How AI-enabled SDN technologies improve the security and functionality of industrial IoT network: Architectures, enabling technologies, and opportunities

Jiang, Jinfang; Lin, Chuan; Han, Guangjie; Abu‐Mahfouz, Adnan M.; Shah, Syed Bilal Hussain; Martínez-García, Miguel

doi:10.1016/j.dcan.2022.07.001

Cited by 16 publications

(11 citation statements)

References 70 publications

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“…In this paper, the author describes the load-balancing techniques for IoT controllers based on SDN networks for medium data centers. From the results and learning from experience the results show the proposed algorithm works well and reduces time from the switch to the controller [16].…”

Section: Literature Reviewmentioning

confidence: 90%

“…As of now, the delay in IP routing is a trending topic because many new communication devices are being introduced to support IP and internet networks, which are accessible globally at any location in the range [4]. In a recent study, the author presented the main issues in mobile IP which, can be divided into six sections, such as the introduction of mobile IP, modifications to IP protocol to accommodate wireless access to the internet (Mobile IP), the concept of the Triangle Routing Problem in Mobile IP, optimization method and proposed solution and methodology involved in Mobile IP [16]. Some new techniques have been reviewed in this paper, which are implemented in the mobile IP network, and outlined that the mobile services reach almost equal to the desktop speed for the multimedia services [17].…”

Section: Literature Reviewmentioning

confidence: 99%

See 1 more Smart Citation

The Comparison of Routing Algorithm for SDN Network using AI for Future Network

Ahmed,

Siddiqui,

Rizvi

et al. 2024

VAWKUM trans. comput. sci.

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After the invention of new IoT devices the new connection has been added in the network and bulk of data flow in the system. AI is very famous algorithum and software-defined networking (SDN) is new fast network controlling method both can be integrate for fast and secure network-related scenarios and finding great experience and growing interest in the research community. The present network connected to many number of objects over the Internet and present a complex scenario. To ensure security, privacy, confidentiality, and programmability, the architecture of AI and blockchain for SDN network is proposed in this paper. For network service provider this is ample time to apply artificial intelligence (AI) and blockchain (BC) in a software-defined network controller to ensure a secure network control, traffic management and system optimimum performnce. Also for shortest path to reduce delay in the network, the best routing algorithum must be apply in the network. The AI (artificial intelligence) algorithum can help SDN controller to fastdecision to reduced delay and can provide security in the network. In this paper routing algorithm also will be investigate faster Network.

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Section: Literature Reviewmentioning

confidence: 90%

Section: Literature Reviewmentioning

confidence: 99%

The Comparison of Routing Algorithm for SDN Network using AI for Future Network

Ahmed,

Siddiqui,

Rizvi

et al. 2024

VAWKUM trans. comput. sci.

View full text Add to dashboard Cite

show abstract

“…The popularity of AI and unmanned machines arises from the effective, real-time, automated solutions that these technologies provide when placed in hazardous environments. They can detect and isolate possible threats before they cause harm, with less or no human involvement (Palacín et al, 2019;Das et al, 2020;Jiang et al, 2022). Recent advances have been developed for the combination of autonomous robots with sensors that are flexible and easily and remotely deployed in unsafe and toxic environments (Ristic et al, 2017).…”

Section: Maximizing Safety In Hazardous Environments With Ai-driven M...mentioning

confidence: 99%

Artificial intelligence and IoT driven technologies for environmental pollution monitoring and management

Popescu,

Mansoor,

Wani

et al. 2024

Front. Environ. Sci.

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Detecting hazardous substances in the environment is crucial for protecting human wellbeing and ecosystems. As technology continues to advance, artificial intelligence (AI) has emerged as a promising tool for creating sensors that can effectively detect and analyze these hazardous substances. The increasing advancements in information technology have led to a growing interest in utilizing this technology for environmental pollution detection. AI-driven sensor systems, AI and Internet of Things (IoT) can be efficiently used for environmental monitoring, such as those for detecting air pollutants, water contaminants, and soil toxins. With the increasing concerns about the detrimental impact of legacy and emerging hazardous substances on ecosystems and human health, it is necessary to develop advanced monitoring systems that can efficiently detect, analyze, and respond to potential risks. Therefore, this review aims to explore recent advancements in using AI, sensors and IOTs for environmental pollution monitoring, taking into account the complexities of predicting and tracking pollution changes due to the dynamic nature of the environment. Integrating machine learning (ML) methods has the potential to revolutionize environmental science, but it also poses challenges. Important considerations include balancing model performance and interpretability, understanding ML model requirements, selecting appropriate models, and addressing concerns related to data sharing. Through examining these issues, this study seeks to highlight the latest trends in leveraging AI and IOT for environmental pollution monitoring.

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“…In this paper, the authors present a systematic review of SDN security, privacy, and taxonomic issues of cyber-attacks. They also identified the reason for the attacks and their impacts [4]. An overview of AI techniques in the SDN paradigm was presented in this paper.…”

Section: Literature Reviewmentioning

confidence: 99%

The Analysis the Performance of SDN Controller and AI System for Future Network

Ahmed,

Abdul moid,

Ismat

et al. 2024

VAWKUM trans. comput. sci.

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the SDN is new network controller concept and it provide faster packet data receiving and dynamic path in large network. It can work with old systems via creating new nodes. It can monitor activities of traffic routing, flowing and congestion and on the basis of these updated from all routers in the network. It can provide best shortest route to data packet in few seconds. But the main issue is that its location and controlling of huge data. The network controller can be track and data can be hack by hackers. The AI (artificial intelligence) system can help SDN controller to work batter, improve speed of the system and provide security to control network. In this paper, the methods working of AI with SDN controller will be analyzed to make system faster and save from cyber-attack and a solution will be proposed based on analyses of SDN Network.

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How AI-enabled SDN technologies improve the security and functionality of industrial IoT network: Architectures, enabling technologies, and opportunities

Cited by 16 publications

References 70 publications

The Comparison of Routing Algorithm for SDN Network using AI for Future Network

The Comparison of Routing Algorithm for SDN Network using AI for Future Network

Artificial intelligence and IoT driven technologies for environmental pollution monitoring and management

The Analysis the Performance of SDN Controller and AI System for Future Network

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