Open Access. Powered by Scholars. Published by Universities.®
Articles 1 - 3 of 3
Full-Text Articles in Engineering
Load-Adjusted Prediction For Proactive Resource Management And Video Server Demand Profiling, Obinna Izima, Ruairí De Fréin
Load-Adjusted Prediction For Proactive Resource Management And Video Server Demand Profiling, Obinna Izima, Ruairí De Fréin
Articles
To lower costs associated with providing cloud resources, a network manager would like to estimate how busy the servers will be in the near future. This is a necessary input in deciding whether to scale up or down computing requirements. We formulate the problem of estimating cloud computational requirements as an integrated framework comprising of a learning and an action stage. In the learning stage, we use Machine Learning (ML) models to predict the video Quality of Delivery (QoD) metric for cloud-hosted servers and use the knowledge gained from the process to make resource management decisions during the action stage. …
A Survey Of Machine Learning Techniques For Video Quality Prediction From Quality Of Delivery Metrics, Obinna Izima, Ruairí De Fréin, Ali Malik
A Survey Of Machine Learning Techniques For Video Quality Prediction From Quality Of Delivery Metrics, Obinna Izima, Ruairí De Fréin, Ali Malik
Articles
A growing number of video streaming networks are incorporating machine learning (ML) applications. The growth of video streaming services places enormous pressure on network and video content providers who need to proactively maintain high levels of video quality. ML has been applied to predict the quality of video streams. Quality of delivery (QoD) measurements, which capture the end-to-end performances of network services, have been leveraged in video quality prediction. The drive for end-to-end encryption, for privacy and digital rights management, has brought about a lack of visibility for operators who desire insights from video quality metrics. In response, numerous solutions …
Applications Of Artificial Intelligence To Cryptography, Jonathan Blackledge, Napo Mosola
Applications Of Artificial Intelligence To Cryptography, Jonathan Blackledge, Napo Mosola
Articles
This paper considers some recent advances in the field of Cryptography using Artificial Intelligence (AI). It specifically considers the applications of Machine Learning (ML) and Evolutionary Computing (EC) to analyze and encrypt data. A short overview is given on Artificial Neural Networks (ANNs) and the principles of Deep Learning using Deep ANNs. In this context, the paper considers: (i) the implementation of EC and ANNs for generating unique and unclonable ciphers; (ii) ML strategies for detecting the genuine randomness (or otherwise) of finite binary strings for applications in Cryptanalysis. The aim of the paper is to provide an overview on …