@inproceedings{6720e145681942b2b974391e3d00eb78,
title = "An energy-aware iot femtocloud system",
abstract = "Mobile and IoT devices are becoming increasingly capable computing platforms that are often underutilized. In this paper, we propose a system that leverages the idle compute cycles in a group of heterogeneous mobile and IoT devices that can be clustered to form an edge femtocloud. At the heart of this system, we formulate a task assignment and scheduling problem that strives to maximize the computational throughput of the constructed femtocloud while maintaining the energy consumption below an operator specified threshold. Due to the NP-Completeness of this scheduling problem, we design a set of heuristics to solve this problem. We implement a prototype of our system and use it to evaluate its performance. Our results demonstrate the system's ability to utilize the available compute capacity of a group of mobile and IoT devices while adhering to pre-specified energy constraints. Compared to other schedulers, our scheduler achieves up to 40\% performance improvement.",
keywords = "Edge Computing, Femtocloud, IoT",
author = "Hend Gedawy and Karim Habak and Khaled Harras and Mounir Hamdi",
note = "Publisher Copyright: {\textcopyright} 2018 IEEE.; 2018 IEEE International Conference on Edge Computing, EDGE 2018 ; Conference date: 02-07-2018 Through 07-07-2018",
year = "2018",
month = sep,
day = "26",
doi = "10.1109/EDGE.2018.00015",
language = "English",
series = "Proceedings - 2018 IEEE International Conference on Edge Computing, EDGE 2018 - Part of the 2018 IEEE World Congress on Services",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "58--65",
booktitle = "Proceedings - 2018 IEEE International Conference on Edge Computing, EDGE 2018 - Part of the 2018 IEEE World Congress on Services",
address = "United States",
}