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Smart Cloud Computing Technologies and Application
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Smart Cloud Computing Technologies and Application

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Internet of Things".

Deadline for manuscript submissions: closed (20 October 2021) | Viewed by 17226

Special Issue Editors

Prof. Dr. Meikang Qiu

E-Mail Website
Guest Editor
Texas A&M University, College Station, TX 77843, USA
Interests: Machine Learning; Big Data; Cyber Security; Cloud Computing; IoT; CPS; Smart Computing; Embedded Systems
Dr. Cheng Zhang

E-Mail Website
Guest Editor
School of Fundamental Science and Engineering, Waseda University, Tokyo 169-8555, Japan
Interests: collaborative robot; IoT; machine learning; network economics
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Smart cloud computing technology has been developed rapidly recently, with the acceleration of Internet of Things (IoT) technology and artificial intelligence (AI) technology. We have entered an era in which cloud-based systems are given the "smart" property that can meet giant demands in multiple fields, from tele-health to e-learning, from vehicular systems to mobile applications. In this Special Issue, we aim to collect recent academic achievements in novel techniques of the most advanced smart cloud computing aligned with other novel technologies, such as IoT, AI, and big data technologies.

Prof. Dr. Meikang Qiu
Dr. Cheng Zhang
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. Sensors 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 2600 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

  • Internet of Things
  • Artificial intelligence-based smart computing
  • Cloud computing
  • Cyber threat intelligence
  • Edge computing
  • Sensor network security

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Published Papers (4 papers)

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Research

19 pages, 897 KiB  
Article
Locust Inspired Algorithm for Cloudlet Scheduling in Cloud Computing Environments
by Mohammed Alaa Ala’anzy, Mohamed Othman, Zurina Mohd Hanapi and Mohamed A. Alrshah
Sensors 2021, 21(21), 7308; https://doi.org/10.3390/s21217308 - 3 Nov 2021
Cited by 6 | Viewed by 2366
Abstract
Cloud computing is an emerging paradigm that offers flexible and seamless services for users based on their needs, including user budget savings. However, the involvement of a vast number of cloud users has made the scheduling of users’ tasks (i.e., cloudlets) a challenging [...] Read more.
Cloud computing is an emerging paradigm that offers flexible and seamless services for users based on their needs, including user budget savings. However, the involvement of a vast number of cloud users has made the scheduling of users’ tasks (i.e., cloudlets) a challenging issue in selecting suitable data centres, servers (hosts), and virtual machines (VMs). Cloudlet scheduling is an NP-complete problem that can be solved using various meta-heuristic algorithms, which are quite popular due to their effectiveness. Massive user tasks and rapid growth in cloud resources have become increasingly complex challenges; therefore, an efficient algorithm is necessary for allocating cloudlets efficiently to attain better execution times, resource utilisation, and waiting times. This paper proposes a cloudlet scheduling, locust inspired algorithm to reduce the average makespan and waiting time and to boost VM and server utilisation. The CloudSim toolkit was used to evaluate our algorithm’s efficiency, and the obtained results revealed that our algorithm outperforms other state-of-the-art nature-inspired algorithms, improving the average makespan, waiting time, and resource utilisation. Full article
(This article belongs to the Special Issue Smart Cloud Computing Technologies and Application)
►▼ Show Figures

Figure 1

Figure 1
<p>CloudSim component overview.</p> Full article ">Figure 2
<p>Scheduling system overview.</p> Full article ">Figure 3
<p>Proposed algorithm architecture.</p> Full article ">Figure 4
<p>Range distributions of cloudlets among VMs.</p> Full article ">Figure 5
<p>Average makespan.</p> Full article ">Figure 6
<p>Average waiting time.</p> Full article ">Figure 7
<p>VM utilisation.</p> Full article ">Figure 8
<p>Average makespan.</p> Full article ">
20 pages, 6072 KiB  
Article
An Efficient Dynamic-Decision Based Task Scheduler for Task Offloading Optimization and Energy Management in Mobile Cloud Computing
by Abid Ali, Muhammad Munawar Iqbal, Harun Jamil, Faiza Qayyum, Sohail Jabbar, Omar Cheikhrouhou, Mohammed Baz and Faisal Jamil
Sensors 2021, 21(13), 4527; https://doi.org/10.3390/s21134527 - 1 Jul 2021
Cited by 38 | Viewed by 3791
Abstract
Restricted abilities of mobile devices in terms of storage, computation, time, energy supply, and transmission causes issues related to energy optimization and time management while processing tasks on mobile phones. This issue pertains to multifarious mobile device-related dimensions, including mobile cloud computing, fog [...] Read more.
Restricted abilities of mobile devices in terms of storage, computation, time, energy supply, and transmission causes issues related to energy optimization and time management while processing tasks on mobile phones. This issue pertains to multifarious mobile device-related dimensions, including mobile cloud computing, fog computing, and edge computing. On the contrary, mobile devices’ dearth of storage and processing power originates several issues for optimal energy and time management. These problems intensify the process of task retaining and offloading on mobile devices. This paper presents a novel task scheduling algorithm that addresses energy consumption and time execution by proposing an energy-efficient dynamic decision-based method. The proposed model quickly adapts to the cloud computing tasks and energy and time computation of mobile devices. Furthermore, we present a novel task scheduling server that performs the offloading computation process on the cloud, enhancing the mobile device’s decision-making ability and computational performance during task offloading. The process of task scheduling harnesses the proposed empirical algorithm. The outcomes of this study enable effective task scheduling wherein energy consumption and task scheduling reduces significantly. Full article
(This article belongs to the Special Issue Smart Cloud Computing Technologies and Application)
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Figure 1

Figure 1
<p>System architecture with task processing and scheduling strategies.</p> Full article ">Figure 2
<p>Task Flow Diagram.</p> Full article ">Figure 3
<p>Network Distribution Model for Mobile Cloud System.</p> Full article ">Figure 4
<p>Job execution sequence in MCC.</p> Full article ">Figure 5
<p>Time calculations on the mobile device.</p> Full article ">Figure 6
<p>Total offloading time from MCC to the cloud virtual machine (VM).</p> Full article ">Figure 7
<p>ƩT<sub>total</sub>λ with power P used for the jobs.</p> Full article ">Figure 8
<p>Energy optimization results for the proposed technique in comparison with Mukherjee et al. [<a href="#B22-sensors-21-04527" class="html-bibr">22</a>].</p> Full article ">Figure 9
<p>The decision of task offloading probability.</p> Full article ">Figure 10
<p>Request submitted to the cloud of Mukherjee et al. [<a href="#B22-sensors-21-04527" class="html-bibr">22</a>] and proposed system.</p> Full article ">Figure 11
<p>Energy optimization request submitted to the cloud of Mukherjee et al. [<a href="#B22-sensors-21-04527" class="html-bibr">22</a>] and proposed system.</p> Full article ">
23 pages, 789 KiB  
Article
IoT Registration and Authentication in Smart City Applications with Blockchain
by Célio Márcio Soares Ferreira, Charles Tim Batista Garrocho, Ricardo Augusto Rabelo Oliveira, Jorge Sá Silva and Carlos Frederico Marcelo da Cunha Cavalcanti
Sensors 2021, 21(4), 1323; https://doi.org/10.3390/s21041323 - 13 Feb 2021
Cited by 35 | Viewed by 6231
Abstract
The advent of 5G will bring a massive adoption of IoT devices across our society. IoT Applications (IoT Apps) will be the primary data collection base. This scenario leads to unprecedented scalability and security challenges, with one of the first areas for these [...] Read more.
The advent of 5G will bring a massive adoption of IoT devices across our society. IoT Applications (IoT Apps) will be the primary data collection base. This scenario leads to unprecedented scalability and security challenges, with one of the first areas for these applications being Smart Cities (SC). IoT devices in new network paradigms, such as Edge Computing and Fog Computing, will collect data from urban environments, providing real-time management information. One of these challenges is ensuring that the data sent from Edge Computing are reliable. Blockchain has been a technology that has gained the spotlight in recent years, due to its robust security in fintech and cryptocurrencies. Its strong encryption and distributed and decentralized network make it potential for this challenge. Using Blockchain with IoT makes it possible for SC applications to have security information distributed, which makes it possible to shield against Distributed Denial of Service (DDOS). IoT devices in an SC can have a long life, which increases the chance of having security holes caused by outdated firmware. Adding a layer of identification and verification of attributes and signature of messages coming from IoT devices by Smart Contracts can bring confidence in the content. SC Apps that extract data from legacy and outdated appliances, installed in inaccessible, unknown, and often untrusted urban environments can benefit from this work. Our work’s main contribution is the development of API Gateways to be used in IoT devices and network gateway to sign, identify, and authorize messages. For this, keys and essential characteristics of the devices previously registered in Blockchain are used. We will discuss the importance of this implementation while considering the SC and present a testbed that is composed of Blockchain Ethereum and real IoT devices. We analyze the transfer time, memory, and CPU impacts during the sending and processing of these messages. The messages are signed, identified, and validated by our API Gateways and only then collected for an IoT data management application. Full article
(This article belongs to the Special Issue Smart Cloud Computing Technologies and Application)
►▼ Show Figures

Figure 1

Figure 1
<p>Testbed Mekle Tree metadata.</p> Full article ">Figure 2
<p>SC, Blockchain and IoT use cases.</p> Full article ">Figure 3
<p>User interacfion using IoT Device Manager.</p> Full article ">Figure 4
<p>Device Configuration File.</p> Full article ">Figure 5
<p>Identifier.</p> Full article ">Figure 6
<p>Metadata.</p> Full article ">Figure 7
<p>Firmware.</p> Full article ">Figure 8
<p>Blockchain Transaction.</p> Full article ">Figure 9
<p>Api Gateway Diagram.</p> Full article ">Figure 10
<p>IoT-Framework-Gui.</p> Full article ">Figure 11
<p>The Testbed network diagram.</p> Full article ">Figure 12
<p>Results without Blockchain API Gateway.</p> Full article ">Figure 13
<p>Average Time using the IoT Edge API Gateway.</p> Full article ">Figure 14
<p>IoT nodes sending payloads.</p> Full article ">Figure 15
<p>CPU usage.</p> Full article ">Figure 16
<p>Memory usage.</p> Full article ">
20 pages, 454 KiB  
Article
A Lattice-Based Homomorphic Proxy Re-Encryption Scheme with Strong Anti-Collusion for Cloud Computing
by Juyan Li, Zhiqi Qiao, Kejia Zhang and Chen Cui
Sensors 2021, 21(1), 288; https://doi.org/10.3390/s21010288 - 4 Jan 2021
Cited by 15 | Viewed by 3699
Abstract
The homomorphic proxy re-encryption scheme combines the characteristics of a homomorphic encryption scheme and proxy re-encryption scheme. The proxy can not only convert a ciphertext of the delegator into a ciphertext of the delegatee, but also can homomorphically calculate the original ciphertext and [...] Read more.
The homomorphic proxy re-encryption scheme combines the characteristics of a homomorphic encryption scheme and proxy re-encryption scheme. The proxy can not only convert a ciphertext of the delegator into a ciphertext of the delegatee, but also can homomorphically calculate the original ciphertext and re-encryption ciphertext belonging to the same user, so it is especially suitable for cloud computing. Yin et al. put forward the concept of a strong collusion attack on a proxy re-encryption scheme, and carried out a strong collusion attack on the scheme through an example. The existing homomorphic proxy re-encryption schemes use key switching algorithms to generate re-encryption keys, so it can not resist strong collusion attack. In this paper, we construct the first lattice-based homomorphic proxy re-encryption scheme with strong anti-collusion (HPRE-SAC). Firstly, algorithm TrapGen is used to generate an encryption key and trapdoor, then trapdoor sampling is used to generate a decryption key and re-encryption key, respectively. Finally, in order to ensure the homomorphism of ciphertext, a key switching algorithm is only used to generate the evaluation key. Compared with the existing homomorphic proxy re-encryption schemes, our HPRE-SAC scheme not only can resist strong collusion attacks, but also has smaller parameters. Full article
(This article belongs to the Special Issue Smart Cloud Computing Technologies and Application)
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Figure 1

Figure 1
<p>The homomorphic proxy re-encryption scheme.</p> Full article ">Figure 2
<p>System model of the homomorphic proxy re-encryption (HPRE) scheme.</p> Full article ">Figure 3
<p>Secure computing of personal healthcare records (PHRs) using HPRE with strong anti-collusion (SAC) in the cloud.</p> Full article ">
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