On Packet Reordering in Time-Sensitive Networks

Mohammadpour, Ehsan; Boudec, Jean-Yves Le

doi:10.1109/tnet.2021.3129590

Cited by 12 publications

(3 citation statements)

References 31 publications

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“…However, this method overlooks the negative impact of reordering on worst-case delay and delay jitter. Mohammadpour et al [ 42 ] investigated the influence of packet reordering on worst-case delay and delay jitter. They demonstrated that, if the flow remains lossless between the source node and the reordering buffer, the buffer itself will not contribute to an increase in worst-case delay and delay jitter.…”

Section: Related Workmentioning

confidence: 99%

Enhanced FRER Mechanism in Time-Sensitive Networking for Reliable Edge Computing

Hu,

Cai,

Wang

et al. 2024

Sensors

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Time-Sensitive Networking (TSN) and edge computing are promising networking technologies for the future of the Industrial Internet. TSN provides a reliable and deterministic low-latency communication service for edge computing. The Frame Replication and Elimination for Reliability (FRER) mechanism is important for improving the network reliability of TSN. It achieves high reliability by transmitting identical frames in parallel on two disjoint paths, while eliminating duplicated frames at the destination node. However, there are two problems with the FRER mechanism. One problem is that it does not consider the path reliability, and the other one is that it is difficult to find two completely disjoint path pairs in some cases. To solve the above problems, this paper proposes a method to find edge-disjoint path pairs considering path reliability for FRER in TSN. The method includes two parts: one is building a reliability model for paths, and the other one is computing a working path and a redundant path with the Edge-Disjoint Path Pairs Selection (EDPPS) algorithm. Theoretical and simulation results show that the proposed method effectively improves path reliability while reducing the delay jitter of frames. Compared with the traditional FRER mechanism, the proposed method reduces delay jitter by 15.6% when the network load is 0.9.

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Section: Related Workmentioning

confidence: 99%

Enhanced FRER Mechanism in Time-Sensitive Networking for Reliable Edge Computing

Hu,

Cai,

Wang

et al. 2024

Sensors

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show abstract

“…Thus, packet reordering sensitive MM makes sure that packet order is retained even under handovers and network changes. However, it has been shown that packet reordering increases the delay and jitter [71]. Smart buffering and packet marking can be utilized to reorder packets that may go out of order during handover using FPMIPv6 to mark end of delivery for new and old paths [72].…”

Section: Packet Reordering (Pr) Sensitivementioning

confidence: 99%

A Review on Deploying Blockchain Technology for Network Mobility Management

Wijesekara

2024

International Transactions on Electrical Engineering and Comput

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In wireless mobile networks, Mobility Management (MM) is a critical aspect that involves different tasks such as handover management, location management, offloading, resource allocation, and others. Blockchain platform comprising of an array of linked blocks innately supports the incorruptibility, sustaining the authenticity, and sustain pseudonymous privacy. Traditional MM is centralized, in contrast to blockchain-grounded MM that is partially or fully decentralized in its approach. As the inaugural researchers to review on blockchain-grounded MM, we are proud to cluster the blockchain-grounded MM concept under 7 clusters and closely study each framework with respect to different aspects such as blockchain specific parameters, MM specific parameters, network parameters, and more. We gathered a sample of 92 source references by curating the articles for eligibility criteria examined from electronic archives utilizing a comprehensive and enduring way. Grounded on this inspection, blockchain-grounded MM reinforces the overall security, trust, and privacy of location management and resource allocation, blockchain-grounded secure handover, facilitating registration and authentication, automatic MM utilizing smart contracts, reducing vulnerabilities, repairing low quality data, coordination, fair scheduling, in offloading, and blockchain-grounded resource allocation. Close studying proves that out of blockchain grounded MM frameworks, 37.5% utilize blockchain grounded secure handover, 92.5% utilize simple blockchain architecture, 32.5% utilize PoW consensus, 100% distributed MM, 97.5% host grounded MM, 95% packet reordering tolerant MM, 52.5% QoS aware MM, and 12.5% proposed for 5G networks. Finally, we present the openings and obstructions of the concept of blockchain-grounded MM and then catering surmounting advices.

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“…This strategy considers the attributes of the entire flow, such as real-time performance of links, load balancing, and ordered packet transmission. Based on this information, a data allocation scheduling model is constructed, and strategies are implemented to improve congestion conditions of subflows, reduce performance differences between concurrent links, minimize packet reordering, and prevent receiver buffer congestion [61]. Strategies at the flow level include Direct Hashing (DH), Table-based Hashing (TH), Highest Random Weight (HRW), etc.…”

Section: Prediction Based On Flow-level Traffic Allocationmentioning

confidence: 99%

Packet Reordering in the Era of 6G: Techniques, Challenges, and Applications

Lin¹,

Zhang²,

Gao³

et al. 2023

Electronics

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The advent of sixth-generation (6G) networks brings unmatched speed, reliability, and capacity for massive connections, making it a cornerstone for revolutionary applications. One such application is in vehicular networks, which have their unique demands and complexities. Specifically, they face the complex issue of packet reordering due to the high-speed movement of vehicles and frequent switching of network connections. This paper examines the impact and causes of packet reordering, its threats to network efficiency, and potential countermeasures, particularly in the context of 6G-enabled vehicular networks. We introduce end-to-end methods and metrics to address packet reordering in 6G, discussing the development trends and application prospects. Our findings highlight the emergence of sophisticated strategies, such as prediction and avoidance, to manage packet reordering. They also reveal potential applications to boost network reliability, emulate traffic distributions, and enhance data security. Furthermore, we anticipate a growing integration of machine learning and data-driven optimization in tackling packet reordering. The insights provided aim to influence the future design and optimization of 6G networks, particularly concerning packet management and performance. This paper aims to assist researchers and practitioners in effectively leveraging packet reordering to promote efficient and secure operations of future 6G networks.

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On Packet Reordering in Time-Sensitive Networks

Cited by 12 publications

References 31 publications

Enhanced FRER Mechanism in Time-Sensitive Networking for Reliable Edge Computing

Enhanced FRER Mechanism in Time-Sensitive Networking for Reliable Edge Computing

A Review on Deploying Blockchain Technology for Network Mobility Management

Packet Reordering in the Era of 6G: Techniques, Challenges, and Applications

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