2021 International Conference on Network Communication and Information Security (ICNCIS2021)
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Assoc. Prof. Yaqiong Liu

Assoc. Prof. Yaqiong Liu

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Assoc. Prof.  Yaqiong Liu

Beijing University of Posts and Telecommunications,

School of Information and Communication Engineering,

China


Speech title:Joint Optimization of Latency and Energy Consumption for Mobile Edge Computing Based Proximity Detection in Road Networks


Brief biography: 

Yaqiong Liu received the bachelor’s degree in computer science and technology and the second bachelor’s degree in financial management from Tianjin University, China, and the Ph.D. degree in computer science and engineering from Nanyang Technological University, Singapore. She is currently an Associate Professor with the School of Information and Communication Engineering, Beijing University of Posts and Telecommunications, China. Her research interests include edge computing, IoT, spatial query processing, location-based services.



Abstract: 

In recent years, artificial intelligence and automotive industry have developed rapidly, and autonomous driving has gradually become the focus of the industry. In road networks, the problem of proximity detection refers to detecting whether two moving objects are close to each other or not in real time. However, the battery life and computing capability of mobile devices are limited in the actual scene, which results in high latency and energy consumption. Therefore, it is a tough problem to determine the proximity relationship between mobile users with low latency and energy consumption. In this article, we aim at finding a tradeoff between latency and energy consumption. We formalize the computation offloading problem base on mobile edge computing (MEC) into a constrained multi-objective optimization prob lem (CMOP) and utilize NSGA-II to solve it. The simulation results demonstrate that NSGA-II can find the Pareto set, which reduces the latency and energy consumption effectively. In addition, a large number of solutions provided by the Pareto set give us more choices of the offloading decision according to the actual situation.