Advances in Scalable Computing Services

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Computing and Artificial Intelligence".

Deadline for manuscript submissions: closed (20 July 2022) | Viewed by 6730

Special Issue Editor

Center for Informatics and Computing Science, Ruđer Bošković Institute, 10000 Zagreb, Croatia
Interests: dew computing; ccalable services; fog computing; cloud computing
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

This Special Issue is devoted to Dew Computing as a new post-cloud computing model which appeared in 2015. While cloud computing uses centralized servers to provide various services, Dew computing uses on-premises computers to provide decentralized, cloud-friendly, and collaborative services to end-users. Dew Computing depends on a Dew–Fog–Cloud vertical scalable service hierarchy. Dew Computing performs several critical functions, such as device connectivity, protocol translation, data filtering and processing, security, updating, management, and more. Newer Dew Computing also operates as a platform for application codes that process data and become an intelligent part of an edge-device-enabled system.

The key features of Dew computing are that on-premises computers provide functionality independent of cloud services and also collaborate with cloud services. Briefly speaking, Dew computing is an organized way of using local computers in the age of cloud computing.

This Special Issue intends to gather the latest research and development results on the Dew Computing paradigm. It seeks original contributions, which demonstrate the theoretical and practical progress of Dew Computing, as well as implementation experiences from researchers in the area of Dew Computing, including but not limited to the following topics:

  • Low-end distributed systems;
  • Dew computing theory and vision;
  • Dew computing structure and architecture;
  • Dew, Cloudn and Fog computing integration and/or interrelation;
  • Dew computing and IoT, ubiquitous computing;
  • Dew computing and databases;
  • Dew computing and blockchain;
  • Dew computing and networks;
  • Dew computing protocols and security;
  • Dew computing applications.

Prof. Dr. Karolj Skala
Guest Editor

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. Applied Sciences 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.

Published Papers (4 papers)

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Research

10 pages, 898 KiB  
Article
Scalable Dew Computing
Appl. Sci. 2022, 12(19), 9510; https://doi.org/10.3390/app12199510 - 22 Sep 2022
Cited by 2 | Viewed by 1622
Abstract
Dew computing differs from the classical cloud and edge computing by bringing devices closer to the end-users and adding autonomous processing independent from the Internet, but it is still able to collaborate with other devices to exchange information on the Internet. The difference [...] Read more.
Dew computing differs from the classical cloud and edge computing by bringing devices closer to the end-users and adding autonomous processing independent from the Internet, but it is still able to collaborate with other devices to exchange information on the Internet. The difference is expressed also on scalability, since edge and cloud providers can provide (almost endless) resources, and in the case of dew computing the scalability needs to be realized on the level of devices, instead of servers. In this paper, we introduce an approach to provide deviceless and thingless computing and ensure scalable dew computing. The deviceless approach allows functions to be executed on nearby devices found closer to the user, and the thingless approach goes even further, providing scalability on a low-level infrastructure that consists of multiple things, such as IoT devices. These approaches introduce the distribution of computing to other smart devices or things on a lower architectural level. Such an approach enhances the existing dew computing architectural model as a sophisticated platform for future generation IoT systems. Full article
(This article belongs to the Special Issue Advances in Scalable Computing Services)
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24 pages, 1826 KiB  
Article
Internet of Things Aware Secure Dew Computing Architecture for Distributed Hotspot Network: A Conceptual Study
Appl. Sci. 2022, 12(18), 8963; https://doi.org/10.3390/app12188963 - 06 Sep 2022
Cited by 5 | Viewed by 1882
Abstract
Building a widely distributed hotspot network is a very tedious task due to its complexity. Providing security, fully distributed network services, and a cost-conscious impact are the major challenges behind this goal. To overcome these issues, we have presented a novel distributed hotspot [...] Read more.
Building a widely distributed hotspot network is a very tedious task due to its complexity. Providing security, fully distributed network services, and a cost-conscious impact are the major challenges behind this goal. To overcome these issues, we have presented a novel distributed hotspot network architecture with five layers that can provide large-scale hotspot coverage as an assimilated result. Our contributions to this new architecture highlight important aspects. First, scalability can be increased by including many Internet of Things (IoT) devices with sensors and Wi-Fi and/or LoraWAN connectivity modules. Second, hotspot owners can rent out their hotspots to create a distributed hotspot network in which the hotspots can act as an ordinary data gateway, a full-fledged hotspot miner, and a light-weight hotspot miner to earn crypto tokens as rewards for certain activities. Third, the advantages of Wi-Fi and LoraWAN can be seamlessly leveraged to achieve optimal coverage, higher network security, and suitable data transmission rate for transferring sensor data from IoT devices to remote application servers and users. Fourth, blockchain is used to enhance the decentralized behavior of the architecture that is presented here by providing immutability and independence from a centralized regulator and making the network architecture more reliable and transparent. The main feature of our paper is the use of the dew-computing paradigm along with hotspots to improve availability, Internet backhaul-agnostic network coverage, and synchronous update capability, and dew-aware leasing to strengthen and improve coverage. We also discuss the key challenges and future roadmap that require further investment and deployment. Full article
(This article belongs to the Special Issue Advances in Scalable Computing Services)
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12 pages, 908 KiB  
Article
Modeling Dew Computing in DISSECT-CF-Fog
Appl. Sci. 2022, 12(17), 8809; https://doi.org/10.3390/app12178809 - 01 Sep 2022
Cited by 1 | Viewed by 1039
Abstract
Fog computing provides an effective solution to various problems by extending the cloud’s functionality to typically more limited computing units closer to user devices. Fog computing can provide a higher level of user experience due to its geographic and network topology location and [...] Read more.
Fog computing provides an effective solution to various problems by extending the cloud’s functionality to typically more limited computing units closer to user devices. Fog computing can provide a higher level of user experience due to its geographic and network topology location and distribution. IoT services also need to be managed seamlessly to ensure adequate QoS (due to the mobility of devices or the temporary periods without an internet connection). Such domains are combined under the auspices of Dew computing, as in critical cases, extending an IoT service to the end user’s device is a feasible task. Such scenarios can hardly be investigated at a large scale due to the lack of dedicated simulation environments. In this paper, we present an extension of the DISSECT-CF-Fog simulator with a Dew computing model, to enable the simulation of IoT-Dew-Fog systems in a cost-effective manner. In particular, we focus on service migration options for mobile devices and cases with temporary internet access limitations. Finally, we performed measurements of real-world use cases with the extended simulator as an evaluation. Our simulation results show that the proposed proactive strategy reduces the processing time of IoT data, exploiting an IoT-Dew-Fog environment. Full article
(This article belongs to the Special Issue Advances in Scalable Computing Services)
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15 pages, 5173 KiB  
Article
A Grant-Free Random Access Process for Low-End Distribution System Using Deep Neural Network
Appl. Sci. 2022, 12(14), 7070; https://doi.org/10.3390/app12147070 - 13 Jul 2022
Viewed by 938
Abstract
With the rising number of Internet of Things (IoT) devices joining the communication network, data exchange is increased tremendously resulting in network congestion. This paper deals with the optimal transmission of IoT devices to maximize the chances of success in random access procedures. [...] Read more.
With the rising number of Internet of Things (IoT) devices joining the communication network, data exchange is increased tremendously resulting in network congestion. This paper deals with the optimal transmission of IoT devices to maximize the chances of success in random access procedures. With every machine trying to use the network for the transfer of data, IoT devices pose serious challenges to the already deployed infrastructure network. With a huge number of IoT devices and fixed limited resources, the existing handshaking-based random access process is not effective. To address this research gap, we propose a grant-free procedure while considering orthogonal transmission and devise a strategy to minimize collisions and idle events and maximize success. We use deep neural networks (DNN) that take channel conditions as an input to predict the device’s transmission for a successful maximization. In order to evaluate the performance of our proposed algorithm, we calculated the average delay with respect to channel coefficient and arrival rate in addition to the number of successes against the channel coefficient. Simulation results show that the proposed algorithm performs well and conforms with the claim of a successful maximization. Full article
(This article belongs to the Special Issue Advances in Scalable Computing Services)
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