activity
20192021
collaborators

7 papers

q-bio.PE2021

A Modified SEIR Model for the Spread of COVID-19 Considering Different Vaccine Types

Aram Ansary Ogholbake, Hana Khamfroush

The COVID-19 pandemic has influenced the lives of people globally. In the past year many researchers have proposed different models and approaches to explore in what ways the sprea…

cs.NI2021

QoS-Aware Placement of Deep Learning Services on the Edge with Multiple Service Implementations

Nathaniel Hudson, Hana Khamfroush, Daniel E. Lucani

Mobile edge computing pushes computationally-intensive services closer to the user to provide reduced delay due to physical proximity. This has led many to consider deploying deep…

cs.DC2020

Optimal Accuracy-Time Trade-off for Deep Learning Services in Edge Computing Systems

Minoo Hosseinzadeh, Andrew Wachal, Hana Khamfroush +1

With the increasing demand for computationally intensive services like deep learning tasks, emerging distributed computing platforms such as edge computing (EC) systems are becomin…

cs.SI2020

Automatic Query Optimization for Retrieving Traffic Tweets

Emory Hufbauer, Hana Khamfroush

Twitter, like many social media and data brokering companies, makes their data available through a search API (application programming interface). In addition to filtering results…

cs.SI2019

Smart Advertisement for Maximal Clicks in Online Social Networks Without User Data

Nathaniel Hudson, Hana Khamfroush, Brent Harrison +1

Click-through rate (CTR) prediction of advertisements on online social network platforms to optimize advertising is of much interest. Prior works build machine learning models that…

cs.NI2019

Meeting QoS of Users in a Edge to Cloud Platform via Optimally Placing Services and Scheduling Tasks

Matthew Turner, Hana Khamfroush

This paper considers the problem of service placement and task scheduling on a three-tiered edge-to-cloud platform when user requests must be met by a certain deadline. Time-sensit…