IEEE INFOCOM 2023 - IEEE Conference on Computer Communications最新文献_第9页

NFChain: A Practical Fingerprinting Scheme for NFC Tag Authentication NFChain:一种实用的NFC标签认证指纹方案

IEEE INFOCOM 2023 - IEEE Conference on Computer Communications Pub Date : 2023-05-17 DOI: 10.1109/INFOCOM53939.2023.10229040

Yanni Yang, Jiannong Cao, Zhenlin An, Yanwen Wang, Pengfei Hu, Guoming Zhang

{"title":"NFChain: A Practical Fingerprinting Scheme for NFC Tag Authentication","authors":"Yanni Yang, Jiannong Cao, Zhenlin An, Yanwen Wang, Pengfei Hu, Guoming Zhang","doi":"10.1109/INFOCOM53939.2023.10229040","DOIUrl":"https://doi.org/10.1109/INFOCOM53939.2023.10229040","url":null,"abstract":"NFC tag authentication is highly demanded to avoid tag abuse. Recent fingerprinting methods employ the physical-layer signal, which embeds the tag hardware imperfections for authentication. However, existing NFC fingerprinting methods suffer from either low scalability for a large number of tags or incompatibility with NFC protocols, impeding the practical application of NFC authentication systems. To fill this gap, we propose NFChain, a new NFC fingerprinting scheme that excavates the tag hardware uniqueness from the protocol-agnostic tag response signal. Specifically, we harness an agile and compatible frequency band of NFC to extract the tag fingerprint from a chain of tag responses over multiple frequencies, which significantly improves fingerprint scalability. However, extracting the desired fingerprint encounters two practical challenges: (1) fingerprint inconsistency under different NFC reader and tag configurations and (2) fingerprint variations across multiple measurements of the same tag due to the signal noise in generic readers. To tackle these challenges, we first design an effective nulling method to eliminate the effect of device configurations. Second, we employ contrastive learning to reduce fingerprint variations for accurate authentication. Extensive experiments show we can achieve as low as 3.7% FRR and 4.1% FAR for over 600 tags.","PeriodicalId":387707,"journal":{"name":"IEEE INFOCOM 2023 - IEEE Conference on Computer Communications","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128537352","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

Oblivion: Poisoning Federated Learning by Inducing Catastrophic Forgetting 遗忘:通过诱导灾难性遗忘毒害联邦学习

IEEE INFOCOM 2023 - IEEE Conference on Computer Communications Pub Date : 2023-05-17 DOI: 10.1109/INFOCOM53939.2023.10228981

Chen Zhang, Boyang Zhou, Zhiqiang He, Zeyuan Liu, Yanjiao Chen, Wenyuan Xu, Baochun Li

{"title":"Oblivion: Poisoning Federated Learning by Inducing Catastrophic Forgetting","authors":"Chen Zhang, Boyang Zhou, Zhiqiang He, Zeyuan Liu, Yanjiao Chen, Wenyuan Xu, Baochun Li","doi":"10.1109/INFOCOM53939.2023.10228981","DOIUrl":"https://doi.org/10.1109/INFOCOM53939.2023.10228981","url":null,"abstract":"Federated learning is exposed to model poisoning attacks as compromised clients may submit malicious model updates to pollute the global model. To defend against such attacks, robust aggregation rules are designed for the centralized server to winnow out outlier updates, and to significantly reduce the effectiveness of existing poisoning attacks. In this paper, we develop an advanced model poisoning attack against defensive aggregation rules. In particular, we exploit the catastrophic forgetting phenomenon during the process of continual learning to destroy the memory of the global model. Our proposed framework, called Oblivion, features two special components. The first component prioritizes the weights that have the most influence on the model accuracy for poisoning, which induces a more significant degradation on the global model than equally perturbing all weights. The second component smooths malicious model updates based on the number of selected compromised clients in the current round, adjusting the degree of poisoning to suit the dynamics of each training round. We implement a fully-functional prototype of Oblivion in PLATO, a real-world scalable federated learning framework. Our extensive experiments over three datasets demonstrate that Oblivion can boost the attack performance of model poisoning attacks against unknown defensive aggregation rules.","PeriodicalId":387707,"journal":{"name":"IEEE INFOCOM 2023 - IEEE Conference on Computer Communications","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134139430","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 Better Cardinality Estimator with Fewer Bits, Constant Update Time, and Mergeability 具有更少位、恒定更新时间和可合并性的更好的基数估计器

IEEE INFOCOM 2023 - IEEE Conference on Computer Communications Pub Date : 2023-05-17 DOI: 10.1109/INFOCOM53939.2023.10229088

Yangyan Du, He Huang, Yu-e Sun, Kejian Li, Boyu Zhang, Guoju Gao

{"title":"A Better Cardinality Estimator with Fewer Bits, Constant Update Time, and Mergeability","authors":"Yangyan Du, He Huang, Yu-e Sun, Kejian Li, Boyu Zhang, Guoju Gao","doi":"10.1109/INFOCOM53939.2023.10229088","DOIUrl":"https://doi.org/10.1109/INFOCOM53939.2023.10229088","url":null,"abstract":"Cardinality estimation is a fundamental problem with diverse practical applications. HyperLogLog (HLL) has become a standard in practice because it offers good memory efficiency, constant update time, and mergeability. Some recent work achieved better memory efficiency, but typically at the cost of impractical update time or losing mergeability, making them incompatible with applications like network-wide traffic measurement. This work presents SpikeSketch, a better cardinality estimator that reduces memory usage of HLL by 37% without sacrificing other crucial metrics. We adopt a bucket-based data structure to promise constant update time, design a smoothed log4 ranking and a spike coding scheme to compress cardinality observables into buckets, and propose a lightweight mergeable lossy compression to balance memory usage, information loss, and mergeability. Then we derive an unbiased estimator for recovering cardinality from the lossy-compressed sketch. Theoretical and empirical results show that SpikeSketch can work as a drop-in replacement for HLL because it achieves a near-optimal MVP (memory-variance-product) of 4.08 (37% smaller than HLL) with constant update time and mergeability. Its memory efficiency even defeats ACPC and HLLL, the state-of-the-art lossless-compressed sketches using linear-time compression to reduce memory usage.","PeriodicalId":387707,"journal":{"name":"IEEE INFOCOM 2023 - IEEE Conference on Computer Communications","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132741827","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

Joint Task Offloading and Resource Allocation in Heterogeneous Edge Environments 异构边缘环境下的联合任务卸载与资源分配

IEEE INFOCOM 2023 - IEEE Conference on Computer Communications Pub Date : 2023-05-17 DOI: 10.1109/INFOCOM53939.2023.10229015

Yu Liu, Yingling Mao, Z. Liu, Fan Ye, Yuanyuan Yang

{"title":"Joint Task Offloading and Resource Allocation in Heterogeneous Edge Environments","authors":"Yu Liu, Yingling Mao, Z. Liu, Fan Ye, Yuanyuan Yang","doi":"10.1109/INFOCOM53939.2023.10229015","DOIUrl":"https://doi.org/10.1109/INFOCOM53939.2023.10229015","url":null,"abstract":"Mobile edge computing is becoming one of the ubiquitous computing paradigms to support applications requiring low latency and high computing capability. FPGA-based reconfigurable accelerators have high energy efficiency and low latency compared to general-purpose servers. Therefore, it is natural to incorporate reconfigurable accelerators in mobile edge computing systems. This paper formulates and studies the problem of joint task offloading, access point selection, and resource allocation in heterogeneous edge environments for latency minimization. Due to the heterogeneity in edge computing devices and the coupling between offloading, access point selection, and resource allocation decisions, it is challenging to optimize over them simultaneously. We decomposed the proposed problem into two disjoint subproblems and developed algorithms for them. The first subproblem is to jointly determine offloading and computing resource allocation decisions and is NP-hard, where we developed an algorithm based on semidefinite relaxation. The second subproblem is to jointly determine access point selection and communication resource allocation decisions, where we proposed an algorithm with a provable approximation ratio of 2.62. We conducted extensive numerical simulations to evaluate the proposed algorithms. Results highlighted that the proposed algorithms outperformed baselines and were near-optimal over a wide range of settings.","PeriodicalId":387707,"journal":{"name":"IEEE INFOCOM 2023 - IEEE Conference on Computer Communications","volume":"115 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132795378","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

Digital Twin-Enabled Service Satisfaction Enhancement in Edge Computing 在边缘计算中提升数字孪生服务满意度

IEEE INFOCOM 2023 - IEEE Conference on Computer Communications Pub Date : 2023-05-17 DOI: 10.1109/INFOCOM53939.2023.10228893

Jing Li, Jianping Wang, Quan Chen, Yuchen Li, A. Zomaya

{"title":"Digital Twin-Enabled Service Satisfaction Enhancement in Edge Computing","authors":"Jing Li, Jianping Wang, Quan Chen, Yuchen Li, A. Zomaya","doi":"10.1109/INFOCOM53939.2023.10228893","DOIUrl":"https://doi.org/10.1109/INFOCOM53939.2023.10228893","url":null,"abstract":"The emerging digital twin technique enhances the network management efficiency and provides comprehensive insights, through mapping physical objects to their digital twins. The user satisfaction on digital twin-enabled query services relies on the freshness of digital twin data, which is measured by the Age of Information (AoI). Because the remote cloud faces challenges in providing data for users due to long service delays, Mobile Edge Computing (MEC), as a promising technology, offers real-time data communication between physical objects and their digital twins at the edge of the core network. However, the mobility of physical objects and dynamic query arrivals make efficient service provisioning in MEC become challenging. In this paper, we investigate the dynamic digital twin placement for improving user service satisfaction in MEC environments. We focus on two user service satisfaction augmentation problems under both static and dynamic digital twin placement schemes: the static and dynamic utility maximization problems. We first formulate an Integer Linear Programming (ILP) solution to the static utility maximization problem when the problem size is small; otherwise, we propose a performance- guaranteed approximation algorithm for it. We then devise an online algorithm for the dynamic utility maximization problem with a provable competitive ratio. Finally, we evaluate the performance of the proposed algorithms through experimental simulations. Simulation results demonstrate that the proposed algorithms outperform the comparison baseline algorithms, and the performance improvement is no less than 11.6%, compared with the baseline algorithms.","PeriodicalId":387707,"journal":{"name":"IEEE INFOCOM 2023 - IEEE Conference on Computer Communications","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130560341","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

CaaS: Enabling Control-as-a-Service for Time-Sensitive Networking CaaS:为时间敏感型网络启用控制即服务

IEEE INFOCOM 2023 - IEEE Conference on Computer Communications Pub Date : 2023-05-17 DOI: 10.1109/INFOCOM53939.2023.10228980

Zheng Yang, Yi Zhao, Fan Dang, Xiaowu He, Jiahang Wu, Hao Cao, Zeyu Wang, Yunhao Liu

{"title":"CaaS: Enabling Control-as-a-Service for Time-Sensitive Networking","authors":"Zheng Yang, Yi Zhao, Fan Dang, Xiaowu He, Jiahang Wu, Hao Cao, Zeyu Wang, Yunhao Liu","doi":"10.1109/INFOCOM53939.2023.10228980","DOIUrl":"https://doi.org/10.1109/INFOCOM53939.2023.10228980","url":null,"abstract":"Flexible manufacturing is one of the core goals of Industry 4.0 and brings new challenges to current industrial control systems. Our detailed field study on auto glass industry revealed that existing production lines are laborious to reconfigure, difficult to upscale, and costly to upgrade during production switching. Such inflexibility arises from the tight coupling of devices, controllers, and control tasks. In this work, we propose a new architecture for industrial control systems named Control-as-a-Service (CaaS). CaaS transfers and distributes control tasks from dedicated controllers into Time-Sensitive Networking (TSN) switches. By combining control and transmission functions in switches, CaaS virtualizes the industrial TSN network to one Programmable Logic Controller (PLC). We propose a set of techniques that realize end-to-end determinism for in-network industrial control and a joint task and traffic scheduling algorithm. We evaluate the performance of CaaS on testbeds based on real-world networked control systems. The results show that the idea of CaaS is feasible and effective, and CaaS achieves absolute packet delivery, 42-45% lower latency, and three orders of magnitude lower jitter. We believe CaaS is a meaningful step towards the distribution, virtualization, and servitization of industrial control.","PeriodicalId":387707,"journal":{"name":"IEEE INFOCOM 2023 - IEEE Conference on Computer Communications","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121895702","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

flexRLM: Flexible Radio Link Monitoring for Multi-User Downlink Millimeter-Wave Networks flexRLM:多用户下行毫米波网络的灵活无线电链路监测

IEEE INFOCOM 2023 - IEEE Conference on Computer Communications Pub Date : 2023-05-17 DOI: 10.1109/INFOCOM53939.2023.10229071

Aleksandar Ichkov, Aron Schott, P. Mähönen, L. Simić

{"title":"flexRLM: Flexible Radio Link Monitoring for Multi-User Downlink Millimeter-Wave Networks","authors":"Aleksandar Ichkov, Aron Schott, P. Mähönen, L. Simić","doi":"10.1109/INFOCOM53939.2023.10229071","DOIUrl":"https://doi.org/10.1109/INFOCOM53939.2023.10229071","url":null,"abstract":"Exploiting millimeter-wave (mm-wave) for high-capacity multi-user networks is predicated on jointly performing beam management for seamless connectivity and efficient resource sharing among all users. Beam management in 5G-NR actively monitors candidate beam pair links (BPLs) on the serving cell to simply select the user’s best beam, but neglects the multi-user resource sharing problem, potentially leading to severe throughput degradation on overloaded cells. We propose flexRLM, a coordinator-based flexible radio link monitoring (RLM) framework for multi-user downlink mm-wave networks. flexRLM enables flexible configuration of monitored BPLs on the serving and other candidate cells and beam selection jointly considering link quality and resource sharing. flexRLM is fully 5G-NR-compliant and uses the LTE coordinator in non-standalone mode to continuously update the monitored BPLs via measurement reports from periodic downlink control synchronization signals. We implement flexRLM in ns-3 and present full-stack simulations to demonstrate the superior performance of flexRLM over default 5G-NR RLM in multi-user networks. Our results show that flexRLM’s continuous updating of monitored BPLs improves both link quality and stability. By monitoring BPLs on candidate cells other than the serving one, flexRLM also significantly decreases handover decision delays. Importantly, flexRLM’s low-complexity coordinated load-balancing achieves a per-user throughput close to the single-user baseline.","PeriodicalId":387707,"journal":{"name":"IEEE INFOCOM 2023 - IEEE Conference on Computer Communications","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126028471","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

MagFingerprint: A Magnetic Based Device Fingerprinting in Wireless Charging 磁指纹:无线充电中基于磁的设备指纹识别技术

IEEE INFOCOM 2023 - IEEE Conference on Computer Communications Pub Date : 2023-05-17 DOI: 10.1109/INFOCOM53939.2023.10229033

Jiachun Li, Yan Meng, Le Zhang, Guoxing Chen, Yuan Tian, Haojin Zhu, X. Shen

{"title":"MagFingerprint: A Magnetic Based Device Fingerprinting in Wireless Charging","authors":"Jiachun Li, Yan Meng, Le Zhang, Guoxing Chen, Yuan Tian, Haojin Zhu, X. Shen","doi":"10.1109/INFOCOM53939.2023.10229033","DOIUrl":"https://doi.org/10.1109/INFOCOM53939.2023.10229033","url":null,"abstract":"Wireless charging is a promising solution for charging battery-driven devices pervasively. However, the wide deployment of wireless charging stations is vulnerable to the device masquerade attack, which causes financial loss when billing or charging system damages like overheating and explosion. Device fingerprinting is a classical technique to thwart the device masquerade attack. But existing works either are vulnerable to forging or require specialized equipment, which is not suitable for wireless charging.In this paper, we design a magnetic based fingerprinting system MagFingerprint, which utilizes the alternating magnetic signals as the fingerprint and is compatible with existing wireless charging systems. MagFingerprint is convenient for the user since it only employs commercial-off-the-shelf (COTS) magnetic sensors and requires no action from users. In particular, for the charging device, based on its intrinsic manufacturing errors, MagFingerprint generates a unique fingerprint according to the distinct magnetic changes during the wireless charging process. It is shown that MagFingerprint can achieve an accuracy of 98.90% on wireless charging exposed coils, while it is also effective on different commercial wireless charging pads of Apple, Huawei, and Xiaomi.","PeriodicalId":387707,"journal":{"name":"IEEE INFOCOM 2023 - IEEE Conference on Computer Communications","volume":"87 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123759483","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

Secure and Robust Two Factor Authentication via Acoustic Fingerprinting 基于声学指纹的安全可靠的双因素身份验证

IEEE INFOCOM 2023 - IEEE Conference on Computer Communications Pub Date : 2023-05-17 DOI: 10.1109/INFOCOM53939.2023.10229054

Yanzhi Ren, Tingyuan Yang, Zhiliang Xia, Hongbo Liu, Yingying Chen, Nan Jiang, Zhaohui Yuan, Hongwei Li

{"title":"Secure and Robust Two Factor Authentication via Acoustic Fingerprinting","authors":"Yanzhi Ren, Tingyuan Yang, Zhiliang Xia, Hongbo Liu, Yingying Chen, Nan Jiang, Zhaohui Yuan, Hongwei Li","doi":"10.1109/INFOCOM53939.2023.10229054","DOIUrl":"https://doi.org/10.1109/INFOCOM53939.2023.10229054","url":null,"abstract":"The two-factor authentication (2FA) has become pervasive as the mobile devices become prevalent. Existing 2FA solutions usually require some form of user involvement, which could severely affect user experience and bring extra burdens to users. In this work, we propose a secure 2FA that utilizes the individual acoustic fingerprint of the speaker/microphone on enrolled device as the second proof. The main idea behind our system is to use both magnitude and phase fingerprints derived from the frequency response of the enrolled device by emitting acoustic beep signals alternately from both enrolled and login devices and receiving their direct arrivals for 2FA. Given the input microphone samplings, our system designs an arrival time detection scheme to accurately identify the beginning point of the beep signal from the received signal. To achieve a robust authentication, we develop a new distance mitigation scheme to eliminate the impact of transmission distances from the sound propagation model for extracting stable fingerprint in both magnitude and phase domain. Our device authentication component then calculates a weighted correlation value between the device profile and fingerprints extracted from run-time measurements to conduct the device authentication for 2FA. Our experimental results show that our proposed system is accurate and robust to both random impersonation and Man-in-the-middle (MiM) attack across different scenarios and device models.","PeriodicalId":387707,"journal":{"name":"IEEE INFOCOM 2023 - IEEE Conference on Computer Communications","volume":"143 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121961821","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 Bayesian Framework for Online Nonconvex Optimization over Distributed Processing Networks 分布式处理网络在线非凸优化的贝叶斯框架

IEEE INFOCOM 2023 - IEEE Conference on Computer Communications Pub Date : 2023-05-17 DOI: 10.1109/INFOCOM53939.2023.10228879

Zai Shi, Yilin Zheng, A. Eryilmaz

{"title":"A Bayesian Framework for Online Nonconvex Optimization over Distributed Processing Networks","authors":"Zai Shi, Yilin Zheng, A. Eryilmaz","doi":"10.1109/INFOCOM53939.2023.10228879","DOIUrl":"https://doi.org/10.1109/INFOCOM53939.2023.10228879","url":null,"abstract":"In many applications such as statistical machine learning, reinforcement learning, and optimization for large data centers, the increasing data size and model complexity have made it impractical to run optimizations over a single machine. Therefore, solving the distributed optimization problem has become an important task. In this work, we consider a distributed processing network $G = left( {mathcal{V},mathcal{E}} right)$ with n nodes, where each node i can only evaluate the values of a local function (i.e., has zeroth-order information) and can only communicate with its neighbors. The objective is to reach consensus on the global optimizer of ${max _{x in mathcal{X}}}frac{1}{n}sumnolimits_{i = 1}^n {{f_i}(x)} $. Previous methods either assume first-order gradient information which is not suitable for many model-free learning scenarios, or consider the zeroth-order information but assume convexity of the objective functions and can only guarantee convergence to a stationary point for nonconvex objectives. To address these limitations, we drop both the known gradient assumption and convexity assumption. Instead, we propose a distributed Bayesian framework for the problem with only zeroth-order information and general nonconvex objective functions in a Matérn Reproducing Kernel Hilbert Space (RKHS). Under this framework, we propose an algorithm and show that with high probability it reaches consensus on all nodes and has a sublinear regret with regard to the global optimal. The results are validated under numerical studies.","PeriodicalId":387707,"journal":{"name":"IEEE INFOCOM 2023 - IEEE Conference on Computer Communications","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124654789","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