Journal of Optical Communications and Networking最新文献_第5页

Decentralized key distribution versus on-demand relaying for QKD networks 去中心化密钥分发与QKD网络的按需中继

IF 4 2区计算机科学

Journal of Optical Communications and Networking Pub Date : 2025-07-25 DOI: 10.1364/JOCN.547793

Maria Alvarez Roa;Catalina Stan;Sebastian Verschoor;Idelfonso Tafur Monroy;Simon Rommel

{"title":"Decentralized key distribution versus on-demand relaying for QKD networks","authors":"Maria Alvarez Roa;Catalina Stan;Sebastian Verschoor;Idelfonso Tafur Monroy;Simon Rommel","doi":"10.1364/JOCN.547793","DOIUrl":"https://doi.org/10.1364/JOCN.547793","url":null,"abstract":"Quantum key distribution (QKD) allows the distribution of secret keys for quantum-secure communication between two distant parties, vital in the quantum computing era in order to protect against quantum-enabled attackers. However, overcoming rate-distance limits in QKD and the establishment of quantum key distribution networks necessitate key relaying over trusted nodes. This process may be resource-intensive, consuming a substantial share of the scarce QKD key material to establish end-to-end secret keys. Hence, an efficient scheme for key relaying and the establishment of end-to-end key pools is essential for practical and extended quantum-secured networking. In this paper, we propose and compare two protocols for managing, storing, and distributing secret key material in QKD networks, addressing challenges such as the success rate of key requests, key consumption, and overhead resulting from relaying. We present an innovative, fully decentralized key distribution strategy as an alternative to the traditional hop-by-hop relaying via trusted nodes, where three experiments are considered to evaluate performance metrics under varying key demand. Our results show that the decentralized pre-flooding approach achieves higher success rates as application demands increase. This analysis highlights the strengths of each approach in enhancing QKD network performance, offering valuable insights for developing robust key distribution strategies in different scenarios.","PeriodicalId":50103,"journal":{"name":"Journal of Optical Communications and Networking","volume":"17 8","pages":"732-742"},"PeriodicalIF":4.0,"publicationDate":"2025-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144704948","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Deep reinforcement learning-aided multi-step job scheduling in optical data center networks 深度强化学习辅助光数据中心网络多步作业调度

IF 4 2区计算机科学

Journal of Optical Communications and Networking Pub Date : 2025-07-24 DOI: 10.1364/JOCN.562531

Che-Yu Liu;Xiaoliang Chen;Roberto Proietti;Zuqing Zhu;S. J. Ben Yoo

{"title":"Deep reinforcement learning-aided multi-step job scheduling in optical data center networks","authors":"Che-Yu Liu;Xiaoliang Chen;Roberto Proietti;Zuqing Zhu;S. J. Ben Yoo","doi":"10.1364/JOCN.562531","DOIUrl":"https://doi.org/10.1364/JOCN.562531","url":null,"abstract":"Orchestrating job scheduling and topology reconfiguration in optical data center networks (ODCNs) is essential for meeting the intensive communication demand of novel applications, such as distributed machine learning (ML) workloads. However, this task involves joint optimization of multi-dimensional resources that can barely be effectively addressed by simple rule-based policies. In this paper, we leverage the powerful state representation and self-learning capabilities from deep reinforcement learning (DRL) and propose a multi-step job schedule algorithm for ODCNs. Our design decomposes a job request into an ordered sequence of virtual machines (VMs) and the related bandwidth demand in between, and then makes a DRL agent learn how to place the VMs sequentially. To do so, we feed the agent with the global bandwidth and IT resource utilization state embedded with the previous VM allocation decisions in each step and reward the agent with both team and individual incentives. The team reward encourages the agent to jointly optimize the VM placement in multiple steps to pursue successful provisioning of the job request, while the individual reward favors advantageous local placement decisions, i.e., to prevent effective policies being overwhelmed by a few subpar decisions. We also introduce a penalty on reconfiguration to balance between performance gains and reconfiguration overheads. Simulation results under various ODCN configurations and job loads show our proposal outperforms the existing heuristic solutions and reduces the job-blocking probability and reconfiguration frequency by at least <tex>$7.35 times$</tex> and <tex>$4.59 times$</tex>, respectively.","PeriodicalId":50103,"journal":{"name":"Journal of Optical Communications and Networking","volume":"17 9","pages":"D96-D105"},"PeriodicalIF":4.0,"publicationDate":"2025-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144695545","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Edge coloring bipartite multigraphs for dynamically configuring optical switches 动态配置光开关的边缘着色二部多图

IF 4 2区计算机科学

Journal of Optical Communications and Networking Pub Date : 2025-07-23 DOI: 10.1364/JOCN.559454

Jan De Neve;Ziyue Zhang;Wouter Tavernier;Didier Colle;Mario Pickavet

{"title":"Edge coloring bipartite multigraphs for dynamically configuring optical switches","authors":"Jan De Neve;Ziyue Zhang;Wouter Tavernier;Didier Colle;Mario Pickavet","doi":"10.1364/JOCN.559454","DOIUrl":"https://doi.org/10.1364/JOCN.559454","url":null,"abstract":"Multi-chip graphics processing units (GPUs) interconnected by a photonic network-on-wafer are a promising technology to further increase the performance of GPUs. The network control algorithm managing dynamic bandwidth allocation (DBA) in this network needs to execute very frequently so that resources can be optimally used. This algorithm relies on edge coloring bipartite multigraphs to translate inter-chip bandwidth demands into updated routing tables for the GPU chips and optical switches in the network. In this work, we design fast edge coloring algorithms, both approximate and exact, for bipartite multigraphs. These algorithms are tailored to the high edge multiplicities of the multigraphs in this research. The runtimes are optimized by using efficient data structures and introducing pre- and post-processing. These new algorithms are up to <tex>${20} times$</tex> faster than the state-of-the-art baseline algorithm. New simulations show that, with such low reconfiguration periods, DBA has the potential to double the performance of a high-traffic GPU workload compared to a static network with the same bandwidth.","PeriodicalId":50103,"journal":{"name":"Journal of Optical Communications and Networking","volume":"17 8","pages":"720-731"},"PeriodicalIF":4.0,"publicationDate":"2025-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144687661","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Explainable AI-assisted low-latency haptic feedback prediction for human-to-machine applications over passive optical networks 可解释的人工智能辅助低延迟触觉反馈预测在无源光网络上的人机应用

IF 4 2区计算机科学

Journal of Optical Communications and Networking Pub Date : 2025-07-22 DOI: 10.1364/JOCN.560757

Yuxiao Wang;Sourav Mondal;Ye Pu;Elaine Wong

引用次数: 0

Saturn: a chiplet-based optical network architecture for breaking the memory wall 土星：一种基于芯片的光网络架构，用于打破内存墙

IF 4 2区计算机科学

Journal of Optical Communications and Networking Pub Date : 2025-07-21 DOI: 10.1364/JOCN.559347

Lijing Zhu;Huaxi Gu;Kun Wang;Guangming Zhang

{"title":"Saturn: a chiplet-based optical network architecture for breaking the memory wall","authors":"Lijing Zhu;Huaxi Gu;Kun Wang;Guangming Zhang","doi":"10.1364/JOCN.559347","DOIUrl":"https://doi.org/10.1364/JOCN.559347","url":null,"abstract":"Given the increasingly computing-intensive and data-intensive workloads of high-performance computing applications, the need for more cores and larger storage capacity is expanding. While computational power is rapidly increasing, data movement capability among cores and memory modules has not stepped forward substantially. Low energy efficiency and parallelism of data movement have become a bottleneck. Optical interconnects with better bandwidth and power performance are a promising method. In addition, chiplet technology significantly amplifies the benefits of optical interconnects. However, existing optical networks do not take the modularity and flexible assembly of chiplets into account, nor do they take advantage of new fabrication and packaging. In this paper, we propose Saturn, an optical interconnection network architecture, including two parts: a core-to-memory network (CTMN) and a core-to-core network. In the CTMN, the integration of optical broadband micro-ring technology and co-designed wavelength assignment enables memory access to be completed in a single hop, providing highly parallel bandwidth. The serpentine layout employed in the CTMN eliminates waveguide crossings, which in turn substantially reduces the insertion loss and energy consumption. Analytical simulations have validated the effectiveness and efficiency of Saturn, showing that it can improve memory access throughput performance while achieving energy reduction compared with a traditional network.","PeriodicalId":50103,"journal":{"name":"Journal of Optical Communications and Networking","volume":"17 8","pages":"713-719"},"PeriodicalIF":4.0,"publicationDate":"2025-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144671222","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Interpretable optical network fault detection and localization with multi-task graph prototype learning 基于多任务图原型学习的可解释光网络故障检测与定位

IF 4 2区计算机科学

Journal of Optical Communications and Networking Pub Date : 2025-07-18 DOI: 10.1364/JOCN.562633

Xiaokang Chen;Xiaoliang Chen;Zuqing Zhu

{"title":"Interpretable optical network fault detection and localization with multi-task graph prototype learning","authors":"Xiaokang Chen;Xiaoliang Chen;Zuqing Zhu","doi":"10.1364/JOCN.562633","DOIUrl":"https://doi.org/10.1364/JOCN.562633","url":null,"abstract":"The recent advances in machine learning (ML) have promoted data-driven automated fault management in optical networks. However, existing ML-aided fault management approaches mainly rely on black-box models that lack intrinsic interpretability to secure their trustworthiness in mission-critical operation scenarios. In this paper, we propose an interpretable optical network fault detection and localization design leveraging multi-task graph prototype learning (MT-GPL). MT-GPL models an optical network and the optical performance monitoring data collected in it as graph-structured data and makes use of graph neural networks to learn graph embeddings that capture both topological correlations (for fault localization) and fault discriminative patterns (for root cause analysis). MT-GPL interprets its reasoning by (i) introducing a prototype layer that learns physics-aligned prototypes indicative of each fault class using the Monte Carlo tree search method and (ii) performing predictions based on the similarities between the embedding of an input graph and the learned prototypes. To enhance the scalability and interpretability of MT-GPL, we develop a multi-task architecture that performs concurrent fault localization and reasoning with node-level and device-level prototype learning and fault predictions. Performance evaluations show that our proposal achieves <tex>${gt}6.5%$</tex> higher prediction accuracy than the multi-layer perceptron model, while the visualizations of its reasoning processes verify the validity of its interpretability.","PeriodicalId":50103,"journal":{"name":"Journal of Optical Communications and Networking","volume":"17 9","pages":"D73-D82"},"PeriodicalIF":4.0,"publicationDate":"2025-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144657451","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Post-disaster cloud-service restoration through datacenter-carrier cooperation 通过数据中心-运营商合作实现灾后云服务恢复

IF 4 2区计算机科学

Journal of Optical Communications and Networking Pub Date : 2025-07-17 DOI: 10.1364/JOCN.561579

Subhadeep Sahoo;Sugang Xu;Sifat Ferdousi;Yusuke Hirota;Massimo Tornatore;Yoshinari Awaji;Biswanath Mukherjee

引用次数: 0

Multi-entity cooperation platform facilitating network-cloud recovery 多实体合作平台，促进网络云恢复

IF 4 2区计算机科学

Journal of Optical Communications and Networking Pub Date : 2025-07-16 DOI: 10.1364/JOCN.560240

Sugang Xu;Subhadeep Sahoo;Sifat Ferdousi;Masaki Shiraiwa;Yusuke Hirota;Massimo Tornatore;Yoshinari Awaji;Biswanath Mukherjee

引用次数: 0

Low-complexity SOP-based vibration broadband sensing and efficient recognition for stable IM/DD optical interconnects in data centers 基于低复杂度sop的数据中心稳定IM/DD光互连的振动宽带传感与高效识别

IF 4 2区计算机科学

Journal of Optical Communications and Networking Pub Date : 2025-07-15 DOI: 10.1364/JOCN.559810

Bang Yang;Jianwei Tang;Huiyang Yu;Yaguang Hao;Shuang Gao;Linsheng Fan;Yong Yao;Junpeng Liang;Jinlong Wei;Yanfu Yang

{"title":"Low-complexity SOP-based vibration broadband sensing and efficient recognition for stable IM/DD optical interconnects in data centers","authors":"Bang Yang;Jianwei Tang;Huiyang Yu;Yaguang Hao;Shuang Gao;Linsheng Fan;Yong Yao;Junpeng Liang;Jinlong Wei;Yanfu Yang","doi":"10.1364/JOCN.559810","DOIUrl":"https://doi.org/10.1364/JOCN.559810","url":null,"abstract":"With the rapid advancement of artificial intelligence (AI) technologies, the stability of optical interconnects in data centers has become increasingly important. Vibration sensing integrated in optical interconnect systems is conducive to identifying external disturbances in optical interconnects and achieving intelligent operation and maintenance. This paper proposes an easy-integration vibration-sensing scheme based on the state of polarization (SOP) of the fiber link. This scheme combines photonic technology with low-complexity digital signal processing (DSP) to detect link vibrations, ensuring full compatibility with intensity-modulation direct-detection (IM/DD) optical interconnect systems while minimizing additional complexity. Experiments show that our proposed scheme effectively detects SOP variations across a wide frequency range (0.5 Hz to 159 kHz). Based on the sensing system, a recognition scheme leveraging the Gramian angular field analysis and convolutional neural network (CNN) is proposed to recognize four types of vibration events simulated by a robotic arm, achieving a classification accuracy of 98%. Furthermore, experimental results confirm that the sensing system can detect SOP variations even under conditions of extremely low received optical power (ROP), where the communication system becomes inoperative. The proposed scheme enables robust event detection with minimal hardware overhead, which is suitable for real-world deployment in pluggable optical modules.","PeriodicalId":50103,"journal":{"name":"Journal of Optical Communications and Networking","volume":"17 8","pages":"692-699"},"PeriodicalIF":4.0,"publicationDate":"2025-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144634781","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Performance investigation on disaggregated artificial intelligence data centers beyond rack scale with optical switching 基于光交换的机架级以上分解人工智能数据中心性能研究

IF 4 2区计算机科学

Journal of Optical Communications and Networking Pub Date : 2025-07-14 DOI: 10.1364/JOCN.559613

Fulong Yan;Hanting Huang;Yanxian Bi;Peizhao Li;Zhiwen Xue;Chao Li;Zichen Liu;Zhixue He;Zihao Li;QiDong Cao

{"title":"Performance investigation on disaggregated artificial intelligence data centers beyond rack scale with optical switching","authors":"Fulong Yan;Hanting Huang;Yanxian Bi;Peizhao Li;Zhiwen Xue;Chao Li;Zichen Liu;Zhixue He;Zihao Li;QiDong Cao","doi":"10.1364/JOCN.559613","DOIUrl":"https://doi.org/10.1364/JOCN.559613","url":null,"abstract":"Accompanying the ever-increasing scale of big data applications, artificial intelligence data centers are facing the issue of resource fragments, resulting in a low network resource utilization ratio. Disaggregating the network resources is an efficient solution to improve the network resource utilization ratio by allocating the required amount of resources. In this paper, we focus on the problem of CPU and GPU resource disaggregation for an artificial intelligence data center. We carry out investigations for data center disaggregation exploiting optical switching. The results show that PCIe over optical (PO) guarantees 3 µs latency with 62 m of fiber. Compared with the PCIe with Ethernet switch (PE) solution, the PO scheme saves 48.3% completion time for the backprop application. Moreover, we compare the cost and power consumption of a data center architecture that scales out as the square of the port count of an optical packet switch (OPSquare) employing a PO scheme with respect to variants of OPSquare and Leaf-Spine under different network scales and interface bandwidths. Results show that the optical network architecture with the PO scheme saves 31.6% in cost and 12% in power consumption, respectively, compared with the Leaf-Spine with Ethernet solution.","PeriodicalId":50103,"journal":{"name":"Journal of Optical Communications and Networking","volume":"17 9","pages":"D43-D52"},"PeriodicalIF":4.0,"publicationDate":"2025-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144623872","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0