Energy-Efficient Computational Offloading for Secure NOMA-Enabled Mobile Edge Computing Networks

Computational offloading and nonorthogonal multiple access (NOMA) are two promising technologies for alleviating the problems of limited battery capacity, insufficient computational capability, and massive deployment of terminal equipment in the Internet of Things (IoT) era. However, offloading data...

Full description

Saved in:
Bibliographic Details
Published inWireless communications and mobile computing Vol. 2022; pp. 1 - 11
Main Author Wang, Haiping
Format Journal Article
LanguageEnglish
Published Oxford Hindawi 27.04.2022
John Wiley & Sons, Inc
Subjects
Online AccessGet full text
ISSN1530-8669
1530-8677
DOI10.1155/2022/5230594

Cover

Loading…
More Information
Summary:Computational offloading and nonorthogonal multiple access (NOMA) are two promising technologies for alleviating the problems of limited battery capacity, insufficient computational capability, and massive deployment of terminal equipment in the Internet of Things (IoT) era. However, offloading data may be threatened by malicious eavesdroppers, which leads to more energy consumptions to avoid being eavesdropped. In this work, we study the energy-efficient way of computational offloading under the condition of certain security requirement in a secure NOMA-enabled mobile-edge computing (MEC) networks, where K end users are intended to offload their data to the N-antenna access point (AP) through the same resource block under the threat of an eavesdropper. We first address energy-efficient local resource allocation by minimizing sum-energy consumption of end users, subject to CPU frequencies, offloading bits, secrecy offloading rate, and transmit power. We then optimize the local resources to obtain the minimum computation latency of task for each end user, with the constraint of certain energy budget. The solutions to the above two optimization problems are given and demonstrated numerically by a 3-user scenario.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:1530-8669
1530-8677
DOI:10.1155/2022/5230594