Cloud Computing

Predicting Short-Term Variations in End-to-End Cloud Data Transfer Throughput Using Neural Networks

Predicting the data transfer throughput of cloud networks plays an important role in several resource optimization applications, such as auto-scaling, replica selection, and load balancing. However, constant short-term variations in cloud networks make the prediction of end-to-end data transfer throughput a very challenging task.

Categories:: Cloud Computing

319 Views

Data collection of user-generated content of social network of communities Reddit in 2023

This data collection focuses on capturing user-generated content from the popular social network Reddit during the year 2023. This dataset comprises 29 user-friendly CSV files collected from Reddit, containing textual data associated with various emotions and related concepts.

Categories:: Artificial Intelligence
Education and Learning Technologies
Machine Learning
Other
Reliability
Security
Social Sciences
Cloud Computing
Communications
Computational Intelligence
Communications
Security

2028 Views

Using AWS rekognition to find trending Celebrities

Goal

The goal of this project is to leverage Amazon Web Service's machine learning services to create a dataset that automatically adds and updates files on IEEE DataPort's S3 storage. Through this process, we sought to learn and demonstrate how an ongoing data collection script can create a shared living dataset by streaming data to our IEEE DataPort dataset storage. In the process, we also hoped to gain further insights into areas including:

Categories:: Social Sciences
Image Processing
Cloud Computing

200 Views

A Dataset of Network Traffic Collected During Large-Scale Human Genome Sequence Analysis

This dataset contains .pcap files collected during the execution of variant calling on large number of human genomes using a cluster. The GATK4 variant calling pipeline was executed using AVAH in two testbeds, CloudLab and FABRIC. A 16-node cluster was used on CloudLab, and an 8-node cluster was used on FABRIC. The files were collected by running tcpdump on the network interfaces of the nodes.

Categories:: Biomedical and Health Sciences
Cloud Computing

858 Views

QoS requirements for Fog Computing applications

Currently, Internet applications running on mobile devices generate a massive amount of data that can be transmitted to a Cloud for processing. However, one fundamental limitation of a Cloud is the connectivity with end devices. Fog computing overcomes this limitation and supports the requirements of time-sensitive applications by distributing computation, communication, and storage services along the Cloud to Things (C2T) continuum, empowering potential new applications, such as smart cities, augmented reality (AR), and virtual reality (VR).

Categories:: IoT
Machine Learning
Cloud Computing

1344 Views

Master-Slave IoT for Active Healthy Life Style

The main objective of this project is to design and develop a collaborative framework which facilitates real-time tracking of a target person even when GPS signal is not available, while collecting motion data to infer his or her lifestyle and health status. The framework orchestrates a wide range of technologies such as localization technologies, machine learning and AI, sensor data analytics and cloud computing. The overall framework design also takes into consideration the culture, lifestyles, behaviours and infrastructures of ASEAN countries.