory., Basem Ibrahim Assiri

LSU Doctoral Dissertations

Shared memory multi-core systems bene_x000C_t from transactional memory implementations due to the inherent avoidance of deadlocks and progress guarantees. In this research, we examine how the system performance is a_x000B_ected by transaction fairness in scheduling and by the precision in consistency. We _x000C_rst explore the fairness aspect using a Lazy Snapshot (multi-version) Algorithm. The fairness of transactions scheduling aims to balance the load between read-only and update transactions. We implement a fairness mechanism based on machine learning techniques that improve fairness decisions according to the transaction execution history. Experimental analysis shows that the throughput of the Lazy Snapshot Algorithm is …


A Study On Fairness And Latency Issues Over High Speed Networks And Data Center Networks, Lin Xue Jan 2014

A Study On Fairness And Latency Issues Over High Speed Networks And Data Center Networks, Lin Xue

LSU Doctoral Dissertations

Newly emerging computer networks, such as high speed networks and data center networks, have characteristics of high bandwidth and high burstiness which make it difficult to address issues such as fairness, queuing latency and link utilization. In this study, we first conduct extensive experimental evaluation of the performance of 10Gbps high speed networks. We found inter-protocol unfairness and larger queuing latency are two outstanding issues in high speed networks and data center networks. There have been several proposals to address fairness and latency issues at switch level via queuing schemes. These queuing schemes have been fairly successful in addressing either …