2023 IEEE Wireless Communications and Networking Conference (WCNC)最新文献_第4页

FIBFT: An Improved Byzantine Consensus Mechanism for Edge Computing 一种改进的边缘计算拜占庭共识机制

2023 IEEE Wireless Communications and Networking Conference (WCNC) Pub Date : 2023-03-01 DOI: 10.1109/WCNC55385.2023.10118628

Ningjie Gao, R. Huo, Shuo Wang, Tao Huang

{"title":"FIBFT: An Improved Byzantine Consensus Mechanism for Edge Computing","authors":"Ningjie Gao, R. Huo, Shuo Wang, Tao Huang","doi":"10.1109/WCNC55385.2023.10118628","DOIUrl":"https://doi.org/10.1109/WCNC55385.2023.10118628","url":null,"abstract":"Blockchain has been widely used to solve data privacy and security issues in edge computing scenarios. However, the blockchain based on edge computing still has some performance problems, such as insufficient scalability, difficulty in balancing security and edge device power consumption, and inability to simultaneously meet low latency, high throughput, high security and privacy issues, etc. In order to solve these problems, this paper proposes a generally improved Byzantine consensus mechanism based on the K-medoids clustering algorithm - FIBFT. Considering the different performance characteristics of each node in the network, the node’s state is first abstracted into a multi-dimensional state space containing eigenvalues, and then the nodes are divided into subnets by the efficient K-medoids clustering algorithm. Each subnet uses a Byzantine consensus mechanism based on arbitration for consensus and data interaction, and the consensus data could be exchanged between the subnets without interfering with the consensus process. The research results show that FIBFT has better scalability and throughput while ensuring high security compared with the traditional Byzantine consensus algorithm.","PeriodicalId":259116,"journal":{"name":"2023 IEEE Wireless Communications and Networking Conference (WCNC)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115404309","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Multi-Scale Feature Selection Framework for WiFi Access Points Line-of-sight Identification WiFi接入点视距识别的多尺度特征选择框架

2023 IEEE Wireless Communications and Networking Conference (WCNC) Pub Date : 2023-03-01 DOI: 10.1109/WCNC55385.2023.10118876

Xu Feng, Khuong An Nguyen, Zhiyuan Luo

引用次数: 0

Analysis of Over-the-Air Time Synchronization for Industrial LiFi Networks 工业LiFi网络空中时间同步分析

2023 IEEE Wireless Communications and Networking Conference (WCNC) Pub Date : 2023-03-01 DOI: 10.1109/WCNC55385.2023.10118779

Ahmet Burak Ozyurt, W. Popoola

引用次数: 0

Indoor Massive IoT Access Relying on Millimeter-Wave Extra-Large-Scale MIMO 基于毫米波超大规模MIMO的室内海量物联网接入

2023 IEEE Wireless Communications and Networking Conference (WCNC) Pub Date : 2023-03-01 DOI: 10.1109/WCNC55385.2023.10118760

Li Qiao, Anwen Liao, Zhen Gao, Hua Wang

引用次数: 1

LEO Mega-Constellations Routing Algorithm Based on Area Segmentation 基于区域分割的LEO大星座路由算法

2023 IEEE Wireless Communications and Networking Conference (WCNC) Pub Date : 2023-03-01 DOI: 10.1109/WCNC55385.2023.10118676

Rui Li, Jiaxin Zhang, Shuang Zheng, Kaiwei Wang, Peng Wang, Xing Zhang

{"title":"LEO Mega-Constellations Routing Algorithm Based on Area Segmentation","authors":"Rui Li, Jiaxin Zhang, Shuang Zheng, Kaiwei Wang, Peng Wang, Xing Zhang","doi":"10.1109/WCNC55385.2023.10118676","DOIUrl":"https://doi.org/10.1109/WCNC55385.2023.10118676","url":null,"abstract":"Low earth orbit (LEO) mega-constellations in future 6G have attracted the attention from both academia and industry. However, due to the high dynamic characteristic of the LEO satellite network topology and the limited on-board resources, existing approaches relying on high on-board processing capabilities and monitoring the global network state, result in intolerable packet loss rate and excessive signalling overhead. In this paper, a routing algorithm based on area segmentation for LEO mega-constellations is proposed according to the topological characteristics of the network. Specifically, we divide the LEO mega-constellations into multiple areas with four quadrant parts. In addition, the transmission cluster is defined consisted of two adjacent parts based on transmission direction. With the relative geographical location and transmission clusters, we joint intra-area and inter-area routing to realize multi-path routing and forwarding by periodically updating the link state, instead of globally calculating. Simulation results demonstrate that the proposed algorithm can achieve higher throughput, decrease the packet loss rate by 22% and reduce the signalling overhead significantly.","PeriodicalId":259116,"journal":{"name":"2023 IEEE Wireless Communications and Networking Conference (WCNC)","volume":"117 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124375250","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Dueling Double Deep Q-Network Based Computation Offloading and Resource Allocation Scheme for Internet of Vehicles 基于Dueling双深度q网络的车联网计算卸载与资源分配方案

2023 IEEE Wireless Communications and Networking Conference (WCNC) Pub Date : 2023-03-01 DOI: 10.1109/WCNC55385.2023.10118937

Fan Jiang, Y. Li, Changyin Sun, Chaowei Wang

{"title":"Dueling Double Deep Q-Network Based Computation Offloading and Resource Allocation Scheme for Internet of Vehicles","authors":"Fan Jiang, Y. Li, Changyin Sun, Chaowei Wang","doi":"10.1109/WCNC55385.2023.10118937","DOIUrl":"https://doi.org/10.1109/WCNC55385.2023.10118937","url":null,"abstract":"This paper investigates a computation offloading and resource allocation policy for multiple vehicle user equipments (VUEs) in the Internet of Vehicles (IoV). Aiming at balancing the delay and energy consumption during the offloading procedure, a Support Vector Machine (SVM) is initially adopted to classify the offloading tasks into two categories according to different delay and energy consumption requirements. Consequently, VUEs can choose to offload the tasks to the mobile edge computing (MEC) server or other VUEs for completion. In particular, to further decrease the task offloading time in the MEC processing mode, the non-orthogonal multiple access (NOMA) scheme is adopted, which makes it possible for the MEC server to serve two VUEs simultaneously on the same sub-channel. To minimize the total cost, a Dueling Double Deep Q-Network (D3QN) based resource allocation algorithm is proposed, which can allocate the corresponding radio or computing resources under different task processing modes. Simulation results demonstrate that the proposed scheme can effectively reduce the total offloading cost within the maximum delay tolerance compared with existing methods.","PeriodicalId":259116,"journal":{"name":"2023 IEEE Wireless Communications and Networking Conference (WCNC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124394413","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Delay-aware and Resource-efficient VNF placement in 6G Non-Terrestrial Networks 6G非地面网络中延迟感知和资源高效的VNF布局

2023 IEEE Wireless Communications and Networking Conference (WCNC) Pub Date : 2023-03-01 DOI: 10.1109/WCNC55385.2023.10118893

Yi Yue, Xiongyan Tang, W. Yang, Xuebei Zhang, Zhiyan Zhang, Chuyang Gao, Lexi Xu

{"title":"Delay-aware and Resource-efficient VNF placement in 6G Non-Terrestrial Networks","authors":"Yi Yue, Xiongyan Tang, W. Yang, Xuebei Zhang, Zhiyan Zhang, Chuyang Gao, Lexi Xu","doi":"10.1109/WCNC55385.2023.10118893","DOIUrl":"https://doi.org/10.1109/WCNC55385.2023.10118893","url":null,"abstract":"Virtual Network Function (VNF) placement in NTNs is challenging because Non-Terrestrial Networks (NTNs), such as satellite networks, have limited resources regarding computational power and rate. However, existing solutions do not consider satellites’ resource constraints and the bandwidth constraints of links, which are essential metrics for designing VNF placement strategies in NTNs. Utilizing Network Function Virtualization (NFV) technology to deploy related network services on satellites in VNFs is a reasonable way. This paper focuses on delay-aware VNF placement in 6G NTNs to meet the ultra-low delay requirements of different applications. In addition, we also consider how to improve the resource utilization of servers to eliminate the resource bottlenecks of resource-constrained 6G NTN facilities. Then we formulate the VNF placement problem as a weighted graph-matching problem, aiming to maximize resource utilization. We propose the Linear Programming based algorithm and the Hungarian-based algorithm to solve the VNF placement problem. Evaluation results show that our proposed solutions outperform the benchmarks regarding resource utilization and execution time.","PeriodicalId":259116,"journal":{"name":"2023 IEEE Wireless Communications and Networking Conference (WCNC)","volume":"361 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124541825","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Task-Oriented Semantic Communication Based on Semantic Triplets 基于语义三联体的面向任务的语义通信

2023 IEEE Wireless Communications and Networking Conference (WCNC) Pub Date : 2023-03-01 DOI: 10.1109/WCNC55385.2023.10118916

Chuanhong Liu, Caili Guo, Siyi Wang, Yuze Li, Dingxing Hu

引用次数: 0

Federated Learning based Hierarchical 3D Indoor Localization 基于联邦学习的分层三维室内定位

2023 IEEE Wireless Communications and Networking Conference (WCNC) Pub Date : 2023-03-01 DOI: 10.1109/WCNC55385.2023.10118848

Yaya Etiabi, Wafa Njima, El-Mehdi Amhoud

{"title":"Federated Learning based Hierarchical 3D Indoor Localization","authors":"Yaya Etiabi, Wafa Njima, El-Mehdi Amhoud","doi":"10.1109/WCNC55385.2023.10118848","DOIUrl":"https://doi.org/10.1109/WCNC55385.2023.10118848","url":null,"abstract":"The proliferation of connected devices in indoor environments opens the floor to a myriad of indoor applications with positioning services as key enablers. However, as privacy issues and resource constraints arise, it becomes more challenging to design accurate positioning systems as required by most applications. To overcome the latter challenges, we present in this paper, a federated learning (FL) framework for hierarchical 3D indoor localization using a deep neural network. Indeed, we firstly shed light on the prominence of exploiting the hierarchy between floors and buildings in a multi-building and multi-floor indoor environment. Then, we propose an FL framework to train the designed hierarchical model. The performance evaluation shows that by adopting a hierarchical learning scheme, we can improve the localization accuracy by up to 24.06% compared to the non-hierarchical approach. We also obtain a building and floor prediction accuracy of 99.90% and 94.87% respectively. With the proposed FL framework, we can achieve a near-performance characteristic as of the central training with an increase of only 7.69% in the localization error. Moreover, the conducted scalability study reveals that the FL system accuracy is improved when more devices join the training.","PeriodicalId":259116,"journal":{"name":"2023 IEEE Wireless Communications and Networking Conference (WCNC)","volume":"263 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114645725","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

Impact of UE Hardware Impairments on Uplink Spectral Efficiency of Cell-Free Massive MIMO Network 终端硬件缺陷对无小区大规模MIMO网络上行频谱效率的影响

2023 IEEE Wireless Communications and Networking Conference (WCNC) Pub Date : 2023-03-01 DOI: 10.1109/WCNC55385.2023.10118823

Ning Li, Pingzhi Fan

引用次数: 0