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7th international conference on grid and cooperative computing, GCC 2008

ISBN: (纸本)9780769534497

the proceedings contain 112 papers. the topics discussed include: DDgrid: grid computing environment with massive concurrency and fault-tolerance support;a layered context reference model for context/situation middleware;grid memory service architecture for high performance computing;providing virtualization-based single system image on clusters;solution of large scale matrix inversion on cluster and grid;parallel data mining on multicore clusters;a novel self-adaptive casting net-based particle swarm optimization;2C: a new approach to design the second level Buffer Cache;implementation of virtual dynamic personal cluster;research and design of a parallel debugging interface in a new parallel debugger framework;study on problem-oriented model for spatial analysis parsing in grid environment;and a modified ant colony system for the selection of machining parameters.

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Special section: Selected papers from the 7th IEEE/ACM international conference on grid computing (grid2006)

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FUTURE GENERATION COMPUTER SYSTEMS-thE international JOURNAL OF grid computing thEORY MEthODS AND APPLICATIONS 2008年第5期24卷 402-403页

作者： Badia, Rosa M. Gannon, Dennis Lee, Craig Barcelona Supercomp Ctr Barcelona 08034 Spain Indiana Univ Dept Comp Sci Bloomington IN 47405 USA Aerosp Corp El Segundo CA 90245 USA

the highlights of the 7th IEEE/ACM international conference on grid computing held in Barcelona on September 28-29, 2006 were presented. the program for this conference covered all areas of grid computing research, which include Internet-based computing models, applications, including eScience and eBusiness applications, middleware and toolkits, and virtual Instrumentation. One of the paper presented an approach to grid scheduling that focused in the global cost optimization problem rather than in the details of individual applications taking into account the entire workload and dynamically adjusting to the varying service demands. Another contribution presented the design of a desktop grid implemented over a modified Peer-to-Peer architecture. Another paper summarized ongoing research and recent results on the development of flexible access control infrastructure for complex resource provisioning in grid-based collaborative applications and on-demand network services provisioning.

关键词： grid computing

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Robust Multi-agent Federated Reinforcement Learning for Task Offloading 7th

Robust Multi-agent Federated Reinforcement Learning for Task...

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7th international conference on Wireless Communications, Networking and Applications, WCNA 2023

作者： Yan, Dibao Wang, Yongfeng Hou, Wenjing Song, Huanhuan Wen, Hong Ma, Wendi Sun, Fan School of Aeronautics and Astronautics University of Electronic Science and Technology of China Chengdu611731 China Aircraft Swarm Intelligent Sensing and Cooperative Control Key Laboratory of Sichuan Province Chengdu611731 China Sichuan Intelligent IoT Communication Technology Engineering Research Center UESTC Chengdu China

ISBN: (纸本)9789819624089

With the proliferation of various mobile smart devices, edge computing and computational offloading technologies have emerged as pivotal support mechanisms, enhancing the service quality of these devices. To facilitate the learning of task offloading strategies across diverse and complex scenarios, this study introduces a federated learning strategy algorithm based on multi-agent deep reinforcement learning. this algorithm aims to aggregate the training strategies of multiple edge computing devices, thereby enabling the synthesis of superior task offloading strategies tailored to a wide array of environments while also providing safeguards against malicious nodes. this paper specifically examines the reward inversion attack, illustrating the algorithm’s capability to identify and counteract such malicious threats effectively. Experimental results validate that the proposed algorithm not only robustly defends against these attacks but also adeptly learns the task offloading strategies pertinent to each node. © the Author(s) 2025.

关键词： Federated learning

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Edge computing-Driven Optimization of Electricity Consumption Information Collection 24

Edge Computing-Driven Optimization of Electricity Consumptio...

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Proceedings of the 7th international conference on Information Technologies and Electrical Engineering

作者： Jingting Lei Lijun Wang Min Zhang Marketing Department of State Grid Shaanxi Electric Power Co. Ltd. Xian Shaanxi China State Grid Shaanxi Electric Power Co. Ltd. Weinan Power Supply Company Weinan Shaanxi China State Grid Xian Power Supply Company Electricity Metering Center Xian Shaanxi China

ISBN: (纸本)9798400707087

As the scale of the power system enlarges, the current system of collecting power consumption information has the disadvantages of delays in transmitting information, excessive bandwidth pressure, and the lack of real-time information processing capability. In order to alleviate the aforementioned issues, this paper provides an edge computing method to enhance the system of collecting power consumption information. the edge computing concept is to execute the preprocessing, analysis, and decision-making functions of the data near the source end at the edge nodes to decrease the center server load and enhance the real-time nature and reliability of the system. this paper initiates the explanation of the use cases of edge computing to collect power consumption information and verifies the optimization strategies of edge computing through specific examples. In practical use cases, edge nodes execute functions such as anomaly detection of power consumption and fault alarms through real-time monitoring and analysis of the information, significantly decreasing the amount of transmitted information and the system's response time. the results prove that the edge computing optimization strategy has superior performance in the efficiency of transmitting information, the ability to process real-time information, and system stability, providing a new technical means to the intelligence and efficiency of the system of collecting power consumption information.

关键词： Anomaly Detection

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Proceedings of the 7th IEEE/ACM international conference on grid computing, grid 2006

Proceedings of the 7th IEEE/ACM International Conference on ...

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7th IEEE/ACM international conference on grid computing, grid 2006

ISBN: (纸本)1424403448

the proceedings contain 49 papers. the topics discussed include: QoS-constrained stochastic workflow scheduling in enterprise and scientific grids;resource discovery techniques in distributed desktop grid environments;overhead analysis of grid workflow applications;workflow global computing with YML;run-time optimization of grid workflow applications;a gridFTP overlay network service;YA: fast and scalable discovery of idle CPUs in a P2P network;fault-aware scheduling for bag-of-tasks applications on desktop grids;QoS support for workflows in a volatile grid;using workflow for dynamic security context management in grid-based applications;flexible and secure logging of grid data access;multi-replication with intelligent staging in data-intensive grid applications;a QoS-aware heuristic algorithm for replica replacement;and operating system support for space application in grid storage systems.

关键词： Semantics

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Proceedings - 2012 7th international conference on P2P, Parallel, grid, Cloud and Internet computing, 3PGCIC 2012

Proceedings - 2012 7th International Conference on P2P, Para...

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2012 7th international conference on P2P, Parallel, grid, Cloud and Internet computing, 3PGCIC 2012

the proceedings contain 58 papers. the topics discussed include: load balancing optimization using the algorithm DEPRO in a distributed environment;modeling resource prices in grid markets;MIP model scheduling for BSP parallel applications on multi-cluster environments;analysis of the BitTorrent protocol modified with fountain code;data replication in P2P collaborative systems;large-scale mining of co-occurrences: challenges and solutions;implementing hadoop platform on eucalyptus cloud infrastructure;a data reception method to reduce interruption time for model and motion separated data in P2P streaming environments;distributed systems in the wild: the theoretical foundations and experimental perspectives;parallel perspectives: reverse engineering for generation multi-X;parallel enhanced hybrid evolutionary algorithm for continuous function optimization;and analysis of the BitTorrent protocol modified with multicast.

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PDGC 2022 - 2022 7th international conference on Parallel, Distributed and grid computing

PDGC 2022 - 2022 7th International Conference on Parallel, D...

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7th international conference on Parallel, Distributed and grid computing, PDGC 2022

ISBN: (纸本)9781665454018

the proceedings contain 136 papers. the topics discussed include: a survey paper on computer aided detection of tuberculosis;sentiment analysis approaches, types, challenges, and applications: an exploratory analysis;enigmas in emotion detection techniques tools: challenges and concerns;analysis of apple plant leaf diseases detection and classification: a review;does metaverse a technological revolution in artificial intelligence? a bibliometric analysis;credit card fraud detection using machine learning, deep learning, and ensemble of the both;machine learning based data classification methods in cloud security using cloudlightning framework;parallel chaos hash based LSB steganography technique using logistic map;a review on sentiment analysis of twitter data for diabetes classification and prediction;an analysis of deep learning models for detection of COVID-19 diseases;and engagement measurement of a learner during e-learning: a deep learning architecture.

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Research on Intelligent Scheduling and Optimization Algorithm of Mobile Nursing 24

Research on Intelligent Scheduling and Optimization Algorith...

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Proceedings of the 7th international conference on Information Technologies and Electrical Engineering

作者： Hong Chang Hong Tian Shenbo Xuan Jindi Wang Ying Feng State Grid Beijing Electric Power Hospital Information Center Beijing China State Grid Information & Telecommunication Co. Ltd. Beijing Branch Beijing China

ISBN: (纸本)9798400707087

this study conducted an in-depth discussion on the intelligent scheduling and optimization algorithm of mobile nursing. By constructing an optimization model for cost minimization and resource maximization utilization, combined with heuristic algorithms, the scheduling efficiency and resource utilization were significantly improved. Specifically, through strategies such as parameter tuning, heuristic improvement, and parallel computing, the optimized algorithm performs well in key indicators such as cost control, resource consumption, and task completion time. Experimental results show that the optimized algorithm can maintain good performance under different task loads, especially under high load conditions. through real data set testing, the robustness and broad applicability of the algorithm are verified. this research not only improves the efficiency of the mobile nursing system and provides solid technical support for practical applications, but also provides valuable theoretical foundation and practical experience for the further optimization and application of intelligent scheduling algorithms.

关键词： Intelligent Scheduling

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Research on Adaptive Segmentation and Collaborative computing of Edge Intelligence Model in Power Edge Gateway 24

Research on Adaptive Segmentation and Collaborative Computin...

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Proceedings of the 7th international conference on Information Technologies and Electrical Engineering

作者： Wei Zhang Peng Wang Zenghai Wang Jie Yang Feng Jiao Liguo Liu State Grid Information & Telecommunication Co. Ltd. Beijing Branch Beijng China

ISBN: (纸本)9798400707087

this paper proposes an edge intelligence model adaptive segmentation and collaborative computing method for power edge gateways to improve computing efficiency and resource utilization. First, an adaptive segmentation algorithm is studied and designed to effectively optimize the computational overhead and delay by adjusting the segmentation strategy of the model in real time. Next, the design of the collaborative computing framework realizes efficient data interaction between edge nodes, and uses advanced data exchange protocols to improve the reliability and speed of communication between nodes. through empirical analysis, it has been verified that the model has significant performance improvements in application scenarios such as real-time fault detection, load forecasting, and smart meter reading analysis. Compared with traditional methods, the performance improvement rate reaches more than 20%. Experimental results show that the model proposed in this paper has high computational efficiency, resource utilization and task response capabilities, and can adapt to diverse power system application requirements. In summary, this article provides theoretical and practical support for the application of edge intelligence in power gateways and verifies its effectiveness in practical application scenarios.

关键词： Adaptive Segmentation

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Research on Distribution Network Load Classification and Identification Technology Based on Edge computing 24

Research on Distribution Network Load Classification and Ide...

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Proceedings of the 7th international conference on Information Technologies and Electrical Engineering

作者： Yuankun Jiang Wei Zhang Yuan Liu Liguo Liu Xuehua Li Chenjie Yang State Grid Information & Telecommunication Co. Ltd. Beijing Branch Beijng China SGIT-UNI (QINGDAO) CLOUD DATA TECHNOLOGY CO. LTD. Beijng China

ISBN: (纸本)9798400707087

In response to the needs of distribution network load classification and identification, this study proposes an efficient classification method based on edge computing, aiming to solve the problem of high real-time and accuracy requirements in the power system. through in-depth analysis of the application potential of edge computing in power systems, a lightweight neural network model was designed and optimized through the momentum gradient descent method, which significantly improved the model's convergence speed and computational efficiency. In the experimental verification, through field testing in multiple scenarios, the results showed that the method performed well in terms of classification accuracy, latency and resource utilization, especially in the classification of residential, commercial and industrial loads, showing high accuracy and Lower processing latency. In addition, through in-depth analysis of actual application cases, this study further proves the wide applicability and application value of edge computing in power load classification. the results of this research provide a new technical path for the optimization and management of power systems, and lay a theoretical and practical foundation for the development of future smart grids.

关键词： Distribution Network

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