dblp: Collaborative Computing 2023 - Part III (original) (raw)

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19th CollaborateCom 2023: Corfu Island, Greece - Part III

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  • Onsite Session Day 2
  • Federated Learning and Application
  • Collaborative Working
  • Edge Computing
  • Prediction, Optimization and Applications

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    Honghao Gao, Xinheng Wang, Nikolaos S. Voros:
    Collaborative Computing: Networking, Applications and Worksharing - 19th EAI International Conference, CollaborateCom 2023, Corfu Island, Greece, October 4-6, 2023, Proceedings, Part III. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 563, Springer 2024, ISBN 978-3-031-54530-6

Onsite Session Day 2

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    Peisong Li, Ziren Xiao, Xinheng Wang, Kaizhu Huang, Yi Huang, Andrei Tchernykh:
    Multi-agent Reinforcement Learning Based Collaborative Multi-task Scheduling for Vehicular Edge Computing. 3-22
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    Zhenchao Ouyang, Jiahe Cui, Yunxiang He, Dongyu Li, Qinglei Hu, Changjie Zhang:
    A Novel Topology Metric for Indoor Point Cloud SLAM Based on Plane Detection Optimization. 23-40
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    Godwin Idoje, Tasos Dagiuklas, Muddesar Iqbal:
    On the Performance of Federated Learning Network. 41-56

Federated Learning and Application

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    Yan Zeng, Hui Zheng, Xin Wang, Beibei Zhang, Mingyao Zhou, Jilin Zhang, Yongjian Ren:
    FedECCR: Federated Learning Method with Encoding Comparison and Classification Rectification. 59-78
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    Dun Cao, Jiasi Xiong, Nanfang Lei, Robert Simon Sherratt, Jin Wang:
    CSA_FedVeh: Cluster-Based Semi-asynchronous Federated Learning Framework for Internet of Vehicles. 79-99
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    Junfeng Hao, Juan Chen, Peng Chen, Yang Wang, Xianhua Niu, Lei Xu, Yunni Xia:
    Efficiently Detecting Anomalies in IoT: A Novel Multi-Task Federated Learning Method. 100-117
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    Zhaobin Ouyang, Yunni Xia, Qinglan Peng, Yin Li, Peng Chen, Xu Wang:
    A Novel Deep Federated Learning-Based and Profit-Driven Service Caching Method. 118-133
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    Zhongqin Bi, Yutang Duan, Weina Zhang, Meijing Shan:
    A Multi-behavior Recommendation Algorithm Based on Personalized Federated Learning. 134-153
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    Lamir Shkurti, Mennan Selimi, Adrian Besimi:
    FederatedMesh: Collaborative Federated Learning for Medical Data Sharing in Mesh Networks. 154-169

Collaborative Working

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    Chaonong Xu, Yujie Jiang:
    Enhance Broadcasting Throughput by Associating Network Coding with UAVs Relays Deployment in Emergency Communications. 173-190
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    Linxin Guo, Shiqi Wang, Min Gao, Chongming Gao:
    Dynamic Target User Selection Model for Market Promotion with Multiple Stakeholders. 191-207
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    Xiangpei Yan, Xiao Xue, Chao Peng, Donghua Liu, Zhiyong Feng, Xiao Wang:
    Collaborative Decision-Making Processes Analysis of Service Ecosystem: A Case Study of Academic Ecosystem Involution. 208-228
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    Robin Kraft, Maximilian Blasi, Marc Schickler, Manfred Reichert, Rüdiger Pryss:
    Operationalizing the Use of Sensor Data in Mobile Crowdsensing: A Systematic Review and Practical Guidelines. 229-248
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    Myriel Fichtner, Sascha Sucker, Dominik Riedelbauch, Stefan Jablonski, Dominik Henrich:
    Enriching Process Models with Relevant Process Details for Flexible Human-Robot Teaming. 249-269

Edge Computing

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    Lei Shi, Rui Ji, Zhen Wei, Shilong Feng, Zhehao Li:
    Joint Optimization of PAoI and Queue Backlog with Energy Constraints in LoRa Gateway Systems. 273-290
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    Cairong Yan, Yiwei Zhang, Xiangyang Feng, Yanglan Gan:
    Enhancing Session-Based Recommendation with Multi-granularity User Interest-Aware Graph Neural Networks. 291-307
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    Junyi Xu, Zhenchun Wei, Xiaohui Yuan, Zengwei Lyu, Lin Feng, Jianghong Han:
    Delay-Constrained Multicast Throughput Maximization in MEC Networks for High-Speed Railways. 308-328
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    Qi Yu, Weilong Ding, Maoxiang Sun, Jihai Huang:
    An Evolving Transformer Network Based on Hybrid Dilated Convolution for Traffic Flow Prediction. 329-343

Prediction, Optimization and Applications

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    Dingkang Han, Yujia Zhu, Liang Jiao, Dikai Mo, Yong Sun, Yuedong Zhang, Qingyun Liu:
    DualDNSMiner: A Dual-Stack Resolver Discovery Method Based on Alias Resolution. 347-364
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    Ruiqi Liu, Min Gao, Yujiang Wu, Jie Zeng, Jia Zhang, Jinyong Gao:
    DT-MUSA: Dual Transfer Driven Multi-source Domain Adaptation for WEEE Reverse Logistics Return Prediction. 365-384
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    Yanguo Zeng, Meiting Xue, Peiran Xu, Yukun Shi, Kaisheng Zeng, Jilin Zhang, Lupeng Yue:
    A Synchronous Parallel Method with Parameters Communication Prediction for Distributed Machine Learning. 385-403

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