GLOBECOM 2022 - 2022 IEEE Global Communications Conference最新文献_第5页

Optimization of Clustering Strategy and Resource Allocation for Clustered Federated Learning 聚类联邦学习的聚类策略优化与资源分配

GLOBECOM 2022 - 2022 IEEE Global Communications Conference Pub Date : 2022-12-04 DOI: 10.1109/GLOBECOM48099.2022.10001540

Wenchao Xia, Bo Xu, Haitao Zhao, Yongxu Zhu, Xinghua Sun, Tony Q. S. Quek

{"title":"Optimization of Clustering Strategy and Resource Allocation for Clustered Federated Learning","authors":"Wenchao Xia, Bo Xu, Haitao Zhao, Yongxu Zhu, Xinghua Sun, Tony Q. S. Quek","doi":"10.1109/GLOBECOM48099.2022.10001540","DOIUrl":"https://doi.org/10.1109/GLOBECOM48099.2022.10001540","url":null,"abstract":"Federated learning (FL) framework enables user devices collaboratively train a global model based on their local datasets without privacy leak. However, the training performance of FL is degraded when the data distributions of different devices are incongruent. Fueled by this issue, we consider a clustered FL (CFL) method where the devices are divided into several clusters according to their data distributions and are trained simultaneously. Convergence analysis is conducted, which shows that the clustered model performance depends on cosine similarity, device number per cluster, and device participation probability. Then, aiming at optimizing the model training performance, a joint problem of resource allocation and device clustering is formulated, which is solved by decoupling it into two sub-problems. Specifically, a coalition formation algorithm is proposed for the device clustering sub-problem, and the sub-problem of bandwidth allocation and transmit power control is solved directly due to its convexity. Finally, simulation experiments are conducted on the MNIST dataset to validate the performance of the proposed algorithm in terms of test accuracy.","PeriodicalId":313199,"journal":{"name":"GLOBECOM 2022 - 2022 IEEE Global Communications Conference","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129216426","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

Towards Resource-aware DNN Partitioning for Edge Devices with Heterogeneous Resources 基于资源感知的异构边缘设备DNN分区研究

GLOBECOM 2022 - 2022 IEEE Global Communications Conference Pub Date : 2022-12-04 DOI: 10.1109/GLOBECOM48099.2022.10000839

Muhammad Zawish, L. Abraham, K. Dev, Steven Davy

{"title":"Towards Resource-aware DNN Partitioning for Edge Devices with Heterogeneous Resources","authors":"Muhammad Zawish, L. Abraham, K. Dev, Steven Davy","doi":"10.1109/GLOBECOM48099.2022.10000839","DOIUrl":"https://doi.org/10.1109/GLOBECOM48099.2022.10000839","url":null,"abstract":"Collaborative deep neural network (DNN) inference over edge and cloud is emerging as an effective approach for enabling several Internet of Things (IoT) applications. Edge devices are mainly resource-constrained and hence can not afford the computational complexity manifested by DNNs. Thereby, researchers have resorted to a collaborative computing approach, where a DNN is partitioned between edge and cloud. Recent art on DNN partitioning has either focused on bandwidth-specific partitioning or relied on offline benchmarking of DNN layers. However, edge devices are inherently heterogeneous and possess inconsistent levels and types of resources. Therefore, in this work, we propose a resource-aware partitioning of DNNs for accelerating collaborative inference over edge-cloud. The proposed approach provides the flexibility of partitioning a DNN with respect to the available nature and scale of resources for a certain edge device. Unlike state-of-the-art, we exploit different types of DNN complexities for partitioning them on heterogeneous edge devices. For example, in a bandwidth-constrained scenario, our approach gained 40% efficiency as compared to the offline benchmarking approach. Therefore, given the different nature of edge devices' computational, storage, and energy requirements, this approach provides a suitable configuration for edge-cloud synergetic inference.","PeriodicalId":313199,"journal":{"name":"GLOBECOM 2022 - 2022 IEEE Global Communications Conference","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123951784","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 Novel Intrusion Detection System for Next Generation In-Vehicle Networks 一种新的下一代车载网络入侵检测系统

GLOBECOM 2022 - 2022 IEEE Global Communications Conference Pub Date : 2022-12-04 DOI: 10.1109/GLOBECOM48099.2022.10000766

Zhouyan Deng, Yijie Xun, Jiajia Liu, Shouqing Li, Yilin Zhao

{"title":"A Novel Intrusion Detection System for Next Generation In-Vehicle Networks","authors":"Zhouyan Deng, Yijie Xun, Jiajia Liu, Shouqing Li, Yilin Zhao","doi":"10.1109/GLOBECOM48099.2022.10000766","DOIUrl":"https://doi.org/10.1109/GLOBECOM48099.2022.10000766","url":null,"abstract":"As emerging technologies such as mobile communication, vehicle to everything, and artificial intelligence are widely used in intelligent connected vehicles, drivers can gain a convenient and colorful driving experience. While these tech-nologies enrich the driving experience, they also bring a series of vulnerable interfaces to the vehicle. These interfaces can be used by hackers to attack other nodes of in-vehicle network that lack authentication and encryption. For this, researchers design scheme to encrypt and authenticate messages to protect in-vehicle networks, but this scheme would occupy the bandwidth resources of in-vehicle network. Therefore, researchers propose parameter monitoring-based intrusion detection system (IDS), information theory-based IDS, and fingerprint-based IDS, which do not occupy bandwidth. However, most IDSs either cannot locate the source of the attack, cannot detect aperiodic frames, or need to know the non-public mapping between electronic control units (ECUs) and identifiers (IDs) of in-vehicle network. To solve these weaknesses, we propose a novel IDS that establishes voltage fingerprints for each ID. This system can detect period and aperiodic malicious frames and locate the source of attack without knowing the mapping between ECUs and IDs. The experimental results on actual vehicles demonstrate that our scheme is robust against real scenarios.","PeriodicalId":313199,"journal":{"name":"GLOBECOM 2022 - 2022 IEEE Global Communications Conference","volume":"104 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124177772","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

Cost-Effective and Deployment-Friendly L4 Load Balancers Based on Programmable Switches 基于可编程交换机的经济高效且易于部署的L4负载均衡器

GLOBECOM 2022 - 2022 IEEE Global Communications Conference Pub Date : 2022-12-04 DOI: 10.1109/GLOBECOM48099.2022.10001588

Dong Zhou, Shuo Wang, Tao Huang

{"title":"Cost-Effective and Deployment-Friendly L4 Load Balancers Based on Programmable Switches","authors":"Dong Zhou, Shuo Wang, Tao Huang","doi":"10.1109/GLOBECOM48099.2022.10001588","DOIUrl":"https://doi.org/10.1109/GLOBECOM48099.2022.10001588","url":null,"abstract":"Recent proposals leverage emerging programmable switches to implement high-throughput and low-latency load balancers in the datacenter. However, most of them store per-connection states in programmable switches to ensure consistent load balancing decisions, which is costly due to the limited on-chip memory. Other proposals avoid storing per-connection states but have difficulty in large-scale deployment due to the modification of running applications. We present CDLB, a cost-effective and deployment-friendly Layer-4 load balancer based on programmable switches in the datacenter. To be cost-effective, CDLB leverages an improved hash-based algorithm that can maintain per-connection consistency in a static environment. To be easier in deployment, we introduce a small state table and design a protocol between load balancers and the controller to maintain per-connection consistency in a dynamic environment without modifying running applications. The state table stores small amounts of connection states temporarily to ensure consistent load balancing decisions under device variations. We implemented CDLB with bmv2 in the mininet environment. The evaluation results show that CDLB greatly reduces overhead and achieves better performance compared with stateful load balancers which store per-connection states in programmable switches, and CDLB maintains per-connection consistency well in a dynamic environment.","PeriodicalId":313199,"journal":{"name":"GLOBECOM 2022 - 2022 IEEE Global Communications Conference","volume":"112 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124235708","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

Energy-Harvesting Based Jammer Localization: A Battery-Free Approach in Wireless Sensor Networks 基于能量收集的干扰器定位:无线传感器网络中的无电池方法

GLOBECOM 2022 - 2022 IEEE Global Communications Conference Pub Date : 2022-12-04 DOI: 10.1109/GLOBECOM48099.2022.10000705

Ahmed Mohamed Hussain, Pietro Tedeschi, G. Oligeri, Amr Mohamed, M. Guizani

{"title":"Energy-Harvesting Based Jammer Localization: A Battery-Free Approach in Wireless Sensor Networks","authors":"Ahmed Mohamed Hussain, Pietro Tedeschi, G. Oligeri, Amr Mohamed, M. Guizani","doi":"10.1109/GLOBECOM48099.2022.10000705","DOIUrl":"https://doi.org/10.1109/GLOBECOM48099.2022.10000705","url":null,"abstract":"Wireless enabling technologies in critical infrastructures are increasing the efficiency of communications. Most of these technologies are vulnerable to jamming attacks. Jamming attacks are among the most effective countermeasures to attack and compromise their availability. Jamming is an interfering signal that limits the intended receiver from correctly receiving the messages. Localizing a jammer deployed by the adversary in wireless sensor networks becomes difficult, if not impossible, due to the inaccessibility of the affected sensors in the network. This paper proposes an effective yet efficient jammer localization scheme where battery-free Radio-Frequency Identification (RFID) sensor tags harvest the energy from the signal emitted by a powerful jammer. We compute the distance and estimate the actual jammer location based on the power received at each energy-harvesting node. We conduct extensive simulations campaign to test and illustrate the effectiveness of the proposed scheme. Finally, we demonstrate the possibility of deploying the proposed scheme with off-shelf equipment and consuming only 0.2175 mJ,","PeriodicalId":313199,"journal":{"name":"GLOBECOM 2022 - 2022 IEEE Global Communications Conference","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124239329","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

An IoT Traffic Modeling Framework and its Application to Autonomous Edge Scaling 物联网流量建模框架及其在自主边缘扩展中的应用

GLOBECOM 2022 - 2022 IEEE Global Communications Conference Pub Date : 2022-12-04 DOI: 10.1109/GLOBECOM48099.2022.10000950

Dana Haj Hussein, M. Ibnkahla

{"title":"An IoT Traffic Modeling Framework and its Application to Autonomous Edge Scaling","authors":"Dana Haj Hussein, M. Ibnkahla","doi":"10.1109/GLOBECOM48099.2022.10000950","DOIUrl":"https://doi.org/10.1109/GLOBECOM48099.2022.10000950","url":null,"abstract":"Future wireless networks will exhibit heterogeneity of traffic generating sources originated by numerous Internet of Things (IoT) nodes as well as traditional mobile phones. Moreover, the space of novel IoT services is expanding the simple monitoring tasks of IoT nodes to more complex services in which a node can be in a monitoring state and transition autonomously to an alarm state when predefined conditions are detected. The complexity of the envisioned future wireless networks is indeed new to the community with challenges affecting many aspects such as protocol design and network operation mechanisms. Traffic modeling lies at the core of these issues. As the advancement of technologies continues, faithful performance evaluation measures are dependent on the underlying traffic model. In this scope, we propose a Tiered Markov Modulated Poisson Process (TMMPP) that is capable of capturing IoT traffic characteristics, e.g. patterns and seasonality, which occur in long time spans, e.g days, with the flexibility of modeling different IoT service behaviors. Moreover, we study an autonomous edge scaling mechanism as a use case illustrating the benefits of the proposed TMMPP traffic model.","PeriodicalId":313199,"journal":{"name":"GLOBECOM 2022 - 2022 IEEE Global Communications Conference","volume":"67 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114072341","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

IoT Device Identification Based on Network Traffic Characteristics 基于网络流量特征的物联网设备识别

GLOBECOM 2022 - 2022 IEEE Global Communications Conference Pub Date : 2022-12-04 DOI: 10.1109/GLOBECOM48099.2022.10001639

M. Mainuddin, Z. Duan, Yingfei Dong, Shaeke Salman, Tania Taami

{"title":"IoT Device Identification Based on Network Traffic Characteristics","authors":"M. Mainuddin, Z. Duan, Yingfei Dong, Shaeke Salman, Tania Taami","doi":"10.1109/GLOBECOM48099.2022.10001639","DOIUrl":"https://doi.org/10.1109/GLOBECOM48099.2022.10001639","url":null,"abstract":"IoT device identification plays an important role in monitoring and improving the performance and security of IoT devices. Compared to traditional non-IoT devices, IoT devices provide us with both unique challenges and opportunities in detecting the types of IoT devices. Based on critical insights obtained in our previous work on understanding the network traffic characteristics of IoT devices, in this paper we develop an effective machine-learning based IoT device identification scheme, named iotID. In developing iotID, we extract 70 features of TCP flows from three complementary aspects: remote network servers and port numbers, packet-level traffic characteristics such as packet inter-arrival times, and flow-level traffic characteristics such as flow duration. Different from existing work, we take into account the imbalance nature of network traffic generated by various devices in both the learning and evaluation phases of iotID. Our performance studies based on network traffic collected on a typical smart home environment consisting of both IoT and non-IoT devices show that iotID can achieve a balanced accuracy score of above 99%.","PeriodicalId":313199,"journal":{"name":"GLOBECOM 2022 - 2022 IEEE Global Communications Conference","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114525516","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

Reinforcement Learning-Based Network Slice Resource Allocation for Federated Learning Applications 基于强化学习的联邦学习应用网络片资源分配

GLOBECOM 2022 - 2022 IEEE Global Communications Conference Pub Date : 2022-12-04 DOI: 10.1109/GLOBECOM48099.2022.10001715

Zhouxiang Wu, Genya Ishigaki, Riti Gour, Congzhou Li, J. Jue

引用次数: 1

Stochastic Resource Allocation in Quantum Key Distribution for Secure Federated Learning 安全联邦学习量子密钥分配中的随机资源分配

GLOBECOM 2022 - 2022 IEEE Global Communications Conference Pub Date : 2022-12-04 DOI: 10.1109/GLOBECOM48099.2022.10001071

Minrui Xu, Wei Chong Ng, D. Niyato, Han Yu, Chunyan Miao, Dong In Kim, X. Shen

{"title":"Stochastic Resource Allocation in Quantum Key Distribution for Secure Federated Learning","authors":"Minrui Xu, Wei Chong Ng, D. Niyato, Han Yu, Chunyan Miao, Dong In Kim, X. Shen","doi":"10.1109/GLOBECOM48099.2022.10001071","DOIUrl":"https://doi.org/10.1109/GLOBECOM48099.2022.10001071","url":null,"abstract":"Federated learning (FL) is a distributed machine learning paradigm with a promising future, which can preserve data privacy while training the global model collaboratively. However, FL is still facing model confidentiality issues. Therefore, in this paper, we propose a quantum key distribution (QKD) based secure FL scheme to facilitate FL model encryption against network eavesdropping attacks. Specifically, we introduce a stochastic resource allocation scheme for QKD to support FL networks. In the network, remote FL workers are connected to the server to train an aggregated global model in a distributed manner. However, due to the unpredictable number of workers at each location, the demand for secret-key rates to support secure model transmission to the server is not uniform. The proposed scheme can allocate QKD resources (i.e., wavelengths) in a way that minimizes the total cost given the stochastic demand. We formulate the optimization problem for the proposed scheme as a stochastic programming model. Numerical results demonstrate that the proposed scheme can successfully achieve the cost-minimizing objective while satisfying all uncertain demands and other security constraints.","PeriodicalId":313199,"journal":{"name":"GLOBECOM 2022 - 2022 IEEE Global Communications Conference","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116218984","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

Optimized Sparrow Search-based Multiplexing of eMBB and URLLC in 5G/B5G Networks 5G/B5G网络中基于麻雀搜索的eMBB和URLLC复用优化

GLOBECOM 2022 - 2022 IEEE Global Communications Conference Pub Date : 2022-12-04 DOI: 10.1109/GLOBECOM48099.2022.10001001

Mengqiu Tian, Changle Li, Yilong Hui, Nan Cheng, Maofeng Luo

{"title":"Optimized Sparrow Search-based Multiplexing of eMBB and URLLC in 5G/B5G Networks","authors":"Mengqiu Tian, Changle Li, Yilong Hui, Nan Cheng, Maofeng Luo","doi":"10.1109/GLOBECOM48099.2022.10001001","DOIUrl":"https://doi.org/10.1109/GLOBECOM48099.2022.10001001","url":null,"abstract":"In 5G/B5G networks, the preemptive scheduling provides an efficient solution to the coexistence problem of eMBB/URLLC services. Current works usually assume that the downlink transmission duration of each URLLC service is within one mini-slot, which ignores the different requirements of URLLC users and may lead to the severe data rate loss of eMBB services and low resource utilization efficiency. To deal with above problem, we propose a novel URLLC preemptive strategy, where the arriving URLLC services could cross through multiple mini-slots rather than only one to puncture resources on demand. With the proposed strategy, considering the heterogeneous delay requirements of URLLC services and the preemptive influence on eMBB services, an efficient algorithm based on optimized sparrow search is also proposed. Through allocating time and frequency resources occupied by each URLLC service on de-mand, the number of URLLC services supported by the gNB is maximized while the satisfaction of eMBB services is ensured. The simulation results indicate that the proposed algorithm can achieve better performance compared with the benchmark schemes.","PeriodicalId":313199,"journal":{"name":"GLOBECOM 2022 - 2022 IEEE Global Communications Conference","volume":"144 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116361355","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