A Smart Collaborative Routing Protocol for Delay Sensitive Applications in Industrial IoT

Zhu, Mingqiang; Liu, Chang; Wang, Nan; You, Ilsun

doi:10.1109/access.2019.2963723

Cited by 26 publications

(12 citation statements)

References 26 publications

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“…The KTRP Method: In paper [16], a routing protocol has been suggested by considering low delay times and high reliability to replace the mixed link scenarios. In this method, first One-step delay model has been introduced for analyzing the possible delays in the Media Access Control (MAC) layer parameters.…”

Section: Sdn Based Methodmentioning

confidence: 99%

A Hierarchical Routing Method based on Fog Technology using the Grey system Theory in Internet of Things

Akbari¹,

Barati²,

Barati³

2020

Preprint

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Considering the great growth of IoT networks and the need for highly reliable networks and also considering the manufacturing divides of IoT equipment which are highly limited by their memory, processing power and battery; we need a highly efficient routing for guaranteeing our network's high life span. So, this paper has suggested an efficient energy routing method based on the overlapping clustering method which is inspired from the Grey theory. The Overlap clustering method means that some Things collect data that must be sent to two or more Fog nodes for processing. In the suggested method the best node is selected as the cluster head based on factors such as remaining energy, distance, link expiration time, signal power for receiving data from things by the Fog nodes. In the next step the Fog node's data are sent in a hierarchical method using a symmetrical tree of processed data to the server. Thus, the main issue here is making using a proper routing method for data sending to the Cloud that doesn't just focus on energy, but also considers other factors such as delay and network life span. The simulation results show that the HR-IoT reduces the average end to end delay more than 17.2% and 23.1%, decreases the response time more than 20.1% and 25.78% and increase packet delivery rate more than 23.1% and 28.78% and lifetime more than 25.1% and 28.78% compared to EECRP and ERGID approaches.

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Section: Sdn Based Methodmentioning

confidence: 99%

A Hierarchical Routing Method based on Fog Technology using the Grey system Theory in Internet of Things

Akbari¹,

Barati²,

Barati³

2020

Preprint

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“…Based on the analysis of existing solutions for QoS routing in IoT and WSN [ 28 , 29 , 30 , 31 , 32 , 33 , 34 , 35 ], the classification of the main types of solutions to ensure the Quality of Service level in telecommunication networks that support and maintain them has been performed ( Table 1 ).…”

Section: Related Research Analysismentioning

confidence: 99%

“…Additionally, all considered solutions can be divided into two broad categories: heuristic and optimization [ 28 , 29 , 30 , 31 , 32 , 33 , 34 , 35 ]. The most promising is precisely the optimization approach, which, when solving QoS routing problems, is aimed at optimal network resources.…”

Section: Related Research Analysismentioning

confidence: 99%

Research and Development of Delay-Sensitive Routing Tensor Model in IoT Core Networks

Lemeshko

Papán

Yeremenko

et al. 2021

Sensors

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In the article, we present the research and development of an improved delay-sensitive routing tensor model for the core of the IoT network. The flow-based tensor model is considered within the coordinate system of interpolar paths and internal node pairs. The advantage of the presented model is the application for IoT architectures to ensure the Quality of Service under the parameters of bandwidth, average end-to-end delay, and the probability of packet loss. Hence, the technical task of delay-sensitive routing is formulated as the optimization problem together with constraints and conditions imposed on the corresponding routing variables. The system of optimality criteria is chosen for an investigation. Each selected criterion concerning the specifics of the demanded routing problem solution aims at the optimal use of available network resources and the improvement of QoS indicators, namely, average end-to-end delay. The analysis of the obtained routing solutions under different criteria is performed. Numerical research of the improved delay-sensitive routing tensor model allowed us to discover its features and proved the adequacy of the results for the multipath order of routing.

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“…Security is divided into network, software, and hardware security. Network security aims to minimize the impact of unauthorized external disturbances by utilizing specific communication protocols [23][24][25][26][27]. Software security prevents other systems from accessing IIoT systems including sensors, gateways, and legacy systems.…”

Section: Functionalities For Centralized Iiot Data-acquisition Middlewarementioning

confidence: 99%

A Survey of Industrial Internet of Things Platforms for Establishing Centralized Data-Acquisition Middleware: Categorization, Experiment, and Challenges

Kwon

Heo

et al. 2021

Scientific Programming

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The development of industrial Internet of Things (IIoT), big data, and artificial intelligence technologies is leading to a major change in the production system. The change is being propagated into the wave of transforming the existing system with a vertical structure into the corresponding horizontal platform or middleware. Accordingly, the way of acquiring IIoT data from an individual system is being altered to the way of being increasingly centralized through an integrated middleware of a scalable server or through a large platform. That said, middleware-based IIoT data acquisition must consider multiple factors, such as infrastructure (e.g., operation environment and network), protocol heterogeneity, interoperability (e.g., links with legacy systems), real-time, and security. This manuscript explains these five aspects in detail and provides a taxonomy of eighteen state-of-the-art IIoT data-acquisition middleware systems based on these aspects. To validate one of these aspects (network), we present our evaluation results at a real production site where IIoT data-acquisition loss rates are compared between wireless (long-term evolution) and wired networks. As a result, the wired communication can be more suitable for centralized IIoT data-acquisition middleware than wireless networks. Finally, we discuss several challenges in establishing the best IIoT data-acquisition middleware in a centralized way.

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A Smart Collaborative Routing Protocol for Delay Sensitive Applications in Industrial IoT

Cited by 26 publications

References 26 publications

A Hierarchical Routing Method based on Fog Technology using the Grey system Theory in Internet of Things

A Hierarchical Routing Method based on Fog Technology using the Grey system Theory in Internet of Things

Research and Development of Delay-Sensitive Routing Tensor Model in IoT Core Networks

A Survey of Industrial Internet of Things Platforms for Establishing Centralized Data-Acquisition Middleware: Categorization, Experiment, and Challenges

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