Scholarly record
CLOUD SERVICES PROVIDERS EVALUATION MODEL FOR DESIGNING HIGH PERFORMANCE, REAL-TIME IOT BIG DATA SOLUTIONS
Abstract
Cloud technology is the backbone of the delivery pipeline of just about every digital service today, from social media and streaming entertainment to connected cars and autonomous internet of things (IoT) infrastructure. Studies show the expectations are more than 15 billion IoT devices to be connected to Cloud services by 2029. Upcoming or new ultra-fast networks such as 5G and Wi-Fi 6E mean that more IoT data will be streamed to and from applications hosted in the cloud. Cloud services and infrastructure essentially help any other technology to be much lighter, faster, and more accessible, and this fact will be an important key driver in the migration of more services to the cloud. The use-cases and scenarios become increasingly complex. This is challenging for decision-makers such as chief information officers, solution architects, scientists, and thers as they are overwhelmed by various choices available by the increasingly growing number of cloud providers. The main requirements that must be met in a pure cloud application are operational excellence, security, reliability, performance efficiency and cost optimization. These requirements are met by several cloud providers and their evaluation is important. In this article, an evaluation model is proposed that helps to identify the most appropriate Cloud Services Provider (CSP) during the design process of high performance, real-time IoT Big Data solutions. Keywords: Cloud Services Providers (CSP), Evaluation model, Amazon Web Services (AWS), Azure, Google cloud platform (GCP), Green Computing
Publication Impact Profile
- Citations
- CrossRef - Citation Indexes: 2
- Captures
- Mendeley - Readers: 3
Publication details
References10
Turek, T., Dziembek, D., Hernes, M. The Use of IT Solutions Offered in the Public Cloud to Reduce the City’s Carbon Footprint. MDPI, Energies, 14, 6389, 2021
Bala Raj, Gill Bob, Smith D., Wright D., Ji K., Magic Quadrant for Cloud Infrastructure and Platform Services. Gartner, 2020
Levestam A., Löfgren G., Criteria Affecting the Choice of Cloud Service Provider. An Exploratory study of the process of choosing a cloud service provider. Industrial Management Degree Project 30 ECTS, 2021
Dineva K., Atanasova T., Design of Scalable IoT Architecture Based on AWS for Smart Livestock. MDPI Animals, 11(9), 2697, 2021
Kamal M., Raza H., Alam M., Mazliham M., Highlight the features of AWS, GCP and Microsoft Azure that have an impact when choosing a Cloud Service Provider. Section Digital Societies, Transformations & Healthcare DOI: 10.35603/sws.iscss.vg2021/s13.68 International Journal of Recent Technology and Engineering (IJRTE), volume 8, issue 5, 2020
Giordanelli R., Mastroianni C., The Cloud Computing Paradigm: Characteristics, Opportunities and Research Issues. ICAR, 2010
Tsochev G., Research on Web Applications for Remote Laboratory Exercises on Computer Networks. IEEE Infotech, 2021
Qu L., Credible Service Selection in Cloud Environments. Macquarie university, PhD thesis, 2016
Petrov P., Kostadinov G., Zhivkov P., Velichkova V., Balabanov T., Approximated sequences reconstruction with genetic algorithms. SAI, 2020
Dineva K., Atanasova T., Architectural ML Framework for IoT Services Delivery Based on Microservices. Distributed Computer and Communication Networks. DCCN 2020. Lecture Notes in Computer Science, vol 12563. Springer, Cham, pp. 698-711, 2020
View or Download full articleAccess options
SWS access login
Login as SWS Scientific CommitteeLogin as SWS Scientific PartnerLogin as SWS AuthorAuthors and approved SWS contributors will read and export their own linked papers after identity matching by SWS profile, email and SGEM GlobalID.
For librarian assistance: [email protected]
Purchase Instant Access
- Article can be downloaded after successful payment.
- Article may be used according to SWS library access terms.
- Article cannot be redistributed.