Advances in Cloud Computing and IoT Systems

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Systems & Control Engineering".

Deadline for manuscript submissions: 15 September 2024 | Viewed by 900

Special Issue Editors


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Guest Editor
School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China
Interests: cloud computing system; intelligent system; artificial intelligence

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Guest Editor
Qingdao Institute of Software, College of Computer Science and Technology, China University of Petroleum (East China), Qingdao 266580, China
Interests: big data processing; artificial intelligence; IoT middleware

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Guest Editor
School of Artificial Intelligence and Computer Science, Jiangnan University, Wuxi 214028, China
Interests: network traffic measurement; social networks; digital media

Special Issue Information

Dear Colleagues,

The evolving communication capability and wide use of smart devices have boosted the development of cloud computing and Internet of Things (IoT) systems. However, the industrial requirements have grown beyond the current technologies and are adding pressure to the researchers in the field.

How to provide effective and efficient services is an urgent issue to address in cloud computing and IoT systems. Cloud computing platforms focus on delivering high-quality services to users with diverse requirements. The complexity of cloud computing and IoT systems is also crucial for further development.

Emerging techniques such as artificial intelligence, federated learning, serverless computing, and blockchain have been integrated into cloud computing and IoT systems to improve the service efficiency, security, and accuracy. Research on those topics are eager for improvements, and research from other fields also have rising potential to be implemented in cloud computing and IoT system.

We encourage scientists, researchers, and industry specialists to explore the potential of cloud computing and IoT systems. The construction of the cloud computing system, the IoT system services, and improvement of the quality of service are all hot topics for such research. This Special Issue will help all those interested in the topic to promote their applications and quality.

Since cloud computing and IoT systems include technologies from multiple academic and industry fields, we invite contributions from experimental researchers and industrial specialists to submit high-quality manuscripts for publication in this SI.

Dr. Ruhui Ma
Prof. Dr. Weishan Zhang
Prof. Dr. Yuan Liu
Guest Editors

Manuscript Submission Information

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Keywords

  • cloud computing structure and platform
  • Internet of Things framework and protocol
  • artificial intelligence in cloud computing and IoT system
  • parallel computing and distributed system
  • cyber security and data privacy
  • network management and simulation
  • service scheduling and offloading
  • resource allocation and virtualization
  • data management and analytics
  • new applications in cloud computing and IoT system

Published Papers (1 paper)

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Research

18 pages, 1991 KiB  
Article
Internet of Things Data Cloud Jobs Scheduling Using Modified Distance Cat Swarm Optimization
by Adil Yousif, Monika Shohdy, Alzubair Hassan and Awad Ali
Electronics 2023, 12(23), 4784; https://doi.org/10.3390/electronics12234784 - 26 Nov 2023
Viewed by 627
Abstract
IoT cloud computing provides all functions of traditional computing as services through the Internet for the users. Big data processing is one of the most crucial advantages of IoT cloud computing. However, IoT cloud job scheduling is considered an NP-hard problem due to [...] Read more.
IoT cloud computing provides all functions of traditional computing as services through the Internet for the users. Big data processing is one of the most crucial advantages of IoT cloud computing. However, IoT cloud job scheduling is considered an NP-hard problem due to the hardness of allocating the clients’ jobs to suitable IoT cloud provider resources. Previous work on job scheduling tried to minimize the execution time of the job scheduling in the IoT cloud, but it still needs improvement. This paper proposes an enhanced job scheduling mechanism using cat swarm optimization (CSO) with modified distance to minimize the execution time. The proposed job scheduling mechanism first creates a set of jobs and resources to generate the population by randomly assigning the jobs to resources. Then, it evaluates the population using the fitness value, which represents the execution time of the jobs. In addition, we use iterations to regenerate populations based on the cat’s behaviour to produce the best job schedule that gives the minimum execution time for the jobs. We evaluated the proposed mechanism by implementing an initial simulation using Java Language and then conducted a complete simulation using the CloudSim simulator. We ran several experimentation scenarios using different numbers of jobs and resources to evaluate the proposed mechanism regarding the execution time. The proposed mechanism significantly reduces the execution time when we compare the proposed mechanism against the firefly algorithm and glowworm swarm optimization. The average execution time of the proposed cat swarm optimization was 131, while the average execution times for the firefly algorithm and glowworm optimization were 237 and 220, respectively. Hence, the experimental findings demonstrated that the proposed mechanism performs better than the firefly algorithm and glowworm swarm optimization in reducing the execution time of the jobs. Full article
(This article belongs to the Special Issue Advances in Cloud Computing and IoT Systems)
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