Smart phosphor with neuromorphic behaviors enabling full-photoluminescent Write and Read for all-optical physical reservoir computing by Yifei Zhao, Man Li, Man Chung Wong, Xun Han, Feng Guo, Yuan Liu, Xinyue Lao, Zhaoying Dang, Sin-Yi Pang, Zehan Wu, Shi Ye, Jianhua Hao

“…This work explores all-optical information processing based on photoluminescence functions using smart phosphor. …”
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Towards a Granular Computing Framework for Multiple Aspect Trajectory Representation and Privacy Preservation: Research Challenges and Opportunities by Zaineb Chelly Dagdia, Vania Bogorny

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Secure Latency-Aware Task Offloading Using Federated Learning and Zero Trust in Edge Computing for IoMT by Waleed Almuseelem

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A multi-user multi-operator computing pricing method for Internet of things based on bi-level optimization by Wei Jiang, Huiqiang Wang, Bingyang Li, Haibin Lv, Qingchuan Meng

“…These applications typically consume large amounts of computing and energy resources. However, due to the physical size limitations of Internet of things terminals, their computing capacity and power are limited, where users’ needs for application processing delay and power consumption cannot be met. …”
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AoI-enabled multi-node cooperative sensing based on integration of sensing, communication, and computing in vehicular networks by Yiqing ZHOU, Haoyue ZHANG, Yanli QI, Qing CAI, Ling LIU, Jiangzhou WANG

“…For the requirements of real-time services in autonomous driving systems, such as high-definition (HD) maps, based on the integration of sensing, communication, and computing, a multi-node cooperative sensing mechanism was proposed with the age of information (AoI) as the real-time indicator.Considering the constraints on communication and computing resources and vehicle energy consumption, the information collection, transmission and processing of sensing nodes were optimally scheduled to minimize the AoI averaged over time.A Lyapunov-based online scheduling algorithm was proposed to transform the long-term stochastic optimization problem into an online optimization problem, which could be solved with low complexity.Compared with the existing mechanism considering integrated communication and computing, the proposed mechanism can improve real-time performance by 9%～50%.…”
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Penerapan Machine Learning untuk Mengendalikan Parameter Budidaya Tanaman Hidroponik Berbasis Edge dan Cloud Computing by Helmy Helmy, Arif Nursyahid, Thomas Agung Setyawan

“…In this study, the control of pH and TDS utilizes machine learning with a multiple linear regression method and edge computing and cloud computing technologies. Edge computing allows real-time data processing at the hydroponic system's sensor devices, while cloud computing provides large storage and processing capacities. …”
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An Efficient Algorithm for Resource Allocation in Mobile Edge Computing Based on Convex Optimization and Karush–Kuhn–Tucker Method by Kaijing Wang, Shelily F. Akhtar, Fahad Ahmed Al-Zahrani

“…It offers a significant amount of processing and storage resources to the edge of networks, offloading applications from vehicle terminals that are computation-intensive and delay-sensitive. …”
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A novel agent based autonomous and service composition framework for cost optimization of resource provisioning in cloud computing by Aarti Singh, Dimple Juneja, Manisha Malhotra

“…A cloud computing environment offers a simplified, centralized platform or resources for use when needed at a low cost. …”
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Parallel Task Offloading and Trajectory Optimization for UAV-Assisted Mobile Edge Computing via Hierarchical Reinforcement Learning by Tuo Wang, Xitai Na, Yusen Nie, Jinglong Liu, Wenda Wang, Zhenduo Meng

“…With the rapid growth of IoT data and increasing demands for low-latency computation, UAV-assisted mobile edge computing (MEC) offers a flexible solution to overcome the limitations of fixed MEC servers. …”
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Optimal dispatch of distributed renewable energy and energy storage systems via optimal configuration of mobile edge computing by He Jiang, Yan Zhao, Hang Zhou

“…An operating framework of distributed power system is presented based on offload strategy of mobile edge computing (MEC) and optimal allocation of computational quantity. …”
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LightLSB: a lightweight secure transmission mechanism for large-scale biometric images in computing limited environment by ZHANG Denghui, SHEN Shengshang, YAO Jiefeng, LI Mohan, LI Aiping

“…Compared with general computing devices, IoT terminal equipment has been becoming smaller and lighter, making it difficult to support the complex operations required by standard cryptography. …”
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The Construction of a Stream Service Application with DeepStream and Simple Realtime Server Using Containerization for Edge Computing by Wen-Chung Shih, Zheng-Yao Wang, Endah Kristiani, Yi-Jun Hsieh, Yuan-Hsin Sung, Chia-Hsin Li, Chao-Tung Yang

“…Overall, the findings contribute valuable insights into building efficient edge computing architectures that support real-time video processing and streaming.…”
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Direct laser writing of graphene oxide for ultra-low power consumption memristors in reservoir computing for digital recognition by Chen Min, Wan Zhengfen, Dong Hao, Chen Qinyu, Gu Min, Zhang Qiming

“…A memristor is a promising candidate of new electronic synaptic devices for neuromorphic computing. However, conventional memristors often exhibit complex device structures, cumbersome manufacturing processes, and high energy consumption. …”
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Energy-Efficient Multi-Agent Deep Reinforcement Learning Task Offloading and Resource Allocation for UAV Edge Computing by Shu Xu, Qingjie Liu, Chengye Gong, Xupeng Wen

“…The framework enables collaborative decision making among multiple UAVs to efficiently serve sparsely distributed ground mobile devices (MDs) and establish an integrated mobility, communication, and computational offloading model, which formulates a joint optimization problem aimed at minimizing the weighted sum of task processing latency and UAV energy consumption. …”
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A2PC: Augmented Advantage Pointer-Critic Model for Low Latency on Mobile IoT With Edge Computing by Rodrigo Carvalho, Faroq Al-Tam, Noelia Correia

“…As a growing trend, edge computing infrastructures are starting to be integrated with Internet of Things (IoT) systems to facilitate time-critical applications. …”
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SIBILA: Automated Machine-Learning-Based Development of Interpretable Machine-Learning Models on High-Performance Computing Platforms by Antonio Jesús Banegas-Luna, Horacio Pérez-Sánchez

“…Its integration of interpretability constraints alongside automated model development processes marks a substantial step forward in bridging the gap between computational efficiency and model transparency in ML applications. …”
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An online and real-time adaptive operational modal parameter identification method based on fog computing in Internet of Things by Cheng Wang, Haiyang Huang, Jianwei Chen, Wei Wei, Tian Wang

“…However, currently cloud computing cannot satisfy real-time requirements and fog computing is a promising technique for real-time processing. …”
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Multifunctional Au–Ag–Cr Nanocomposites: From Multiplex Sensing and Advanced Logic Computing to Scalable Information Protection by Jie Zhou, Jiao Yang Lu, Zhi Xin Xie, Dong Hua Wang, Bin Sheng He, Wei Tao Huang

“…This work not only offers novel insights into the design and multifunctionality of multicomponent nanocomposites but also paves the way for a new paradigm in molecular information technology that integrates sensing, logic processing, and information security.…”
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Ranking data privacy techniques in cloud computing based on Tamir’s complex fuzzy Schweizer-Sklar aggregation approach by Jabbar Ahmmad, Hamiden Abd El-Wahed Khalifa, Hafiz Muhammad Waqas, Alhanouf Alburaikan, Taha Radwan

“…Abstract In the era of cloud computing, it has become an important challenge to secure data privacy by storing and processing massive amounts of sensitive information in shared environments. …”
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WiCNNAct: Wi-Fi-Based Human Activity Recognition Utilizing Deep Learning on the Edge Computing Devices by Venkata Raghava Shashank Viswanathuni, Rakesh Reddy Yakkati, Sreenivasa Reddy Yeduri, Linga Reddy Cenkeramaddi

“…The model is deployed on various edge computing devices, including Raspberry Pi, to assess real-time deployment feasibility. …”
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