Collision-free optimal packet scheduling algorithm for multi-hop wireless IoT networks

Kim, Hak-Jin; Kim, Marie S.; Han, Seung-Jae

doi:10.1016/j.comnet.2022.108816

Cited by 7 publications

(2 citation statements)

References 17 publications

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“…Unlike conventional studies that solely address the channel assignment problem, joint works with routing protocols have been proposed [21]- [24]. This problem is also proved to be NP-hard in [23].…”

Section: Related Workmentioning

confidence: 99%

A Conflict-Aware Channel Assignment in Multi-Radio Multi-Channel Wireless Mesh Networks

Shin,

Lee,

Choi

2024

IEEE Access

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This paper proposes a theoretical model-driven channel assignment scheme designed to enhance network performance in multi-radio multi-channel wireless mesh networks. Unlike previous conflict graph-based channel assignments that addressed co-channel interference and hidden terminal problems while overlooking an exposed terminal problem, our proposed approach integrates these problems comprehensively to mitigate network performance degradation. Given a communication graph, we establish a conflict graph based on hop distance for practical implementation. The weighted conflict graph is constructed by analyzing packet collision conditions under the IEEE 802.11 standard with the CSMA/CA protocol, considering not only the transmission range and interference range but also the carrier sensing range simultaneously. Given a weighted conflict graph and available channel lists on each router, we devise a Weighted Soft List Coloring problem to address the channel assignment challenge. We prove the NP-hardness of this problem by establishing its dual problem, Max list-Cut. We present an approximation algorithm with worst-case performance at most twice the optimal solution while preserving network topology. We substantiate the performance of the proposed channel assignment algorithm through simulations in various topologies. The proposed algorithm, on average, demonstrates a network throughput increase of 162% and 174% compared to the greedy heuristic algorithm with 3 channels and 12 channels, respectively.INDEX TERMS Channel assignment in IEEE 802.11 networks, multi-radio and multi-channel, weighted soft list coloring problem, Max list-Cut problem, approximation algorithm.

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Section: Related Workmentioning

confidence: 99%

A Conflict-Aware Channel Assignment in Multi-Radio Multi-Channel Wireless Mesh Networks

Shin,

Lee,

Choi

2024

IEEE Access

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“…FORA can also use WirelessHART or 5G for remote FN installations. In the future, it will be interesting to explore the use of Wireless TSN, as such a solution is envisioned in IEEE 802.11be (WiFi 7) and 5G 3GPP, which have industrial use cases [25].…”

Section: Deterministic Communicationmentioning

confidence: 99%

The FORA European Training Network on Fog Computing for Robotics and Industrial Automation

Barzegaran

Pop

2023

2023 Design, Automation &Amp; Test in Europe Conference &Amp; Exhibition (DATE)

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Fog Computing for Robotics and Industrial Automation, FORA, was a European Training Network which focused on future industrial automation architectures and applications based on an emerging technology, called Fog Computing. The research project focused on research related to Fog Computing with applicability to industrial automation and manufacturing.The main outcome of the FORA project was the development of a deterministic Fog Computing Platform (FCP) to be used for implementing industrial automation and robotics solutions for Industry 4.0. This paper reports on the scientific outcomes of the FORA project. FORA has proposed a reference system architecture for Fog Computing, which was published as an open Architecture Analysis Design Language (AADL) model. The technologies developed in FORA include fog nodes and hypervisors, resource management mechanisms and middleware for deploying scalable Fog Computing applications, while guaranteeing the non-functional properties of the virtualized industrial control applications, and methods and processes for assuring the safety and security of the FCP. Several industrial use cases were used to evaluate the suitability of the FORA FCP for the Industrial IoT area, and to demonstrate how the platform can be used to develop industrial control applications and data analytics applications.

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Variational Quantum Eigensolver for Optimizing Network Scheduling Using QUBO Formulation

Rizvi,

Gondel,

Paracha

et al. 2024

Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Collision-free optimal packet scheduling algorithm for multi-hop wireless IoT networks

Cited by 7 publications

References 17 publications

A Conflict-Aware Channel Assignment in Multi-Radio Multi-Channel Wireless Mesh Networks

A Conflict-Aware Channel Assignment in Multi-Radio Multi-Channel Wireless Mesh Networks

The FORA European Training Network on Fog Computing for Robotics and Industrial Automation

Variational Quantum Eigensolver for Optimizing Network Scheduling Using QUBO Formulation

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