Resilient virtual communication networks using multi-commodity flow based local optimal mapping

Yang, Qiang; Li, Wei; Souza, José Neuman de; Zomaya, Albert Y.

doi:10.1016/j.jnca.2018.02.022

Cited by 7 publications

(7 citation statements)

References 10 publications

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“…I Bodrog et al [2] I Ali-Tolppa et al [25] I Karim et al [26] I Ahmad et al [27] I Tiwari et al [28] I Yang et al [29] I Al-juaifari et al [30] I Bothe et al [Bothe]…”

Section: Machine Learning and Artificial Intelligencementioning

confidence: 99%

“…The principal challenge of research into self-healing functionality on computer networks is the ability to achieve reliability, one of the three core characteristics of a self-healing system described [27,29]. A method was proposed based on utilising shared operation and spare nodes in each neural network layer to compensate for any faulty node and resolve the self-healing reliability challenge.…”

Section: Network Architecturementioning

confidence: 99%

“…In evaluating self-healing in virtual networks (VN), Ref. [29] presented a multi-commodity flow problem (MFP) network called MFP-VNMH, which can enhance the VN mapping of overall VNs. The proposed approach enables self-healing capabilities on network virtualisation.…”

Section: Network Architecturementioning

confidence: 99%

See 2 more Smart Citations

Self-Healing in Cyber–Physical Systems Using Machine Learning: A Critical Analysis of Theories and Tools

Johnphill,

Sadiq,

Al-Obeidat

et al. 2023

Future Internet

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The rapid advancement of networking, computing, sensing, and control systems has introduced a wide range of cyber threats, including those from new devices deployed during the development of scenarios. With recent advancements in automobiles, medical devices, smart industrial systems, and other technologies, system failures resulting from external attacks or internal process malfunctions are increasingly common. Restoring the system’s stable state requires autonomous intervention through the self-healing process to maintain service quality. This paper, therefore, aims to analyse state of the art and identify where self-healing using machine learning can be applied to cyber–physical systems to enhance security and prevent failures within the system. The paper describes three key components of self-healing functionality in computer systems: anomaly detection, fault alert, and fault auto-remediation. The significance of these components is that self-healing functionality cannot be practical without considering all three. Understanding the self-healing theories that form the guiding principles for implementing these functionalities with real-life implications is crucial. There are strong indications that self-healing functionality in the cyber–physical system is an emerging area of research that holds great promise for the future of computing technology. It has the potential to provide seamless self-organising and self-restoration functionality to cyber–physical systems, leading to increased security of systems and improved user experience. For instance, a functional self-healing system implemented on a power grid will react autonomously when a threat or fault occurs, without requiring human intervention to restore power to communities and preserve critical services after power outages or defects. This paper presents the existing vulnerabilities, threats, and challenges and critically analyses the current self-healing theories and methods that use machine learning for cyber–physical systems.

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“…I Bodrog et al [2] I Ali-Tolppa et al [25] I Karim et al [26] I Ahmad et al [27] I Tiwari et al [28] I Yang et al [29] I Al-juaifari et al [30] I Bothe et al [Bothe]…”

Section: Machine Learning and Artificial Intelligencementioning

confidence: 99%

Section: Network Architecturementioning

confidence: 99%

See 1 more Smart Citation

Self-Healing in Cyber–Physical Systems Using Machine Learning: A Critical Analysis of Theories and Tools

Johnphill,

Sadiq,

Al-Obeidat

et al. 2023

Future Internet

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“…When using our strategy to accelerate convergence, the network can quickly reach a consensus. In [42,43], the authors explained the reasons for the fluctuations and the process of convergence through theoretical derivation, simple examples, and experimental proofs.…”

Section: Convergence Time Varies With Network Sizementioning

confidence: 99%

Robust and Fast Converging Cross-Layer Failure Correction in Segment-Routed Networks

2021

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Due to overlay technologies, service providers have a logical view of the underlay network and can optimize the experience quality without modifying the physical network. However, the cross-layer interaction inevitably causes network fluctuation due to their inconsistent optimization objectives. Aside from that, network failures that occur in both layers not only cause network performance degradation but also significantly increase the frequency of cross-layer interaction. These problems make the network fluctuate for a long time, reduce the network performance, and influence the user experience, especially for time-sensitive applications. In this paper, we design a cross-layer architecture in which the logical layer can satisfy the service function chain demands and maximize the user experience and physical layer so it can optimize the overall network performance. Our cross-layer architecture can make proactive corrections in both layers. Furthermore, we investigate the cross-layer interaction and design two strategies to eliminate fluctuations and make the network converge quickly.

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“…If there is a positive matching, the first matching result will provide the action to be conducted over the packet. Currently, three different actions are designed, useful in the context of the Edge-to-Core segment: DROP packet, L1 MIRROR packet and L2 REDI-RECT packet, allowing implementing several use cases such as selective monitoring [39], self-protection [40], intrusion response systems [41] and video optimization [21], among others. Returns the total of rules…”

Section: Match/action Stagementioning

confidence: 99%

Towards an FPGA-Accelerated programmable data path for edge-to-core communications in 5G networks

Ricart‐Sanchez

Malagón

Salvá-García

et al. 2018

Journal of Network and Computer Applications

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Resilient virtual communication networks using multi-commodity flow based local optimal mapping

Cited by 7 publications

References 10 publications

Self-Healing in Cyber–Physical Systems Using Machine Learning: A Critical Analysis of Theories and Tools

Self-Healing in Cyber–Physical Systems Using Machine Learning: A Critical Analysis of Theories and Tools

Robust and Fast Converging Cross-Layer Failure Correction in Segment-Routed Networks

Towards an FPGA-Accelerated programmable data path for edge-to-core communications in 5G networks

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