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Multimodal Multitask control Plane Verification Framework

IEEE TRANSACTIONS ON NETWORK AND SERVICE MANAGEMENT 2024年第6期21卷 6684-6702页

作者： Dai, Yuqi Zhang, Hua Wang, Jingyu Liao, Jianxin Southeast Univ Natl Mobile Commun Res Lab Nanjing 211111 Peoples R China Beijing Univ Posts & Telecommun State Key Lab Networking & Switching Technol Beijing 100876 Peoples R China

Modern networks are susceptible to configuration errors, such as misconfigurations and policy conflicts due to the complex interactions of diverse devices through various protocols. control plane verification offers an effective solution to prevent these errors. However, existing tools face several challenges: (i) prolonged verification times, (ii) the verification of only specific policies, and (iii) poor robustness against node and link failures. To address these issues, we propose a control plane verification framework based on a multimodal multitask learning model. This framework enables simultaneous verification of multiple policies directly from various network configuration files. The learning model utilizes modality fusion techniques to capture both topology-related and traffic-related network features. It is trained on datasets augmented with the failure model to enhance robustness against failures. We compare our framework with three state-of-the-art verification tools: Minesweeper, Hoyan, and Tiramisu. Our evaluation shows that our framework is 2600 times faster than Minesweeper, twice as fast as Hoyan, and 19 times faster than Tiramisu, while maintaining 100% verification accuracy. Furthermore, our framework excels in verifying traffic-related network policies and remains effective even under node and link failures.

关键词： Robustness scalability Accuracy Task analysis Routing protocols Feature extraction Cognition control plane verification configuration verification multimodal multitask learning

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A Reinforcement Learning Based Data Storage and traffic Management in Information-Centric Data Center networks

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MOBILE networks & APPLICATIONS 2022年第1期27卷 266-275页

作者： Yang, Weihong Qin, Yang Yang, ZhaoZheng Harbin Inst Technol Shenzhen Dept Comp Sci Shenzhen Peoples R China

Data Center networks (DCN), a core infrastructure of cloud computing, place heavy demands on efficient storage and management of massive data. The data storage scheme, which decides how to assign data to nodes for storage, has a significant impact on the performance of the data center. However, most of the existing solutions focus on where to store the data (i.e., the selection of storage node) but have not considered how to store them (i.e., the traffic management such as routing and transmission rate adjustment). By leveraging the Information-Centric networks (ICN) architecture, this paper tackles the data storage and traffic management issue in Information-Centric Data Center networks (ICDCN) based on Reinforcement Learning (RL) method, since RL has been developed as a promising solution to address dynamic network issues. We present a global optimization of joint traffic management and data storage and then solve it by the distributed multi-agent Q-learning. In ICDCN, the data is routed based on the data's name, which achieves better routing scalability by decoupling the data and its physical location. Compared with ip's stateless forwarding plane, the stateful forwarding information maintained at every node supports adaptively routing and hop-by-hop traffic control by using the Q-learning method. We evaluate our proposal on an NS-3-based simulator, and the results show that the proposed scheme can effectively reduce transmission time and increase throughput while achieving load-balanced among servers.

关键词： Information-centric data center networks Data storage traffic management Distributed Q-learning

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[Invited Paper] Time Gating control Approaches for Time Critical Applications from Perspective of Wireless LANs and All Optical networks

[Invited Paper] Time Gating Control Approaches for Time Crit...

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International Conference on Computing, Networking and Communications (ICNC)

作者： Tode, Hideki Tanigawa, Yosuke Yeu, Ratha Hasegawa, Akio Osaka Metropolitan Univ Dept Core Informat Grad Sch Informat Sakai Osaka 5998531 Japan Adv Telecommun Res Inst Int Seika Cho Kyoto 6190288 Japan

ISBN: (纸本)9798350371000;9798350370997

In recent years, with the proliferation of diverse time-critical applications, there is a growing need for technologies that can limit packet transmission delays within acceptable bounds while also maintaining low packet loss rates. This paper addresses this challenge by introducing the concept of Time-Gating control. In particular, it aims to maintain compatibility with existing information network infrastructures like TCP/ip and CSMA/CA, ensuring low cost and high scalability. Initially, the paper focuses on wireless access networks in smart factory environments, proposing a method that introduces a hierarchical time-unit structure for periodic traffic, such as sensor data and surveillance video. This method determines time widths for the overlap-free transmission of varied periodic communications, thereby facilitating temporal load distribution. We present results from functional verification tests conducted using a software prototype in this environment. Furthermore, as a solution for nonpediodic traffic with permissive delay constraints, an overview of a virtual slot-based CSMA/CA method is introduced. In addition, targeting completely different applications, we explore the implementation of Time-Gating control in All Optical Packet Switching networks within Beyond 5G access-metro and data center networks. Here, we design a new TCP transmission method incorporating this control mechanism and discuss its advantages and superior performance.

关键词： Transmission control protocol

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Digital Subcarrier Multiplexing: Enabling Software-Configurable Optical networks

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JOURNAL OF LIGHTWAVE TECHNOLOGY 2023年第4期41卷 1175-1191页

作者： Welch, Dave Napoli, Antonio Back, Johan Buggaveeti, Sanketh Castro, Carlos Chase, Aaron Chen, Xi Dominic, Vince Duthel, Thomas Eriksson, Tobias A. Erkilinc, Sezer Evans, Peter Fludger, Chris R. S. Foo, Ben Frost, Thomas Gavrilovic, Paul Hand, Steven J. Kakkar, Aditya Kumpera, Ales Lal, Vikrant Maher, Robert Marques, Fabio Masoud, Fady Mathur, Atul Milano, Ray Olmedo, Miguel Iglesias Olson, Magnus Pavinski, Don Pedro, Joao Rashidinejad, Amir Samra, Parmijit Sande, Warren Somani, Azmina Sun, Han Swenson, Norman Tsai, Huan-Shang Yekani, Amin Zhang, Jiaming Ziari, Mehrdad Infinera Corp 6373 San Ignacio Ave San Jose CA 95119 USA Infinera D-81541 Munich Germany Infinera S-11743 Stockholm Sweden Infinera Unipessoal Lda P-2790078 Carnaxide Portugal Infinera Ottawa ON K2K 2X3 Canada Infinera Corp Allentown PA 18106 USA

The various topologies, traffic patterns and cost targets of optical networks have prevented the deployment of end-to-end solutions across multi-domains, and the optimization of the network as a whole. The consequent limitations in flexibility, scalability, and adaptability of optical networks will become increasingly important with new applications, such as 5G/6G. Coherent transceivers based on digital subcarrier multiplexing (DSCM) are proposed to address these current constraints. In particular, DSCM allows (i) the design of high-capacity point-to-point (P2P) and -multipoint (P2MP) optical networks;(ii) simplified aggregation with passive optics;and (iii) connections between low- and high-speed transceivers. Furthermore, DSCM-based networks reduce the number of opto-electro-opto stages, halve the number of bookended transceivers, and provide a better match for existing hub-and-spoke (H&S) traffic patterns in fast-growing and dynamic access/metro segments. A DSCM-based transceiver will pave the way for the deployment of next-generation flexible, adaptable, and scalable software-configurable optical networks. Key steps and elements to realize this solution are laid out, and promising applications outlined. The first real-time experimental results of coherent P2MP transceivers are presented.

关键词： Transceivers Point-to-multipoint communications traffic control Passive optical networks Costs Optical transmitters OFDM Digital subcarrier multiplexing point-to-multipoint coherent access metro aggregation fronthaul 5G

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QSCCP: A QoS-Aware Congestion control Protocol for Information-Centric Networking

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IEEE TRANSACTIONS ON NETWORK AND SERVICE MANAGEMENT 2025年第1期22卷 532-556页

作者： Bai, He Li, Hui Que, Jianming Smahi, Abla Zhang, Minglong Chongx, Peter Han Joo Li, Shuo-Yen Robert Wang, Xiyu Lu, Ping Peking Univ Sch Elect & Comp Engn Guangdong Prov Key Lab Ultra High Definit Immers M Shenzhen 518055 Peoples R China Fuyao Univ Sci & Technol Sch Comp Sci Fuzhou 350109 Peoples R China Mississippi State Univ Dept Elect & Comp Engn Starkville MS 39762 USA Auckland Univ Technol Dept Elect & Elect Engn Auckland 1010 New Zealand Univ Elect Sci & Technol China Natl Key Lab Sci & Technol Commun Chengdu 610054 Peoples R China ZTE Corp Cent R&D Inst Shenzhen 518057 Peoples R China ZTE Corp Dept Ind Digitalizat Solut Shenzhen 518057 Peoples R China

Information-Centric Networking (ICN) is a promising future network architecture that shifts the host-based network paradigm to a content-oriented one. Over the past decade, numerous ICN congestion control (CC) schemes have been proposed, tailored to address congestion issues based on ICN's transmission characteristics. However, several key challenges still need to be addressed. One critical issue is that most existing CC studies for ICN do not consider the diverse Quality of Service (QoS) requirements of modern network applications. This limitation hinders their applicability across various applications with different network performance preferences. Another ongoing challenge lies in improving transmission performance, particularly considering how to appropriately coordinate congestion control participants to enhance content retrieval efficiency and ensure reasonable resource allocation, especially in multipath scenarios. To tackle these challenges, we propose QSCCP, a QoS-aware congestion control protocol built upon NDN (Named Data Networking), a well-known ICN architecture. In QSCCP, diverse QoS preferences of various traffic are supported within a collaborative congestion control framework. A novel multi-level, class-based scheduling and forwarding mechanism is designed to ensure varied and fine-grained QoS guarantees. A distributed congestion notification and precise feedback mechanism is also provided, which efficiently collaborates with an adaptive multipath forwarding strategy and consumer rate adjustment to rationally allocate network resources and improve transmission efficiency, particularly in multipath scenarios. Extensive experimental results demonstrate that QSCCP satisfies diverse QoS requirements while achieving outstanding transmission performance. It outperforms existing schemes in throughput, fairness, delay, and packet loss, with a rapid convergence rate and excellent stability.

关键词： Quality of service Protocols Resource management Packet loss Receivers scalability Information-centric networking ip networks Diffserv networks Collaboration Information-centric networks congestion control transport protocol quality of service (QoS)

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Wireless-Aware TSN Engineering: Implications for 5G and Upcoming 6G networks

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IEEE NETWORK 2025年第3期39卷 99-107页

作者： Egger, Simon Duerr, Frank Varga, Balazs De Andrade, Marilet Sharma, Gourav Prateek Sachs, Joachim Harmatos, Janos Gross, James Univ Stuttgart Inst Parallel & Distributed Syst D-70569 Stuttgart Germany Ericsson Res H-1117 Budapest Hungary Ericsson Res S-16440 Stockholm Sweden KTH Royal Inst Technol Sch Elect Engn & Comp Sci S-11428 Stockholm Sweden Ericsson Res Aachen D-52134 Germany

The importance of time- and mission-critical applications is increasing as industries and society are advancing in their digitalization. As such applications introduce stringent quality of service (QoS) requirements on the underlying network infrastructure, open standards like time-sensitive networking (TSN) and DetNet are being developed to provide dependable and time-sensitive communication in bridged LAN networks and ip networks, respectively. More recently, the extension to support wireless time-sensitive connectivity has received special interest due to improved network deployment flexibility with mobile devices. These efforts have led to the standardized support of TSN/DetNet in 5G, allowing the 5G system and its mobile devices to be integrated transparently into TSN/DetNet networks while conforming to their user and control plane protocols. Nevertheless, the induced packet delays- and in particular the packet delay variations (PDVs)- of 5G are significantly larger than in their wired counterparts. In this work, we illustrate that established methods to configure TSN/DetNet networks insufficiently address major runtime uncertainties, and that they would consequently result in QoS impairments or scalability issues. We therefore advocate for two systematic approaches to improve traffic shaping in this setting: first, we propose Packet Delay Correction where the PDV is corrected within the 5G system. Second, we introduce "wireless-aware" TSN scheduling to account for the packet delay characteristics of 5G. We demonstrate that wireless-aware TSN scheduling and Packet Delay Correction are complementary in their design and can be combined to provide formal end-to-end reliability guarantees at scale. In addition, being a key aspect to support wireless-aware TSN scheduling in 5G and future 6G networks, we introduce a data-driven framework to predict the packet delay characteristics of the wireless systems over a finite time horizon. Finally, we identify open research

关键词： 5G mobile communication Delays Wireless communication Wireless sensor networks Network topology Topology Ethernet Schedules Training Mission critical systems 6G mobile communication

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CoSAF: Toward a Secure Meta-Computing iioT Infrastructure Through Collaborative Source Address Filtering

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IEEE INTERNET OF THINGS JOURNAL 2025年第10期12卷 13709-13722页

作者： Yang, Shu Zhang, Zequn Cui, Laizhong Shenzhen Univ Coll Comp Sci & Software Engn Shenzhen 518060 Peoples R China

The rapid growth of the Industrial Internet of Things (iioT) requires a secure meta-computing environment to support applications like industrial monitoring and remote control. However, this environment faces major security challenges, especially the risk of source address forgery, which can enable DDoS and botnet attacks, disrupting operations and compromising equipment. Current Internet infrastructure forwards packets based only on destination addresses, lacking the capability for source address verification. Although edge-based solutions like firewalls and systems, such as source address validation architecture (SAVA) and source address validation improvement (SAVI), are deployed, they fall short of comprehensive source address validation (SAV), allowing malicious traffic to propagate through core networks. To enhance security, a collaborative approach based on meta-computing principles is needed, allowing routers to verify source addresses cooperatively. Given the impracticality of fully upgrading routers, incremental deployment is essential. We show that optimizing incremental SAV deployment is NP-hard. To address this, we propose collaborative optimized source address filtering (COSAF), a heuristic algorithm that uses a sink-tree structure to effectively filter attack flows and optimize resource allocation. COSAF also takes SAV table capacity into account to improve resource utilization. Extensive simulations demonstrate that COSAF outperforms traditional methods.

关键词： Industrial Internet of Things Source address validation Collaboration ip networks scalability Network topology Faces Denial-of-service attack Resource management Heuristic algorithms Incremental deployment algorithm Industrial Internet of Things (iioT) intradomain meta-computing source address validation (SAV)

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In-Network Quality control of ip Camera Streams 23

In-Network Quality Control of IP Camera Streams

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International Symposium on Theory, Algorithmic Foundations, and Protocol Design for Mobile networks and Mobile Computing (ACM MobiHoc)

作者： Gyorgyi, Csaba Kecskemeti, Karoly Voros, Peter Laki, Sandor Szabo, Geza Eotvos Lorand Univ Budapest Hungary Ericsson Res Budapest Hungary

ISBN: (纸本)9781450399265

Manufacturing processes are often monitored by ip cameras. The generated video streams can be transferred via a wireless link to be processed and used by remote industrial controllers that manage and configure the industrial task in real-time. However, the link has limited bandwidth and is not capable of transmitting the aggregated traffic of all the ip cameras. Moreover, the platform provider of the remote controller (e.g., cloud) might charge extra fees for high volumes of network traffic. To optimize the data transport, we propose an in-network video quality control method for ip camera streams that drops non-essential frames from temporally irrelevant ip camera streams even when bandwidth is available. Our solution introduces a high-level API through which the operator can define which camera streams are needed with high quality at which actuator positions/states of the industrial process. Our method assumes an aggregation point that monitors the actuators' states and reduces the quality of camera streams that are not important for the control process, selectively dropping a set of video frames. We have implemented a P4-based prototype of the aggregation point and show that the remote controller can be fed with high-quality video streams while meeting bandwidth limitations and potentially saving data transfer costs without modifying the end-points.

关键词： P4 Network Exposure Video Quality control In-Network Computing

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Application of E1 Link Bundling Technology in Wide Area networks 6

Application of E1 Link Bundling Technology in Wide Area Netw...

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6th IEEE International Conference on Civil Aviation Safety and Information Technology, ICCASIT 2024

作者： Huang, Yilu Li, Qingyu Liu, Zhen Zhou, Longxiang Satellite Maritime Tracking and Control Department Jiangyin China

ISBN: (纸本)9798350389418

The Wide Area Network serves as the primary network for business traffic, boasting advantages such as extensive connection range, centralized resources, and scalability. E1 links utilize Time Division Multiplexing technology, providing interference-free channels and high link quality. They support flexible binding of time slots to adjust access bandwidth according to user needs, enabling service providers to offer a rich array of ip services on-demand and at lower costs. As a principal type of link for WAN connections, E1 link bundling technology effectively enhances the reliability and flexibility of the network, playing a significant practical role in increasing the capacity for business traffic. © 2024 IEEE.

关键词： Time division multiple access

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Enhancing Security in dynamic IoT networks through Incremental Meta-learning 18

Enhancing Security in dynamic IoT networks through Increment...

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18th IEEE International Conference on Advanced networks and Telecommunications Systems, ANTS 2024

作者： Gopakumar, Megha Sankaran, Sriram Centre for Cybersecurity Systems and Networks Amrita Vishwa Vidyapeetham Amritapuri India

ISBN: (纸本)9798350391725

The widespread adoption of Internet of Things (IoT) devices presents numerous challenges, including security vulnerabilities, scalability, data management, and reliability concerns. Device identification is of paramount importance for addressing these challenges as it serves as a foundation for implementing security measures, a monitoring system to set up access control and regulate device usage within networks. Commonly used device identifiers such as MAC and ip addresses, are vulnerable to spoofing, highlighting the need for techniques such as network traffic-based device behavior analysis. Developing a device identification system for IoT is challenging due to dynamic nature of IoT environments. Further, identifying devices is exacerbated with limited network activity traces. Previous works rely on batch learning models that require extensive labeled data and are unable to adapt to real-time data changes. In this work, we develop an incremental meta-learning framework that uses machine learning to analyze and generalize device behaviors from network traces. Integrating incremental learning algorithms into the framework allows continuous adaptation to evolving data while using meta-learner model ensures efficient model training with limited data. The proposed model outperformed recent works with an accuracy of {8 9. 5 4 %} and provided consistent performance across five stages of incremental training. © 2024 IEEE.

关键词： Adversarial machine learning

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