@inproceedings{505e1869e6c54b808bc9a8267ea4cca2,
title = "Edge Computing Tasks Orchestration: An Energy-Aware Approach",
abstract = "In this paper, we investigate experimentally the use of auctioning as a method for optimizing task orchestration in distributed computing systems by making selfish agents compete to execute computational tasks. Our goal is to find an approach that can improve the performance of these systems, using a deadline, fines, and reward limits in a reverse second-price sealed bid auction, to incentive and control the system, specifically in terms of improving task throughput and power consumption. With improvements to both energy consumption and task throughput, we have developed a promising approach, that is able to scale with the number of machines in the system. Results suggest that this type of auction may be useful for improving the implementation of these systems in a wide range of scenarios.",
keywords = "auction, deadline, experiments, game theory, task offloading",
author = "Thomsen, {Johan Lohde} and {Dragsbak Schmidt Thomsen}, Kristian and Schmidt, {Rasmus B.} and Jakobsgaard, {Soren D.} and Thor Beregaard and Michele Albano and Sergio Moreschini and Davide Taibi",
note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; IEEE International Conference on Edge Computing and Communications (EDGE) ; Conference date: 02-07-2023 Through 08-07-2023",
year = "2023",
doi = "10.1109/EDGE60047.2023.00027",
language = "English",
series = "IEEE International Conference on Edge Computing",
publisher = "IEEE",
pages = "115--117",
editor = "Claudio Ardagna and Feras Awaysheh and Hongyi Bian and Chang, {Carl K.} and Chang, {Rong N.} and Flavia Delicato and Nirmit Desai and Jing Fan and Fox, {Geoffrey C.} and Andrzej Goscinski and Zhi Jin and Anna Kobusinska and Omer Rana",
booktitle = "2023 IEEE International Conference on Edge Computing and Communications, IEEE EDGE 2023",
address = "United States",
}