Energy-Efficient Joint Resource Allocation Algorithms for MEC-Enabled Emotional Computing in Urban Communities

This paper considers a mobile edge computing (MEC) system, where the MEC server first collects data from emotion sensors and then computes the emotion of each user. We give the formula of the emotional prediction accuracy. In order to improve the energy efficiency of the system, we propose resources...

Ausführliche Beschreibung

Gespeichert in:

Bibliographische Detailangaben
Veröffentlicht in:	IEEE access Jg. 7; S. 137410 - 137419
Hauptverfasser:	Yang, Ziyan, Du, Yao, Che, Chang, Wang, Wenyong, Mei, Haibo, Zhou, Dongdai, Yang, Kun
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Piscataway IEEE 2019 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Algorithms Computational geometry Computational modeling Convexity Data collection Edge computing Emotion recognition emotional computing Emotions Energy consumption Energy efficiency Feature extraction Internet of Things Mobile computing mobile edge computing (MEC) Optimization Optimization techniques Resource allocation Resource management resources allocation Sensors Servers
ISSN:	2169-3536, 2169-3536
Online-Zugang:	Volltext
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

Schreiben Sie den ersten Kommentar!