@inproceedings{937b34750cb344f0a275ca7c38e24bab,
title = "Resource Allocation and Throughput Maximization for IoT Real-time Applications",
abstract = "The foreseen enormous generation of mobile data would result in congestion of the spectrum available. To efficiently use the available spectrum new paradigm named fog computing is a promising solution. In this paper, we developed a fog-IoT network to provide an \textbackslash{}varepsilon-optimal resource allocation to maximize the overall network throughput. A joint cloudlet selection and power allocation problem is formulated under association and Quality-of-Service (QoS) constraints. The formulated problem falls in class of mixed-integer nonlinear programming (MINLP) problem which is NP-hard generally. We solved our problem by applying a less complex linearization technique that uses the outer approximation algorithm (OAA). Resource allocation and power allocation are efficiently conducted as a result of this optimization, which is less complicated compared to exhaustive search.",
author = "Rabeea Basir and Saad Qaisar and Mudassar Ali and Haris Pervaiz and Muhammad Naeem and Imran, \{Muhammad Ali\}",
note = "Publisher Copyright: {\textcopyright} 2020 IEEE.; 91st IEEE Vehicular Technology Conference, VTC Spring 2020 ; Conference date: 25-05-2020 Through 28-05-2020",
year = "2020",
month = may,
doi = "10.1109/VTC2020-Spring48590.2020.9129613",
language = "English",
series = "IEEE Vehicular Technology Conference",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "2020 IEEE 91st Vehicular Technology Conference, VTC Spring 2020 - Proceedings",
address = "United States",
}