Convergence of cloud, Internet of Things, and big data: New platforms and applications

摘要

Cloud, Internet of Things (IoT), and big data have not only become the fundamental technologies and platforms in computing and network communication, but they have greater potential in a wide range of other areas such as business, finance, transportation, healthcare, social media, and engineering, among others. Cloud computing provides a large pool of compute and storage resources and enables transparent access to such resources through the Internet. IoT is used to connect physical devices through the Internet that can generate large volume of (big) data. For instance, IoT can connect most modern devices such as smart phones, smart TVs, traffic and weather sensors, and other smart digital devices that generate large volumes of the data. Thus cloud, IoT, and big data can be used together to offer new and exciting services in the aforementioned areas. This special issue has been organized to solicit papers via an open call as well as selected papers from the 7th International Conference on Future Internet of Things and Cloud (FiCloud-2019), IEEE TCI, and the 5th International Conference on Big Data Innovations and Applications (Innovate-Data 2019), Springer, which were held during August 26–28, 2019, in Istanbul, Turkey. The conferences were attended by a large number of participants from different countries across the world. The conferences featured a number of technical sessions of research papers, industry talks, and keynote talks. A number of workshops and symposia were also organized alongside the main conferences. This special issue aims to foster the dissemination of high-quality research with new ideas, approaches, theories and practice to solve the challenging issues in the design and development of new platforms and application areas related to the convergence of cloud, IoT, and big data. Some of the cutting-edge topics covered by the research articles in this special issue include: the design and development of new models and architectures, analysis and evaluation of security, privacy and trust models, performance evaluation, and data mining techniques. A number of papers were submitted to this special issue and each was reviewed by multiple referees. Based on the reviews, 13 papers were accepted for this special issue. The work presented in these papers is summarized as follow. Stavrinides and Karatza1 highlighted the significance of supplementary resources from public cloud to effectively handle the increasing IoT workflow jobs in a fog environment. As the cloud involves higher data transfer latency and monetary cost, the proposed approach takes into account these two factors, in addition to the real-time constraints of the workload. The proposed scheduling heuristic is based on the trade-off between performance and monetary cost. The proposed scheduling strategy is compared against a baseline policy that utilizes only the fog resources. The simulation experiments have been carried out under varying sizes of workflow input data and for workloads with soft and hard deadlines. Barati and Rana2 presented an investigation into the privacy of data in an emerging composite service provision from visible and invisible cloud service providers. This article presented an architecture based on blockchain and smart contracts to understand a challenging issue of the impact of users' data privacy in such environment. The implementation of the proposed architecture demonstrated effective access control management. The article also described the scalability and cost of undertaking this access control mechanism. The proposed approach can be used to support service aggregation across both private and public clouds. Afzal et al.3 carried out investigations into the challenges involved in unlicensed radio spectrum usage by increasing IoT devices leading to increased collisions with impact on the quality of service. This article proposed a cognitive radio (CR) based solution to address this problem. The network, formed by CRs, allows an