A Joint Sensing and Communication Framework in Resource Constrained Mobile Edge Networks

Li, X., Feng, G., Liu, T., Sun, Y. , Qin, S. and Liu, Y. (2022) A Joint Sensing and Communication Framework in Resource Constrained Mobile Edge Networks. In: 2022 IEEE Global Communications Conference (GLOBECOM), Rio de Janeiro, Brazil, 04-08 Dec 2022, pp. 4087-4092. ISBN 9781665435406 (doi: 10.1109/GLOBECOM48099.2022.10001008)

Abstract

Mobile crowd sensing (MCS) is a promising paradigm which leverages sensor-embedded mobile devices to collect and share data. To perform a sensing task in MCS, appropriate participating users are selected first, and efficient data sensing and transmission policies are then designed for data aggregation. In mobile edge networks, network resource availability affects how to select the participating users, and the bandwidth allocated to a user affects its process of data sensing and transmission. Since user selection, bandwidth allocation, data sensing and transmission are closely coupled issues in a resource constrained MCS system, we focus on designing a joint sensing and communication framework in this paper, by jointly optimizing the aforementioned four policies under resource constraints. Specifically, the optimal data sensing and transmission policies are first derived under a given user selection and bandwidth allocation scheme. Then the user selection and bandwidth allocation are optimized based on dynamic programming. Simulation results show that the proposed mechanism significantly outperforms several baseline solutions without considering wireless link vulnerability and/or resource limitations.

• Item Type: Conference Proceedings
• Additional Information: This work was supported in part by Guangdong Basic and Applied Basic Research Foundation under No. 2021A1515110599, in part by the Natural Science Foundation of Sichuan Province under No. 2022NSFSC0481, and in part by the Fundamental Research Funds for the Central Universities under No. ZYGX2020ZB044.
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Sun, Dr Yao and Feng, Professor Gang
• Authors: Li, X., Feng, G., Liu, T., Sun, Y., Qin, S., and Liu, Y.
• College/School: College of Science and Engineering > School of Engineering; College of Science and Engineering > School of Engineering > Autonomous Systems and Connectivity
• ISBN: 9781665435406
• Published Online: 11 January 2023
• Copyright Holders: Copyright © 2022 IEEE
• First Published: First published in 2022 IEEE Global Communications Conference (GLOBECOM): 4087-4092
• Publisher Policy: Reproduced in accordance with the publisher copyright policy

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