2021 IEEE Global Communications Conference (GLOBECOM)最新文献_第6页

In-Network Processing for Low-Latency Industrial Anomaly Detection in Softwarized Networks 软件网络中低延迟工业异常检测的网内处理

2021 IEEE Global Communications Conference (GLOBECOM) Pub Date : 2021-12-01 DOI: 10.1109/GLOBECOM46510.2021.9685489

Huanzhuo Wu, Jia He, Máté Tömösközi, Zuo Xiang, F. Fitzek

{"title":"In-Network Processing for Low-Latency Industrial Anomaly Detection in Softwarized Networks","authors":"Huanzhuo Wu, Jia He, Máté Tömösközi, Zuo Xiang, F. Fitzek","doi":"10.1109/GLOBECOM46510.2021.9685489","DOIUrl":"https://doi.org/10.1109/GLOBECOM46510.2021.9685489","url":null,"abstract":"Modern manufacturers are currently undertaking the integration of novel digital technologies - such as 5G-based wireless networks, the Internet of Things (IoT), and cloud computing - to elevate their production process to a brand new level, the level of smart factories. In the setting of a modern smart factory, time-critical applications are increasingly important to facilitate efficient and safe production. However, these applications suffer from delays in data transmission and processing due to the high density of wireless sensors and the large volumes of data that they generate. As the advent of next-generation networks has made network nodes intelligent and capable of handling multiple network functions, the increased computational power of the nodes makes it possible to offload some of the computational overhead. In this paper, we show for the first time our IA-Net-Lite industrial anomaly detection system with the novel capability of in-network data processing. IA-Net-Lite utilizes intelligent network devices to combine data transmission and processing, as well as to progressively filter redundant data in order to optimize service latency. By testing in a practical network emulator, we showed that the proposed approach can reduce the service latency by up to 40%. Moreover, the benefits of our approach could potentially be exploited in other large-volume and artificial intelligence applications.","PeriodicalId":200641,"journal":{"name":"2021 IEEE Global Communications Conference (GLOBECOM)","volume":"74 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116190196","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: 4

RIS-assisted Aerial Backhaul System for UAV-BSs: An Energy-efficiency Perspective UAV-BSs的ris辅助空中回程系统:能源效率的观点

2021 IEEE Global Communications Conference (GLOBECOM) Pub Date : 2021-12-01 DOI: 10.1109/GLOBECOM46510.2021.9685565

Hong-Bae Jeon, Sung-Ho Park, Jaedon Park, Kaibin Huang, C. Chae

{"title":"RIS-assisted Aerial Backhaul System for UAV-BSs: An Energy-efficiency Perspective","authors":"Hong-Bae Jeon, Sung-Ho Park, Jaedon Park, Kaibin Huang, C. Chae","doi":"10.1109/GLOBECOM46510.2021.9685565","DOIUrl":"https://doi.org/10.1109/GLOBECOM46510.2021.9685565","url":null,"abstract":"In this paper, we propose a novel wireless backhaul architecture, mounted on a high-altitude aerial platform, which is enabled by reconfigurable intelligent surface (RIS). We assume a sudden increase in traffic in an urban area, and to serve the ground users therein, authorities rapidly deploy unmanned-aerial-vehicle base-stations (UAV-BSs). In this scenario, since the direct backhaul link from the ground source can be blocked due to several obstacles from the urban area, we propose reflecting the backhaul signal using aerial-RIS and the phase of each RIS element, which leads to an increase in energy-efficiency ensuring the reliable backhaul link for every UAV-BS. We optimize the placement and array-partitioning strategy of aerial-RIS and the phase of each RIS element, which leads to an increase of energy-efficiency under guaranteeing the reliable backhaul link for every UAV-BS. We show that the complexity of our algorithm is upper-bounded by the quadratic order, thus implying high computational efficiency. We verify the performance of the proposed algorithm via extensive numerical evaluations and show that our method achieves an outstanding performance in terms of energy-efficiency compared to benchmark schemes.","PeriodicalId":200641,"journal":{"name":"2021 IEEE Global Communications Conference (GLOBECOM)","volume":"136 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116318401","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: 6

Uplink Data Transmission Based on Collaborative Beamforming in UAV-assisted MWSNs 基于协同波束形成的无人机辅助MWSNs上行数据传输

2021 IEEE Global Communications Conference (GLOBECOM) Pub Date : 2021-12-01 DOI: 10.1109/GLOBECOM46510.2021.9685853

Aimin Wang, Yuxin Wang, Geng Sun, Jiahui Li, Shuang Liang, Yanheng Liu

{"title":"Uplink Data Transmission Based on Collaborative Beamforming in UAV-assisted MWSNs","authors":"Aimin Wang, Yuxin Wang, Geng Sun, Jiahui Li, Shuang Liang, Yanheng Liu","doi":"10.1109/GLOBECOM46510.2021.9685853","DOIUrl":"https://doi.org/10.1109/GLOBECOM46510.2021.9685853","url":null,"abstract":"Unmanned aerial vehicles (UAVs) have attracted growing attention in enhancing the performance of mobile wireless sensor networks (MWSNs) since they can act as the aerial base stations (ABSs) and have the autonomous nature to collect data. In this paper, we consider to construct a virtual antenna array (VAA) consists of mobile sensor nodes (MSNs) and adopt the collaborative beamforming (CB) to achieve the long-distance and efficient uplink data transmissions with the ABSs. First, we formulate a high data transmission rate multi-objective optimization problem (HDTRMOP) of the CB-based UAV-assisted MWSN to simultaneously improve the total transmission rates, suppress the total maximum sidelobe levels (SLLs) and reduce the total motion energy consumptions of MSNs by jointly optimizing the positions and excitation current weights of MSN-enabled VAA, and the order of communicating with different ABSs. Then, we propose an improved non-dominated sorting genetic algorithm-III (INSGA-III) with chaos initialization, average grade mechanism and hybrid-solution generate strategy to solve the problem. Simulation results verify that the proposed algorithm can effectively solve the formulated HDTRMOP and it has better performance than some other benchmark methods.","PeriodicalId":200641,"journal":{"name":"2021 IEEE Global Communications Conference (GLOBECOM)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116512518","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: 2

Slider: Towards Precise, Robust and Updatable Sketch-based DDoS Flooding Attack Detection 滑块:朝着精确，稳健和可更新的基于草图的DDoS洪水攻击检测

2021 IEEE Global Communications Conference (GLOBECOM) Pub Date : 2021-12-01 DOI: 10.1109/GLOBECOM46510.2021.9685622

Xin Cheng, Zhiliang Wang, Shize Zhang, Jia Li, Jiahai Yang, Xinran Liu

引用次数: 2

Honeypot-Enabled Optimal Defense Strategy Selection for Smart Grids 基于蜜罐的智能电网最佳防御策略选择

2021 IEEE Global Communications Conference (GLOBECOM) Pub Date : 2021-12-01 DOI: 10.1109/GLOBECOM46510.2021.9685397

Beibei Li, Yaxin Shi, Qinglei Kong, Chao Zhai, Yuankai Ouyang

引用次数: 0

Photonic sensors for non-invasive home monitoring of elders 用于老年人无创家庭监测的光子传感器

2021 IEEE Global Communications Conference (GLOBECOM) Pub Date : 2021-12-01 DOI: 10.1109/GLOBECOM46510.2021.9685192

A. Nepomuceno, P. Antunes, N. Alberto, P. André, H. Chi, A. Radwan, M. F. Domingues

引用次数: 0

Cloud-Edge Collaboration with Green Scheduling and Deep Learning for Industrial Internet of Things 面向工业物联网的云边缘协同绿色调度和深度学习

2021 IEEE Global Communications Conference (GLOBECOM) Pub Date : 2021-12-01 DOI: 10.1109/GLOBECOM46510.2021.9685966

Y. Cui, Heli Zhang, Hong Ji, Xi Li, Xun Shao

{"title":"Cloud-Edge Collaboration with Green Scheduling and Deep Learning for Industrial Internet of Things","authors":"Y. Cui, Heli Zhang, Hong Ji, Xi Li, Xun Shao","doi":"10.1109/GLOBECOM46510.2021.9685966","DOIUrl":"https://doi.org/10.1109/GLOBECOM46510.2021.9685966","url":null,"abstract":"As a key technology of the sixth generation (6G), cloud-edge collaboration has attracted attention in the industrial Internet of Things (IIoT). However, the delay-sensitive and resource-intensive intelligent services in IIoT not only require a large number of computing resources to reduce the delay cost and energy consumption of devices but also require fast and accurate intelligent decisions to avoid service congestion. In this paper, we design an offloading scheme based on cloud-edge collaboration and edge collaboration, including four computing modes, which jointly consider the delay and energy optimization of devices. We propose a parallel deep learning-driven cooperative offloading (PDCO) algorithm, which weighs the real-time and accuracy of offloading scheme. To deal with the difficulty of obtaining labels, a low-complexity hybrid label processing method is designed to reduce the cost of labeling data, and then multiple parallel deep neural networks (DNNs) are trained to generate the best offloading decision timely. Simulation results show that the proposed algorithm can generate offloading decisions with more than 90% accuracy in 0.1s while considering green scheduling.","PeriodicalId":200641,"journal":{"name":"2021 IEEE Global Communications Conference (GLOBECOM)","volume":"81 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124534273","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: 2

Non-parametric Decision-Making by Bayesian Attractor Model for Dynamic Slice Selection 基于贝叶斯吸引子模型的非参数动态切片选择决策

2021 IEEE Global Communications Conference (GLOBECOM) Pub Date : 2021-12-01 DOI: 10.1109/GLOBECOM46510.2021.9685972

Tatsuya Otoshi, S. Arakawa, M. Murata, T. Hosomi

{"title":"Non-parametric Decision-Making by Bayesian Attractor Model for Dynamic Slice Selection","authors":"Tatsuya Otoshi, S. Arakawa, M. Murata, T. Hosomi","doi":"10.1109/GLOBECOM46510.2021.9685972","DOIUrl":"https://doi.org/10.1109/GLOBECOM46510.2021.9685972","url":null,"abstract":"In 5G, the network is divided into slices to provide communications with different characteristics, such as low latency and reliable communications (URRLC), multiple connections (MTC), and high speed and high capacity communications (eMBB), for different applications. Although the selection of network slices is often static, in practice, dynamic slice selection is required depending on the application situation. However, there are issues such as the slice change itself changing the application situation and the delay associated with the slice change. In this paper, we realize dynamic slice selection by recognizing the rough situation and the mapping between the recognized situation and the slice. The Bayesian Attractor Model (BAM) is used for recognition to achieve consistent recognition and is extended to the Dirichlet Process Mixture Model (DPMM) to achieve automatic attractor construction. The mapping between situations and slices is also automatically learned by using feedback. As an application of dynamic slice selection, we also show slice selection based on the video streaming situation. Through numerical examples, we show that our method can keep the quality of video streaming high while reducing slice changes.","PeriodicalId":200641,"journal":{"name":"2021 IEEE Global Communications Conference (GLOBECOM)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127784624","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: 2

Deep Reinforcement Learning for URLLC in 5G Mission-Critical Cloud Robotic Application 5G关键任务云机器人应用中URLLC的深度强化学习

2021 IEEE Global Communications Conference (GLOBECOM) Pub Date : 2021-12-01 DOI: 10.1109/GLOBECOM46510.2021.9685978

T. Ho, T. Nguyen, K. Nguyen, M. Cheriet

引用次数: 3

Blockchain and FL-based Network Resource Management for Interactive Immersive Services 基于区块链和fl的交互式沉浸式服务网络资源管理

2021 IEEE Global Communications Conference (GLOBECOM) Pub Date : 2021-12-01 DOI: 10.1109/GLOBECOM46510.2021.9685091

M. Aloqaily, Ouns Bouachir, I. A. Ridhawi

{"title":"Blockchain and FL-based Network Resource Management for Interactive Immersive Services","authors":"M. Aloqaily, Ouns Bouachir, I. A. Ridhawi","doi":"10.1109/GLOBECOM46510.2021.9685091","DOIUrl":"https://doi.org/10.1109/GLOBECOM46510.2021.9685091","url":null,"abstract":"Advanced services leveraged for future smart cities have played a significant role in the advancement of 5G networks towards the 6G vision. Interactive immersive applications are an example of those enabled services. Such applications allow for the interaction between multiple users in a 3D environment created by virtual presentations of real objects and participants using various technologies such as Virtual Reality (VR), Augmented Reality (AR), Extended Reality (XR), Digital Twin (DT) and holography. These applications require advanced computing models which allow for the processing of massive gathered amounts of data. Motions, gestures and object modification should be captured, added to the virtual environment, and shared with all the participants. Relying only on the cloud to process this data can cause significant delays. Therefore, a hybrid cloud/edge architecturewith an intelligent resource orchestration mechanism, that is able to allocate the available capacities efficiently is necessary. In this paper, a blockchain and federated learning-enabled predicted edge-resource allocation (FLP-RA) algorithm is introduced to manage the allocation of computing resources in B5G networks. It allows for smart edge nodes to train their local data and share it with other nodes to create a global estimation of future network loads. As such, nodes are able to make accurate decisions to distribute the available resources to provide the lowest computing delay.","PeriodicalId":200641,"journal":{"name":"2021 IEEE Global Communications Conference (GLOBECOM)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125795153","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: 8