Collaborative Optimization Strategy for Dependent Task Offloading in Vehicular Edge Computing by Xiting Peng, Yandi Zhang, Xiaoyu Zhang, Chaofeng Zhang, Wei Yang

“…This paper proposes a task-offloading scheme based on deep reinforcement learning to optimize the strategy between vehicles and edge computing resources. The task-offloading problem is modeled as a Markov Decision Process, and an improved twin-delayed deep deterministic policy gradient algorithm, LT-TD3, is introduced to enhance the decision-making process. …”
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Backbone extraction through statistical edge filtering: A comparative study. by Ali Yassin, Hocine Cherifi, Hamida Seba, Olivier Togni

“…Furthermore, the results suggest a limited influence of the edge betweenness on the filtering process. The backbones global properties analysis (edge fraction, node fraction, weight fraction, weight entropy, reachability, number of components, and transitivity) identifies three typical behavior types for each property. …”
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A Matching Game for LLM Layer Deployment in Heterogeneous Edge Networks by Benedetta Picano, Dinh Thai Hoang, Diep N. Nguyen

“…This mutual selection process minimizes inference latency in the learning process and models the bubble time as game externalities, assuming a sequential pipeline execution. …”
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Iterative Assessment of Edge Criticality: Efficiency Enhancement or Hidden Insufficiency Detection by Vasily Lubashevskiy, Hamza Ejjbiri, Ihor Lubashevsky

“…The second is the Optimization-based approach, which treats network decomposition as an integral process and optimizes the edge sequence for network decomposition using genetic-like algorithms. …”
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Mechanochemical control of graphene etching along zigzag and armchair edge directions by Yilong Jiang, Chuan Tang, Chao Chen, Yangqin Liu, Yang Wang, Seong H. Kim, Junhui Sun, Linmao Qian, Lei Chen

“…To fully realize its potential, it is critical to develop a precision etching process producing graphene edges along desired directions. …”
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The Heat Exchange in the Edge Area – the Problem of Hot Mix Asphalt Compaction by Paweł Mieczkowski

“…This facilitates the correct planning of the process of compaction, and by the same obtaining the required density of mix.…”
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The Cutting Edge of Comics: Destructive Technologies in Morrison and Quitely’s We3 by Isabelle Licari-Guillaume

“…This exploration of hybridity develops within a visual narrative where the low-tech process of paper and pencil drawing is subsequently enhanced through computer treatment, foregrounding its high-tech, digital dimension. …”
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Task distribution offloading algorithm of vehicle edge network based on DQN by Haitao ZHAO, Tangwei ZHANG, Yue CHEN, Houlin ZHAO, Hongbo ZHU

“…In order to achieve the best balance between latency,computational rate and energy consumption,for a edge access network of IoV,a distribution offloading algorithm based on deep Q network (DQN) was considered.Firstly,these tasks of different vehicles were prioritized according to the analytic hierarchy process (AHP),so as to give different weights to the task processing rate to establish a relationship model.Secondly,by introducing edge computing based on DQN,the task offloading model was established by making weighted sum of task processing rate as optimization goal,which realized the long-term utility of strategies for offloading decisions.The performance evaluation results show that,compared with the Q-learning algorithm,the average task processing delay of the proposed method can effectively improve the task offload efficiency.…”
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Leveraging edge learning and game theory for intrusion detection in Internet of things by Haoran LIANG, Jun WU, Chengcheng ZHAO, Jianhua LI

“…With the commercialization of 5G and the development of 6G, more and more Internet of things (IoT) devices are linked to the novel cyber-physical system (CPS) to support intelligent decision making.However, the highly decentralized and heterogeneous IoT devices face potential threats that may mislead the CPS.Traditional intrusion detection solutions cannot protect the privacy of IoT devices, and they have to deal with the single point of failure, which prevents these solutions from being deploying in IoT scenarios.The edge learning and game theory based intrusion detection for IoT was proposed.Firstly, an edge learning based intrusion detection framework was proposed to detect potential threats in IoT.Moreover, a multi-leader multi-follower game was employed to motivate trusted parameter servers and edge devices to participate in the edge learning process.Experiments and evaluations show the security and effectiveness of the proposed intrusion detection framework.…”
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Edge computing privacy protection method based on blockchain and federated learning by Chen FANG, Yuanbo GUO, Yifeng WANG, Yongjin HU, Jiali MA, Han ZHANG, Yangyang HU

“…Aiming at the needs of edge computing for data privacy, the correctness of calculation results and the auditability of data processing, a privacy protection method for edge computing based on blockchain and federated learning was proposed, which can realize collaborative training with multiple devices at the edge of the network without a trusted environment and special hardware facilities.The blockchain was used to endow the edge computing with features such as tamper-proof and resistance to single-point-of-failure attacks, and the gradient verification and incentive mechanism were incorporated into the consensus protocol to encourage more local devices to honestly contribute computing power and data to the federated learning.For the potential privacy leakage problems caused by sharing model parameters, an adaptive differential privacy mechanism was designed to protect parameter privacy while reducing the impact of noise on the model accuracy, and moments accountant was used to accurately track the privacy loss during the training process.Experimental results show that the proposed method can resist 30% of poisoning attacks, and can achieve privacy protection with high model accuracy, and is suitable for edge computing scenarios that require high level of security and accuracy.…”
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A Comprehensive Survey of Cutting-Edge Methods for Software Architecture Evaluation by Amna Sajid, Muhammad Waqas Arshad

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Edge-activated graphene nanopores for thermally robust hydrogen membrane separations by Chi Cheng, Lohyun Kim, Aaron H. Persad, Chun Man Chow, Rohit Karnik

“…Combined experiment and modelling trace this behavior to graphene nanopore edge functional groups, whose thermal fluctuations modulate effective pore size. …”
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Dynamic computing offloading strategy in LEO constellation edge computing network by GAO Yufang, JI Zhi, ZHAO Kanglian, LI Wenfeng, HU Peicong

“…To address this problem, a multi-user computing offloading strategy based on stochastic game was proposed under the system model of dynamic environment low earth orbit constellation edge computing network. On the premise of considering the selfishness of users, the stochastic characteristics of the satellite-ground channel and the dynamic nature of ground user access, from the perspective of game theory, the offloading decision-making process of ground users in the dynamic environment was formulated as a stochastic game. …”
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Provisioning of Live Container Migration in Edge/Cloud Environments: Techniques and Challenges by Radhwan Al-Bayram, Rawaa Qasha

“…In IoT applications and edge/cloud deployment, the live container migration can substantially reduce computing system overheads by minimizing the migration time and transmitting minimum memory pages from the source host without interrupting the service process. …”
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Distributed Optimization for Mobile Robots under Mobile Edge Computing Environment by Hui Luo, Quan Yin

“…In this respect, mobile edge computing (MEC) technology and millimeter wave (mmW) technology can provide powerful support. …”
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Adhesive built-up edge on tool steels due to friction and wear by O.M. Makovkin, O.V. Dykha, I.K. Valchuk

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Deep reinforcement learning based resource provisioning for federated edge learning by Xingyun Chen, Junjie Pang, Tonghui Sun

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A Low-Power Streaming Speech Enhancement Accelerator for Edge Devices by Ci-Hao Wu, Tian-Sheuan Chang

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Resource Allocation for Edge-enhanced Distributed Power Wireless Sensor Network by Gang WU, Jinhui ZHOU, Hui LI

“…Then, the total resource processing capacity of the central unit/distribution unit is determined by controlling the waiting latency in the load transfer process under the common constraints of the remaining resources of the RF remote unit, the load queuing latency, and the remaining resources of the central unit/distribution unit. …”
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A Panoramic Review on Cutting-Edge Methods for Video Anomaly Localization by Rashmiranjan Nayak, Sambit Kumar Mishra, Asish Kumar Dalai, Umesh Chandra Pati, Santos Kumar Das

“…Video anomaly detection and localization is the process of spatiotemporally localizing the anomalous video segment corresponding to the abnormal event or activities. …”
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