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Stability-aware data offloading optimization in edge-based mobile crowdsensing

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Abstract

Mobile CrowdSensing (MCS) has become a powerful sensing paradigm for information collection recently. As sensing becomes more complicated, it is beneficial to deploy edge servers between users and the cloud center with a so-called mobile edge computing. Instead of directly offloading the sensing data to the cloud center, mobile users offload the sensing data to the edge servers. Then, the edge server processes and transmits the data to the cloud center in a distributed and parallel manner. It’s however critically important to balance cost, such as energy consumption, and the stability of the queues on both mobile users and edge servers. Therefore, to minimize the data offloading cost while maintaining system stability, we should carefully design the sensing data offloading strategy for edge-based crowdsensing. To this end, we formulate a double-queue Lyapunov optimization problem and propose a sensing data offloading strategy. We analyze the upper bounds of the total offloading cost and queue backlog. We further formulate the heterogeneous sensing data problem as the minimum weight bipartite graph matching problem and develop an approach that is based on Kuhn-Munkres algorithm. Finally, we conduct simulations based on three mobility sets. Simulation results show that the proposed techniques outperform several state-of-art algorithms in overall cost, system stability, and other performance metrics.

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Acknowledgements

This work was supported in part by the National Key R&D Program of China (Grant Nos. 2022YFB3103700 and 2022YFB3103702), and the National Natural Science Foundation of China (Grant Nos. 62272193, 62472194, and 62102161).

Author information

Authors and Affiliations

  1. Department of Computer Science and Technology, Jilin University, Changchun, 130012, China

    Dongming Luan, En Wang, Wenbin Liu & Yongjian Yang

  2. Department of Computer Science, University of North Carolina at Greensboro, Greensboro, NC, 27412, USA

    Jing Deng

Authors
  1. Dongming Luan
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  2. En Wang
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  4. Yongjian Yang
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Corresponding author

Correspondence to Wenbin Liu.

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Competing interests The authors declare that they have no competing interests or financial conflicts to disclose.

Additional information

Dongming LUAN received his BE degree in software engineering from Jilin University, China in 2017, his ME degree in computer science and technology from Jilin University, China in 2020, and his PhD degree in computer science and technology from Jilin University, China in 2024. Now, he is an assistant researcher in College of Computer Science and Technology in Jilin University, China. His current research interest is mobile crowdsensing.

En WANG (Member, IEEE) received his BE degree in software engineering from Jilin University, China in 2011 and his ME and PhD degrees in computer science and technology from Jilin University, China in 2013 and 2016, respectively. He was also a joint PhD student with the Department of Computer and Information Science, Temple University, USA. He is currently a professor in the Department of Computer Science and Technology at Jilin University, China. His current research focuses on mobile computing, crowd intelligence, and data mining.

Wenbin LIU received the BS degree in physics and the PhD degree in computer science and technology from Jilin University, China in 2012 and 2020. He was also a joint PhD student in the Wireless Networks and Multimedia Services Department, Telecom SudParis/Institut Mines-Telecom, Evry, France. He is currently a Postdoctoral Researcher in Dingxin Scholar Program with the College of Computer Science and Technology, Jilin University, China. His research interests include mobile crowdsensing, mobile computing, and ubiquitous computing.

Yongjian YANG received his BE degree in colledge of automatization in Jilin University of Technology, China in 1983, his ME degree in computer communication from Beijing University of Post and Telecommunications, China in 1991, and his PhD degree in software and theory of computer from Jilin University, China in 2005. He is currently a professor and a PhD supervisor at Jilin University, the vice dean of the Software College of Jilin University, the director of Key lab under the Ministry of Information Industry, the standing director of the Communication Academy, and a member of the Computer Science Academy of Jilin Province. His research interests include: network intelligence management, wireless mobile communication.

Jing DENG (Fellow, IEEE) is the Bank of America Distinguished Professor and head of the Department of Computer Science at UNC Greensboro, USA. He received his PhD degree from School of Electrical and Computer Engineering at Cornell University, USA in January, 2002. He received his ME and BE degrees in Electronic Engineering at Tsinghua University, China in 1994 and 1997, respectively. Dr. Deng is an associate editor of IEEE Transactions on Mobile Computing. He served as an editor of IEEE Transactions on Vehicular Technology during 2008–2018. He received the Test-of-Time Award presented by the ACM Special Interest Group on Security, Audit and Control (SIGSAC) in 2013. Dr. Deng’s research interests include online social networks, wireless networks, and network security.

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Luan, D., Wang, E., Liu, W. et al. Stability-aware data offloading optimization in edge-based mobile crowdsensing. Front. Comput. Sci. 19, 1911503 (2025). https://doi.org/10.1007/s11704-024-40620-6

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