Network

29 pages, 824 KiB

Open AccessReview

Recent Development of Emerging Indoor Wireless Networks towards 6G

by Sampath Edirisinghe, Orga Galagedarage, Imali Dias and Chathurika Ranaweera

Network 2023, 3(2), 269-297; https://doi.org/10.3390/network3020014 - 12 May 2023

Cited by 8 | Viewed by 3818

Sixth-generation (6G) mobile technology is currently under development, and is envisioned to fulfill the requirements of a fully connected world, providing ubiquitous wireless connectivity for diverse users and emerging applications. Transformative solutions are expected to drive the surge to accommodate a rapidly growing number of intelligent devices and services. In this regard, wireless local area networks (WLANs) have a major role to play in indoor spaces, from supporting explosive growth in high-bandwidth applications to massive sensor arrays with diverse network requirements. Sixth-generation technology is expected to have a superconvergence of networks, including WLANs, to support this growth in applications in multiple dimensions. To this end, this paper comprehensively reviews the latest developments in diverse WLAN technologies, including WiFi, visible light communication, and optical wireless communication networks, as well as their technical capabilities. This paper also discusses how well these emerging WLANs align with supporting 6G requirements. The analyses presented in the paper provide insight into the research opportunities that need to be investigated to overcome the challenges in integrating WLANs in a 6G ecosystem. Full article

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16 pages, 2028 KiB

Open AccessArticle

Clustered Distributed Learning Exploiting Node Centrality and Residual Energy (CINE) in WSNs

by Laura Galluccio, Joannes Sam Mertens and Giacomo Morabito

Network 2023, 3(2), 253-268; https://doi.org/10.3390/network3020013 - 23 Apr 2023

Viewed by 1491

Abstract

With the explosion of big data, the implementation of distributed machine learning mechanisms in wireless sensor networks (WSNs) is becoming required for reducing the number of data traveling throughout the network and for identifying anomalies promptly and reliably. In WSNs, the above need has to be considered along with the limited energy and processing resources available at the nodes. In this paper, we tackle the resulting complex problem by designing a multi-criteria protocol CINE that stands for “Clustered distributed learnIng exploiting Node centrality and residual Energy” for distributed learning in WSNs. More specifically, considering the energy and processing capabilities of nodes, we design a scheme that assumes that nodes are partitioned in clusters and selects a central node in each cluster, called cluster head (CH), that executes the training of the machine learning (ML) model for all the other nodes in the cluster, called cluster members (CMs). In fact, CMs are responsible for executing the inference only. Since the CH role requires the consumption of more resources, the proposed scheme rotates the CH role among all nodes in the cluster. The protocol has been simulated and tested using real environmental data sets. Full article

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14 pages, 922 KiB

Open AccessArticle

Improvement of Network Flow Using Multi-Commodity Flow Problem

by Takato Fukugami and Tomofumi Matsuzawa

Network 2023, 3(2), 239-252; https://doi.org/10.3390/network3020012 - 04 Apr 2023

Viewed by 2321

Abstract

In recent years, Internet traffic has increased due to its widespread use. This can be attributed to the growth of social games on smartphones and video distribution services with increasingly high image quality. In these situations, a routing mechanism is required to control congestion, but most existing routing protocols select a single optimal path. This causes the load to be concentrated on certain links, increasing the risk of congestion. In addition to the optimal path, the network has redundant paths leading to the destination node. In this study, we propose a multipath control with multi-commodity flow problem. Comparing the proposed method with OSPF, which is single-path control, and OSPF-ECMP, which is multipath control, we confirmed that the proposed method records higher packet arrival rates. This is expected to reduce congestion. Full article

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Network, Volume 3, Issue 2 (June 2023) – 3 articles

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