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arXiv 2025年

作者： Xia, Xiaobo Liu, Xiaofeng Liu, Jiale Fang, Kuai Lu, Lu Oymak, Samet Currie, William S. Liu, Tongliang School of Computer Science University of Sydney Australia Department of Statistics and Data Science Yale University United States Michigan Institute for Data and AI in Society University of Michigan United States School for Environment and Sustainability University of Michigan United States College of Information Science and Technology Penn State University United States Department of Earth System Science Stanford University United States Department of Electrical Engineering and Computer Science University of Michigan United States

Water quality is foundational to environmental sustainability, ecosystem resilience, and public health. Deep learning models, particularly Long Short-Term Memory (LSTM) networks, offer trans-formative potential for large-scale water quality prediction and scientific insights generation. However, their widespread adoption in high-stakes decision-making, such as pollution mitigation and equitable resource allocation, is prevented by unresolved trustworthiness challenges including fairness, uncertainty, interpretability, robustness, generalizability, and reproducibility. In this work, we present the first comprehensive evaluation of trustworthiness in a continental-scale multi-task LSTM model predicting 20 water quality variables (encompassing physical/chemical processes, geochemical weathering, and nutrient cycling) across 482 U.S. basins. Our investigation uncovers systematic patterns of model performance disparities linked to basin characteristics, the inherent complexity of biogeochemical processes, and variable predictability, emphasizing critical performance fairness concerns. We further propose methodological frameworks for quantitatively evaluating critical aspects of trustworthiness, including uncertainty, interpretability, and robustness, identifying key limitations that could challenge reliable real-world deployment. This work serves as a timely call to action for advancing trustworthy data-driven methods for water resources management and provides a pathway to offering critical insights for researchers, decision-makers, and practitioners seeking to leverage artificial intelligence (AI) responsibly in environmental management. Copyright © 2025, The Authors. All rights reserved.

关键词： Resource allocation

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Coalition Formation for Heterogeneous Federated Learning Enabled Channel Estimation in RIS-assisted Cell-free MIMO

arXiv

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arXiv 2025年

作者： Qi, Nan Liu, Haoxuan Tsiftsis, Theodoros A. Boulogeorgos, Alexandros-Apostolos A. Zhou, Fuhui Jin, Shi Wu, Qihui Key Laboratory of Dynamic Cognitive System of Electromagnetic Spectrum Space Ministry of Industry and Information Technology Nanjing University of Aeronautics and Astronautics Nanjing210016 China Department of Informatics and Telecommunications University of Thessaly Lamia35100 Greece Department of Electrical and Computer Engineering University of Western Macedonia Kozani50100 Greece National Mobile Communications Research Laboratory Frontiers Science Center for Mobile Information Communication and Security Southeast University Nanjing210096 China

Downlink channel estimation remains a significant bottleneck in reconfigurable intelligent surface-assisted cell-free multiple-input multiple-output communication systems. Conventional approaches primarily rely on centralized deep learning methods to estimate the high-dimensional and complex cascaded channels. These methods require data aggregation from all users for centralized model training, leading to excessive communication overhead and significant data privacy concerns. Additionally, the large size of local learning models imposes heavy computational demands on end users, necessitating strong computational capabilities that most commercial devices lack. To address the aforementioned challenges, a coalition-formation-guided heterogeneous federated learning (FL) framework is proposed. This framework leverages coalition formation to guide the formation of heterogeneous FL user groups for efficient channel estimation. Specifically, by utilizing a distributed deep reinforcement learning (DRL) approach, each FL user intelligently and independently decides whether to join or leave a coalition, aiming at improving channel estimation accuracy, while reducing local model size and computational costs for end users. Moreover, to accelerate the DRL-FL convergence process and reduce computational burdens on end users, a transfer learning method is introduced. This method incorporates both received reference signal power and distance similarity metrics, by considering that nodes with similar distances to the base station and comparable received signal power have a strong likelihood of experiencing similar channel fading. Massive experiments performed that reveal that, compared with the benchmarks, the proposed framework significantly reduces the computational overhead of end users by 16%, improves data privacy, and improves channel estimation accuracy by 20%. © 2025, CC BY.

关键词： Federated learning

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Dynamic Pricing based Near-Optimal Resource Allocation for Elastic Edge Offloading

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IEEE Transactions on Mobile Computing 2025年

作者： Xia, Yun Xue, Hai Zhang, Di Mumtaz, Shahid Xu, Xiaolong Rodrigues, Joel J. P. C. University of Shanghai for Science and Technology School of Optical-Electrical and Computer Engineering Shanghai200093 China Zhengzhou University School of Electrical and Information Engineering Henan International Joint Laboratory of Intelligent Health Information System National Telemedicine Center National Engineering Laboratory for Internet Medical Systems and Applications Zhengzhou450001 China Nottingham Trent University Department of Engineering NottinghamNG1 4FQ United Kingdom Kyung Hee University Department of Electronic Engineering Gyeonggi-do Yongin-si17104 Korea Republic of Nanjing University of Information Science and Technology School of Software Nanjing210044 China Amazonas State University Manaus Brazil

In mobile edge computing (MEC), task offloading can significantly reduce task execution latency and energy consumption of end user (EU). However, edge server (ES) resources are limited, necessitating efficient allocation to ensure the sustainable and healthy development for MEC system. In this paper, we propose a dynamic pricing mechanism based near-optimal resource allocation for elastic edge offloading. First, we construct a resource pricing model and accordingly develop the utility functions for both EU and ES, the optimal pricing model parameters are derived by optimizing the utility functions. In the meantime, our theoretical analysis reveals that the EU's utility function reaches a local maximum within the search range, but exhibits barely growth with increased resource allocation beyond this point. To this end, we further propose the Dynamic Inertia and Speed-Constrained particle swarm optimization (DISC-PSO) algorithm, which efficiently identifies the near-optimal resource allocation. Comprehensive simulation results validate the effectiveness of DISC-PSO algorithm, demonstrating that it significantly outperforms existing schemes by reducing the average number of iterations to reach a near-optimal solution by 86.88%, increasing the EU utility function value by 0.13%, and decreasing the variance of results by 96.78%. © 2025 IEEE. All rights reserved.

关键词： Mobile edge computing

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Generative AI-Enhanced Cooperative MEC of UAVs and Ground Stations for Unmanned Surface Vehicles

arXiv

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arXiv 2025年

作者： You, Jiahao Jia, Ziye Dong, Chao Wu, Qihui Han, Zhu The Key Laboratory of Dynamic Cognitive System of Electromagnetic Spectrum Space Ministry of Industry and Information Technology Nanjing University of Aeronautics and Astronautics Jiangsu Nanjing211106 China National Mobile Communications Research Laboratory Southeast University Jiangsu Nanjing211111 China Department of Electrical and Computer Engineering University of Houston HoustonTX77004 United States Department of Computer Science and Engineering Kyung Hee University Seoul446-701 Korea Republic of

The increasing deployment of unmanned surface vehicles (USVs) require computational support and coverage in applications such as maritime search and rescue. Unmanned aerial vehicles (UAVs) can offer low-cost, flexible aerial services, and ground stations (GSs) can provide powerful supports, which can cooperate to help the USVs in complex scenarios. However, the collaboration between UAVs and GSs for USVs faces challenges of task uncertainties, USVs trajectory uncertainties, heterogeneities, and limited computational resources. To address these issues, we propose a cooperative UAV and GS based robust multi-access edge computing framework to assist USVs in completing computational tasks. Specifically, we formulate the optimization problem of joint task offloading and UAV trajectory to minimize the total execution time, which is in the form of mixed integer nonlinear programming and NP-hard to tackle. Therefore, we propose the algorithm of generative artificial intelligence-enhanced heterogeneous agent proximal policy optimization (GAI-HAPPO). The proposed algorithm integrates GAI models to enhance the actor network ability to model complex environments and extract high-level features, thereby allowing the algorithm to predict uncertainties and adapt to dynamic conditions. Additionally, GAI stabilizes the critic network, addressing the instability of multi-agent reinforcement learning approaches. Finally, extensive simulations demonstrate that the proposed algorithm outperforms the existing benchmark methods, thus highlighting the potentials in tackling intricate, cross-domain issues in the considered scenarios. © 2025, CC BY.

关键词： Unmanned surface vehicles

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Handoff techniques for 4G wireless mobile Internet

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information technology Journal 2007年第5期6卷 745-750页

作者： Li, Xichun Salleh, Rosli Department of Computer System and Technology Faculty of Computer Science and Information Technology University of Malay 50603 Kuala Lumpur Malaysia

In this study, new handoff technique is developed to support wireless mobile bandwidth efficiency and higher data rates. This study will address handoff issues when a mobile node comes into WLAN overlapping region from a CDMA2000 coverage area and the mobile node will be supplied service by these two networks simultaneously through setting up a mix-bandwidth data path between the two networks. The performance of the proposed new data path will be evaluated and compared with current existing scheme through extensive simulations. The cost of the established new data path is also evaluated in terms of throughput and data transmission efficiency. © 2007 Asian Network for Scientific information.

关键词： Wireless networks

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A bandwidth-aware job grouping-based scheduling on grid environment

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information technology Journal 2009年第3期8卷 372-377页

作者： Ang, T.F. Ng, W.K. Ling, T.C. Por, L.Y. Liew, C.S. Department of Computer System and Technology Faculty of Computer Science and Information Technology University of Malaya 50603 Kuala Lumpur Malaysia

This study explores the feasibility of job scheduling strategies and extend the job grouping-based approach using the idea of bandwidth-awareness. As today's best-effort network generally experiences low bandwidth and high delay, we aim to maximize the Grid resource utilization and reduce the delay by considering the bandwidth criterion. A simulation environment using GridSim is developed to model job scheduling process. Exploiting the simulation environment, a job scheduling strategy that encompasses the job grouping concept coupled together with bandwidth-aware scheduling is proposed and evaluated. The proposed scheduling strategy focuses on grouping independent jobs with small processing requirements into suitable jobs with larger processing requirements and schedules them in accordance with indeterminist network conditions. The simulation result demonstrates that the proposed strategy succeeds in minimizing the total processing time by at most 82% as compared to its counterpart. © 2009 Asian Network for Scientific information.

关键词： Scheduling

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GSM mobile SMS/MMS using public key infrastructure: M-PKI

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WSEAS Transactions on computers 2008年第8期7卷 1219-1229页

作者： Anuar, Nor Badrul Kuen, Lai Ngan Zakaria, Omar Gani, Abdullah Wahab, Ainuddin Wahid Abdul Department of System and Computer Technology Faculty of Computer Science and Information Technology University of Malaya 50603 Kuala Lumpur Malaysia

Presently, mobile handheld device has successfully replaced traditional telephone to become the most popular wireless communication tools. Mobile Short Message Service (SMS) and Multimedia Message Service (MMS) fulfill almost all the user requirements as an effective communication and information delivering service. Since SMS/MMS become so popular on daily communication, there is a demand to communicate or exchange confidential information in a secure environment. Public Key Infrastructure (PKI) is a proven solution, which using pairing of key, for secure communication encryption. In this paper, m-PKI is introduced to provide PKI encryption to the mobile SMS and MMS. This new approach allows the end-user to send private and classified message via SMS. The key pair generation and distribution are performed by the Certificate Authority (CA). The size of the key pair are studied and decided by the tradeoff between performance and security.

关键词： Public key cryptography

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Usability and performance of secure mobile messaging: M-PKI

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WSEAS Transactions on information Science and Applications 2009年第2期6卷 179-189页

Human life style change substantially when the cellular technology goes commercial. Short Messaging Service (SMS) and Multimedia Message Service (MMS) play important roles in our daily life. The recent report carried out by Mobile Data Association (MDA) [1] shows that the yearly growth of SMS and MMS achieves 30 percent from year 2007 to 2008. Conventional SMS/ MMS does not provide any protection on the text message sent. It causes the security threats such as privacy and message integrity. Mobile users seek for the solution to allow them to exchange confidential information in a safe environment. This leads to the implementation of M-PKI, which is an application that secures the mobile messaging service by using public key infrastructure (PKI). This new approach allows the end-user to send private and classified message via SMS. Besides, M-PKI offers message classification. This feature is specially designed to meet various user requirements on the level of security and performance. The usage and performance of M-PKI messaging in performing encryption and decryption process are tested on selected java-enabled phone.

关键词： Public key cryptography

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Mobile multimedia control model for fire disaster of city building

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Journal of Applied Sciences 2009年第2期9卷 304-311页

作者： Li, Xichun Salleh, R. Zakaria, O. Department of Computer System and Technology Faculty of Computer Science and Information Technology University of Malay 50603 Kuala Lumpur Malaysia

In this study, we focus on combination of GIS and 5G wireless mobile multimedia networks to propose a real-time file disaster processing model-Mobile Multimedia Control Model (MMCM) so that a quick response can be taken once fires over to reduce destroy, especially peoples life. In the end of the study, two models will be compared. © 2009 Asian Network for Scientific information.

关键词： Disasters

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Mobile Collaborative Informal Learning Design: Study of Collaborative Effectiveness Using Activity Theory

International Journal of Interactive Mobile Technologies

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International Journal of Interactive Mobile Technologies 2012年第3期6卷 34-41页

作者： Baloch, Hasnain Zafar Abdulrhaman, Aziziah Ihad, Noorminshah A. University of Technology Malaysia Malaysia Faculty of Computer Science and Information system Department of Information system University of Technology Malaysia Malaysia

Smart Mobile Devices (SMD) are there for many years but using them as learning tools started to emerge as new research area. The trend to merge collaborative learning methodology by using mobile devices in informal context is important for implementation of Learner Centric Learning (LCL). Survey and numerous studies show that more than 95% of students in colleges are users of these smart mobile devices in developed world. Developing counties are also catching up and we can see this percentage is almost same in university level in these countries. Students are using SMDs for learning in some form. Higher education Institutions also try to embark their E-learning to Mobile learning (ML). The aim of this paper is to do propose operational framework for designing Mobile Collaborative Informal learning activities using SMDs. Show results of experimental and case study done to study the Mobile Collaborative Informal learning using Activity Theory (AT). Core Components of framework are Mobile Learning Activities/Objects, Wireless/Mobile Smart devices, Collaborative knowledge and Collaborative learning. The research mention here is its infancy stage. © 2012, International Federation of Engineering Education Societies (IFEES). All rights reserved.

关键词： Students

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