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Training time minimization for federated edge learning with optimized gradient quantization and bandwidth Research Article

Peixi LIU, Jiamo JIANG, Guangxu ZHU, Lei CHENG, Wei JIANG, Wu LUO, Ying DU, Zhiqin WANG,jiangjiamo@caict.ac.cn,gxzhu@sribd.cn

Frontiers of Information Technology & Electronic Engineering 2022, Volume 23, Issue 8, Pages 1247-1263 doi: 10.1631/FITEE.2100538

Abstract: Training a machine learning model with (FEEL) is typically time consuming due to the constrained computationpower of edge devices and the limited wireless resources in edge networks.In this study, the problem is investigated in a quantized FEEL system, where heterogeneous edge devicessend quantized gradients to the edge server via orthogonal channels.With different learning tasks and models, the validation of our analysis and the near-optimal performance

Keywords： Federated edge learning Quantization optimization Bandwith allocation Training time minimization

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Low-Cost Federated Broad Learning for Privacy-Preserved Knowledge Sharing in the RIS-Aided Internet of

Xiaoming Yuan,Jiahui Chen,Ning Zhang,Qiang Ye,Changle Li,Chunsheng Zhu,Xuemin Sherman Shen,

Engineering doi: 10.1016/j.eng.2023.04.015

Abstract: In order to protect data privacy and improve data learning efficiency in knowledge sharing, we proposean asynchronous federated broad learning (FBL) framework that integrates broad learning (BL) into federatedlearning (FL).Based on the results of resource scheduling, we design a reward-allocation algorithm based on federatedincentive learning (FIL) in FBL to compensate clients for their costs.

Keywords： Knowledge sharing Internet of Vehicles Federated learning Broad learning Reconfigurable intelligent surfaces

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Incentive-Aware Blockchain-Assisted Intelligent Edge Caching and Computation Offloading for IoT Article

Qian Wang, Siguang Chen, Meng Wu

Engineering 2023, Volume 31, Issue 12, Pages 127-138 doi: 10.1016/j.eng.2022.10.014

Abstract: Facing with the explosive growth of data and the higher quality of service required by users, edge computingHowever, the resources in edge nodes (ENs) are not inexhaustible.In this paper, we propose an incentive-aware blockchain-assisted intelligent edge caching and computationFurthermore, a blockchain incentive and contribution co-aware federated deep reinforcement learning algorithmMeanwhile, a contribution-based federated aggregation method is developed, in which the aggregation weights

Keywords： Computation offloading Caching Incentive Blockchain Federated deep reinforcement learning

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Federated unsupervised representation learning Research Article

Fengda ZHANG, Kun KUANG, Long CHEN, Zhaoyang YOU, Tao SHEN, Jun XIAO, Yin ZHANG, Chao WU, Fei WU, Yueting ZHUANG, Xiaolin LI,fdzhang@zju.edu.cn,kunkuang@zju.edu.cn

Frontiers of Information Technology & Electronic Engineering 2023, Volume 24, Issue 8, Pages 1181-1193 doi: 10.1631/FITEE.2200268

Abstract: To leverage the enormous amount of unlabeled data on distributed edge devices, we formulate a new problemin called federated unsupervised (FURL) to learn a common representation model without supervisionTo address these challenges, we propose the federated contrastive averaging with dictionary and alignment

Keywords： Federated learning Unsupervised learning Representation learning Contrastive learning

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Federated Learning for 6G: Applications, Challenges, and Opportunities Review

Zhaohui Yang, Mingzhe Chen, Kai-Kit Wong, H. Vincent Poor, Shuguang Cui

Engineering 2022, Volume 8, Issue 1, Pages 33-41 doi: 10.1016/j.eng.2021.12.002

Abstract:

Standard machine-learning approaches involve the centralization of training data in a data center,where centralized machine-learning algorithms can be applied for data analysis and inference.One approach to mitigate these problems is federated learning (FL), which enables the devices to traina common machine learning model without data sharing and transmission.

Keywords： Federated learning 6G Reconfigurable intelligent surface Semantic communication Sensing communication

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Federated mutual learning: a collaborative machine learning method for heterogeneous data, models, and Research Article

Tao SHEN, Jie ZHANG, Xinkang JIA, Fengda ZHANG, Zheqi LV, Kun KUANG, Chao WU, Fei WU,chao.wu@zju.edu.cn,wufei@zju.edu.cn

Frontiers of Information Technology & Electronic Engineering 2023, Volume 24, Issue 10, Pages 1390-1402 doi: 10.1631/FITEE.2300098

Abstract: (FL) is a novel technique in deep learning that enables clients to collaboratively train a shared modelFurthermore, we propose a novel framework called federated mutual learning (FML), which enables eachWe introduce a technique called deep mutual learning (DML) to transfer knowledge between these two modelsincludes only certain parts, and the personalized model is task-specific and enhanced through mutual learning

Keywords： Federated learning Knowledge distillation Privacy preserving Heterogeneous environment

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Edge preparation methods for cutting tools: a review

Frontiers of Mechanical Engineering 2023, Volume 18, Issue 4, doi: 10.1007/s11465-023-0766-y

Abstract: Edge preparation can remove cutting edge defects, such as burrs, chippings, and grinding marks, generatedVarious edge preparation methods have been proposed for different tool matrix materials, geometries,cutting edge with cutting performance, are briefly introduced.Then, edge preparation methods for cutting tools, in which materials at the cutting edge area are removedFinally, the future development direction of tool edge preparation technology is prospected.

Keywords： edge preparation method preparation principle cutting edge geometry edge characterization tool performance

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Structural design of morphing trailing edge actuated by SMA

Qi WANG, Zhiwei XU, Qian ZHU

Frontiers of Mechanical Engineering 2013, Volume 8, Issue 3, Pages 268-275 doi: 10.1007/s11465-013-0261-y

Abstract:

In this paper, the morphing trailing edge is designed to achieve the up and down deflection underlayout programs, a solid model is created in CATIA and the structures of the morphing wing trailing edgeand control system is designed to accomplish the controlling experiment of the morphing wing trailing edgeAt last, via the force analysis, the trailing edge is fabricated with four sections of aluminum alloyless than 4% and response time is less than 6.7 s, the precise controlling of the morphing trailing edge

Keywords： morphing wing trailing edge shape memory alloy digital signal processor PID algorithm

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Frequencies of circular plate with concentric ring and elastic edge support

Lokavarapu Bhaskara RAO,Chellapilla Kameswara RAO

Frontiers of Mechanical Engineering 2014, Volume 9, Issue 2, Pages 168-176 doi: 10.1007/s11465-014-0299-5

Abstract:

Exact solutions for the flexural vibrations of circular plates having elastic edge conditions along

Keywords： circular plate frequency elastic edge rigid ring mode switching

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Knife-edge technique for laser cooling

WANG Zhanshan, MA Shanshan, MA Yan, ZHAO Min, LIU Hengbiao

Frontiers of Mechanical Engineering 2007, Volume 2, Issue 4, Pages 468-473 doi: 10.1007/s11465-007-0081-z

Abstract: In the application of knife-edge technique, the temperature of atoms through laser cooling was measuredKnife-edge technique can measure the temperature of an atomic beam through laser cooling.

Keywords： knife-edge technique uniformity coupled transfer fluorescent

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Multi-agent deep reinforcement learning for end–edge orchestrated resource allocation in industrial wireless Research Article

Xiaoyu LIU, Chi XU, Haibin YU, Peng ZENG,liuxiaoyu1@sia.cn,xuchi@sia.cn,yhb@sia.cn,zp@sia.cn

Frontiers of Information Technology & Electronic Engineering 2022, Volume 23, Issue 1, Pages 47-60 doi: 10.1631/FITEE.2100331

Abstract: Edge artificial intelligence will empower the ever simple (IWNs) supporting complex and dynamic taskscollaboratively exploiting the computation and communication resources of both machine-type devices (MTDs) and edgeFirst, we present the system model of IWNs, wherein each MTD is regarded as a self-learning agent.To break the time correlation of training data while accelerating the learning process of MADRL-RA, we

Keywords： Multi-agent deep reinforcement learning End–edge orchestrated Industrial wireless networks Delay

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Real-time task processing method based on edge computing for spinning CPS

Shiyong YIN, Jinsong BAO, Jie LI, Jie ZHANG

Frontiers of Mechanical Engineering 2019, Volume 14, Issue 3, Pages 320-331 doi: 10.1007/s11465-019-0542-1

Abstract: This paper presents an edge computing-based method that is different from traditional centralized cloudEdge computing nodes, real-time tasks, and edge computing resources are defined.A system model is established, and a real-time task processing method is proposed for the edge computingExperimental results indicate that the proposed real-time task processing method based on edge computing

Keywords： edge computing real-time task scheduling CPS spinning

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Edge Computing Technology: Development and Countermeasures

Hong Xuehai and Wang Yang

Strategic Study of CAE 2018, Volume 20, Issue 2, Pages 20-26 doi: 10.15302/J-SSCAE-2018.02.004

Abstract:

Edge computing is an emerging technology that reduces transmission delaysbandwidth consumption by placing computing, storage, bandwidth, applications, and other resources on the edgeThis paper discusses the concept of edge computing, key problems that require solutions, main advancesin edge computing, influence of edge computing developments, and opportunities and development countermeasuresof edge calculation.

Keywords： cloud computing edge computing fog computing mobile edge computing internet of things front-end

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Tailoring electrical conductivity of two dimensional nanomaterials using plasma for edge electronics:

Aswathy Vasudevan, Vasyl Shvalya, Aleksander Zidanšek, Uroš Cvelbar

Frontiers of Chemical Science and Engineering 2019, Volume 13, Issue 3, Pages 427-443 doi: 10.1007/s11705-019-1805-4

Abstract: This review deals with recent advances in the modification of 2D carbon nanostructures for novel ‘edge

Keywords： graphene edge electronics 2D nanomaterials plasma electrical conductivity

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Cost-effective resource segmentation in hierarchical mobile edge clouds Special Feature on Future Network-Research Article

Ming-shuang JIN, Shuai GAO, Hong-bin LUO, Hong-ke ZHANG

Frontiers of Information Technology & Electronic Engineering 2019, Volume 20, Issue 9, Pages 1209-1220 doi: 10.1631/FITEE.1800203

Abstract: ., edge caching and edge computing) at the network edge.., cache placement strategy and vCPU provision strategy) for edge applications from the perspective of

Keywords： Edge clouds Edge computing Edge caching Resource segmentation Virtual machine (VM) allocation

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Title Author Date Type Operation

Training time minimization for federated edge learning with optimized gradient quantization and bandwidth

Peixi LIU, Jiamo JIANG, Guangxu ZHU, Lei CHENG, Wei JIANG, Wu LUO, Ying DU, Zhiqin WANG,jiangjiamo@caict.ac.cn,gxzhu@sribd.cn

Journal Article

Low-Cost Federated Broad Learning for Privacy-Preserved Knowledge Sharing in the RIS-Aided Internet of

Xiaoming Yuan,Jiahui Chen,Ning Zhang,Qiang Ye,Changle Li,Chunsheng Zhu,Xuemin Sherman Shen,

Journal Article

Incentive-Aware Blockchain-Assisted Intelligent Edge Caching and Computation Offloading for IoT

Qian Wang, Siguang Chen, Meng Wu

Journal Article

Federated unsupervised representation learning

Fengda ZHANG, Kun KUANG, Long CHEN, Zhaoyang YOU, Tao SHEN, Jun XIAO, Yin ZHANG, Chao WU, Fei WU, Yueting ZHUANG, Xiaolin LI,fdzhang@zju.edu.cn,kunkuang@zju.edu.cn

Journal Article

Federated Learning for 6G: Applications, Challenges, and Opportunities

Zhaohui Yang, Mingzhe Chen, Kai-Kit Wong, H. Vincent Poor, Shuguang Cui

Journal Article

Federated mutual learning: a collaborative machine learning method for heterogeneous data, models, and

Tao SHEN, Jie ZHANG, Xinkang JIA, Fengda ZHANG, Zheqi LV, Kun KUANG, Chao WU, Fei WU,chao.wu@zju.edu.cn,wufei@zju.edu.cn

Journal Article

Edge preparation methods for cutting tools: a review

Journal Article

Structural design of morphing trailing edge actuated by SMA

Qi WANG, Zhiwei XU, Qian ZHU

Journal Article