Skip to main content

AI-empowered Resource Provision and Service Scheduling in Multi-Clouds

With the rapid development of the Internet of Things (IoT) technologies and the increasing popularity of IoT devices, more and more computation-intensive IoT applications become available. However, due to the limited resources of IoT devices, it is very hard for IoT devices to process the computation-intensive applications by themselves locally. Cloud computing is a popular solution to this issue, which can provide resources in a cost effective and elastic way. IoT users do not need to build or maintain the cloud computing system. Instead, they just need to rent resources from the cloud providers. However, it is hard to rely solely on a single cloud to provide all the resources and schedule all the services for the IoT users. First, a single cloud may not have sufficient resources to offer services for all the IoT applications from geographically different regions, and the cloud sometimes needs to fix the system vulnerabilities, which will result in a serious performance degradation if there is only one cloud offering service. Second, it is demonstrated that with the increasing number in cloud providers, IoT users are willing to be served by different clouds to avoid the cloud provider lock-in. Therefore, it is more and more popular and promising to serve IoT users by multi-clouds.

In multi-clouds, in order to provide IoT users with good quality of experience (QoE) in a cost-effective manner, a careful and well-designed resource provision and service scheduling strategy is very critical. With the dramatic increase in the number of IoT users, a massive amount of data is generated and needs to be uploaded and processed by the clouds. But the network bandwidth of each cloud is often limited, and for the cloud with low network bandwidth, scheduling too many service requests will cause network congestion or even system crash. The resource capacity of each cloud is also different and varying, and the service request arrivals of IoT users are highly dynamic and stochastic. When the provided resources are not sufficient enough, IoT users will experience degraded QoE. However, reserving and renting too many resources may lead to a large waste of resources. Therefore, it is severely challenging to design the resource provision and service scheduling strategy in multi-clouds for IoT users. Artificial Intelligence techniques are promising solutions to address the above challenges. AI techniques have shown great potentials especially when dealing with complex, dynamic and uncertain systems. This special issue aims to attract and disseminate high-quality research results and practical solutions from both academia and industry to advance the AI-empowered multi-clouds for IoT. The topics of interest include, but are not limited to:

  • AI for pricing in resource provision in multi-clouds for IoT
  • AI for QoE-aware service scheduling in multi-clouds for IoT
  • AI for privacy protection in multi-clouds for IoT
  • Intelligent mobility management in service scheduling for multi-clouds
  • Intelligent traffic forecasting and prediction in multi-clouds for IoT
  • Intelligent computation offloading for energy efficiency of IoT users in multi-clouds
  • Intelligent big data analytics and processing in multi-clouds for IoT
  • Testbed of AI algorithms for resource provision in multi-clouds for IoT
  • Intelligent context-aware resource provision in multi-clouds
  • Industrial applications, data and platforms in multi-clouds for IoT

Guest Editors

Ying Chen, Associate Professor, Beijing Information Science and Technology University, China; chenying@bistu.edu.cn
Shangguang Wang, Professor, Beijing University of Posts and Telecommunications; sgwang@bupt.edu.cn
Geyong Min, Professor, University of Exeter, United Kingdom; g.min@exeter.ac.uk
Qiang Ye, Assistant Professor, Memorial University of Newfoundland, Canada; qiangy@mun.ca
Phu Thinh Do, Assistant Professor, Post and Telecommunication Institute of Technology, Vietnam; dopthinh@ptithcm.edu.vn

Provisional Deadline

Submission Deadline: 31st December 2022

Submissions

Submissions should be original papers and should not be under consideration for publication elsewhere.
Extended versions of papers from relevant conferences and workshops are invited as long as the additional contribution is substantial (at least 30% of new content).
Authors should follow the formatting and submission instructions for Journal of Cloud Computing at https://www.springer.com/13677.
For more information visit the Springer Nature Information for journal Article Authors pages at https://www.springer.com/gp/authors-editors/journal-author.
All papers will be peer-reviewed.

  1. In resource constrained edge environment, multiple service providers can compete to rent the limited resources to cache their service instances on edge servers close to end users, thereby significantly reducin...

    Authors: Binbin Huang, Ziqi Ran, Dongjin Yu, Yuanyuan Xiang, Xiaoying Shi, Zhongjin Li and Zhengqian Xu
    Citation: Journal of Cloud Computing 2023 12:132
  2. The evolution of the Internet of Things technology (IoT) has boosted the drastic increase in network traffic demand. Caching and multicasting in the multi-clouds scenario are effective approaches to alleviate ...

    Authors: Ruohan Shi, Qilin Fan, Shu Fu, Xu Zhang, Xiuhua Li and Meng Chen
    Citation: Journal of Cloud Computing 2023 12:123
  3. In vehicular edge computing, the low-delay services are invoked by the vehicles from the edge clouds while the vehicles moving on the roads. Because of the insufficiency of computing capacity and storage resou...

    Authors: Yuze Huang, Beipeng Feng, Yuhui Cao, Zhenzhen Guo, Miao Zhang and Boren Zheng
    Citation: Journal of Cloud Computing 2023 12:119
  4. With the rise of edge computing technology and the development of intelligent mobile devices, task offloading in the edge-cloud environment has become a research hotspot. Task offloading is also a key research...

    Authors: Lingkang Meng, Yingjie Wang, Haipeng Wang, Xiangrong Tong, Zice Sun and Zhipeng Cai
    Citation: Journal of Cloud Computing 2023 12:76
  5. The rise of 5G technology has driven the development of edge computing. Computation offloading is the key and challenging point in edge computing, which investigates offloading resource-intensive computing tas...

    Authors: Qinghang Gao, Jianmao Xiao, Yuanlong Cao, Shuiguang Deng, Chuying Ouyang and Zhiyong Feng
    Citation: Journal of Cloud Computing 2023 12:72
  6. According to the connotation and structure of government service resources, data of government service resources in L city from 2019 to 2021 are used to calculate the efficiency of government service resource ...

    Authors: Ya-guang Guo, Qian Yin, Yixiong Wang, Jun Xu and Leqi Zhu
    Citation: Journal of Cloud Computing 2023 12:18
  7. Nowadays, smart health technologies are used in different life and environmental areas, such as smart life, healthcare, cognitive smart cities, and social systems. Intelligent, reliable, and ubiquitous healthc...

    Authors: Sahand Hamzehei, Omid Akbarzadeh, Hani Attar, Khosro Rezaee, Nazanin Fasihihour and Mohammad R. Khosravi
    Citation: Journal of Cloud Computing 2023 12:12
  8. 3D object recognition has great research and application value in the fields of automatic drive, virtual reality, and commercial manufacturing. Although various deep models have been exploited and achieved rem...

    Authors: Mofei Song and Qi Guo
    Citation: Journal of Cloud Computing 2022 11:92
  9. Multi-cloud computing is becoming a promising paradigm to provide abundant computation resources for Internet-of-Things (IoT) devices. For a multi-device multi-cloud network, the real-time computing requiremen...

    Authors: Juan Chen, Peng Chen, Xianhua Niu, Zongling Wu, Ling Xiong and Canghong Shi
    Citation: Journal of Cloud Computing 2022 11:90
  10. Vehicular edge computing (VEC) is emerging as a new computing paradigm to improve the quality of vehicular services and enhance the capabilities of vehicles. It enables performing tasks with low latency by dep...

    Authors: Guozhi Liu, Fei Dai, Bi Huang, Zhenping Qiang, Shuai Wang and Lecheng Li
    Citation: Journal of Cloud Computing 2022 11:68
  11. In the cloud manufacturing process, service composition can combine a single service into a complex service to meet the task requirements. An efficient service composition strategy is crucial, as it affects th...

    Authors: Jun Zeng, Juan Yao, Min Gao and Junhao Wen
    Citation: Journal of Cloud Computing 2022 11:66
  12. Multi-cloud computing provides services by used different clouds simultaneously multi-signature can be used as the interactive technology between multi-cloud and users. However, the limited resources of some t...

    Authors: Chaoyue Tan, Yuling Chen, Yongtang Wu, Xiaochuan He and Tao Li
    Citation: Journal of Cloud Computing 2022 11:61
  13. With the wide adoption of health and sport concepts in human society, how to effectively analyze the personalized sports preferences of students based on past sports training records has become a crucial and e...

    Authors: Guoyan Diao, Fang Liu, Zhikai Zuo and Mohammad Kazem Moghimi
    Citation: Journal of Cloud Computing 2022 11:52
  14. In the era of information explosion, the energy consumption of cloud data centers is significant. It’s critical to reduce the energy consumption of large-scale data centers while guaranteeing quality of servic...

    Authors: Jinjiang Wang, Hangyu Gu, Junyang Yu, Yixin Song, Xin He and Yalin Song
    Citation: Journal of Cloud Computing 2022 11:50
  15. Cloud computing has emerged as a promising paradigm for meeting the growing resource demands of Internet of Things (IoT) devices. Meanwhile, with the popularity of mobile aerial base stations, Unmanned Aerial ...

    Authors: Yu Zhou, Hui Ge, Bowen Ma, Shuhang Zhang and Jiwei Huang
    Citation: Journal of Cloud Computing 2022 11:42
  16. Cloud-native database systems have started to gain broad support and popularity due to more and more applications and systems moving to the cloud. Various cloud-native databases have been emerging in recent ye...

    Authors: Xiaoyue Feng, Chaopeng Guo, Tianzhe Jiao and Jie Song
    Citation: Journal of Cloud Computing 2022 11:39
  17. With the continuous spread of COVID-19 virus, how to guarantee the healthy living of people especially the students who are of relative weak physique is becoming a key research issue of significant values. Spe...

    Authors: Yu Xie, Kuilin Zhang, Huaizhen Kou and Mohammad Jafar Mokarram
    Citation: Journal of Cloud Computing 2022 11:38
  18. With the rapid development of Internet of Things (IoT) technology and the rising popularity of IoT devices, an increasing number of computing intensive IoT applications have been developed. However, due to the...

    Authors: Yi-jie Bian, Lu Xie and Jing-qi Li
    Citation: Journal of Cloud Computing 2022 11:35
  19. In recent years, with the development of Unmanned Aerial Vehicle (UAV) and Cloud Internet-of-Things (Cloud IoT) technology, data collection using UAVs has become a new technology hotspot for many Cloud IoT app...

    Authors: Yiguang Gong, Kai Chen, Tianyu Niu and Yunping Liu
    Citation: Journal of Cloud Computing 2022 11:29