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Electronics
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State-of-the-Art in Wireless Edge Networks
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State-of-the-Art in Wireless Edge Networks

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Microwave and Wireless Communications".

Deadline for manuscript submissions: closed (15 April 2023) | Viewed by 1927

Special Issue Editors

Dr. Minseok Choi

E-Mail Website
Guest Editor
Electronics Engineering, Kyung Hee University, Yongin 17104, Korea
Interests: distributed system wireless caching network; federated learning; edge computing system; stochastic network optimization; Markov decision process (reinforcement learning)
Dr. Joongheon Kim

E-Mail Website
Guest Editor
School of Electrical Engineering, Korea University, Seoul 02841, Korea
Interests: deep reinforcement learning; mobile platforms; energy-efficient computing
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

As edge servers and devices evolve in storage, computing, and processing capabilities, the paradigm of centralized networks is shifting to decentralized ones. In decentralized or distributed wireless networks, various wireless edge technologies have been largely developed to reduce service delays and excessive data traffic on the core network by efficiently utilizing improved resources and capabilities of storage, computing, and processing at the wireless edge. Representatively, with the development of memory and non-memory semiconductors, wireless caching and edge computing technologies have been extensively researched. Also, improved deep learning algorithms allow distributed learning, in which edge devices can train the deep neural network by themselves to contribute the global model training. Incorporating these recent wireless edge technologies, a novel wireless edge network is expected to control tradeoffs among various performance indicators and to optimize multiple tasks, such as communications, caching, computing, and learning. For this goal, this Special Issue aims to bring together researchers, industry practitioners, and individuals working on these related areas to share their new ideas, latest findings, and state-of-the-art results.

This Special Issue includes fundamental analyses and proposals of state-of-the-arts in wireless edge technologies, such as edge computing, wireless caching, and distributed learning, for a variety of application scenarios, such as cellular networks, Internet-of-Things, content delivery networks, vehicle-to-everything (V2X), distributed smart grids, etc.

You may choose our Joint Special Issue in Network.   

Dr. Minseok Choi
Dr. Joongheon Kim 
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Electronics is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • edge computing system for wireless edge
  • wireless caching network
  • distributed learning and federated learning
  • video streaming in wireless edge networks
  • artificial intelligence-assisted wireless edge networks
  • decentralized network optimization
  • wireless edge technologies for Internet-of-Things, vehicle-to-everything (V2X), and distributed smart grids
  • network architectures and protocols for wireless edge
  • distributed system incorporating caching, computing, federated learning, blockchain, etc.

Published Papers (1 paper)

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Research

18 pages, 939 KiB  
Article
HRFP: Highly Relevant Frequent Patterns-Based Prefetching and Caching Algorithms for Distributed File Systems
by Anusha Nalajala, T. Ragunathan, Ranesh Naha and Sudheer Kumar Battula
Electronics 2023, 12(5), 1183; https://doi.org/10.3390/electronics12051183 - 1 Mar 2023
Viewed by 1360
Abstract
Data-intensive applications are generating massive amounts of data which is stored on cloud computing platforms where distributed file systems are utilized for storage at the back end. Most users of those applications deployed on cloud computing systems read data more often than they [...] Read more.
Data-intensive applications are generating massive amounts of data which is stored on cloud computing platforms where distributed file systems are utilized for storage at the back end. Most users of those applications deployed on cloud computing systems read data more often than they write. Hence, enhancing the performance of read operations is an important research issue. Prefetching and caching are used as important techniques in the context of distributed file systems to improve the performance of read operations. In this research, we introduced a novel highly relevant frequent patterns (HRFP)-based algorithm that prefetches content from the distributed file system environment and stores it in the client-side caches that are present in the same environment. We have also introduced a new replacement policy and an efficient migration technique for moving the patterns from the main memory caches to the caches present in the solid-state devices based on a new metric namely the relevancy of the patterns. According to the simulation results, the proposed approach outperformed other algorithms that have been suggested in the literature by a minimum of 15% and a maximum of 53%. Full article
(This article belongs to the Special Issue State-of-the-Art in Wireless Edge Networks)
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