Data replication techniques in the Internet of Things: a systematic literature review. Issue 4 (28th June 2021)

• Record Type: Journal Article
• Authors: Sun, Xianke; Wang, Gaoliang; Xu, Liuyang; Yuan, Honglei
• Is Part Of: Library hi tech. Volume 39:Issue 4(2021)
• Page Start: 1121
• Page End: 1136
• Publication Date: 2021-06-28
• Subjects: Data replication -- Internet of Things (IoT) -- Static/dynamic replication -- Distributed replication; Library science -- Technological innovations -- Periodicals; Libraries -- Automation -- Periodicals; Information science -- Periodicals; 025.00285
• DOI: 10.1108/LHT-01-2021-0044
• Languages: English
• ISSNs: 0737-8831

Abstract

Abstract : Purpose: In data grids, replication has been regarded as a crucial optimization strategy. Computing tasks are performed on IoT gateways at the cloud edges to obtain a prompt response. So, investigating the data replication mechanisms in the IoT is necessary. Henceforth, a systematic survey of data replication strategies in IoT techniques is presented in this paper, and some suggestions are offered for the upcoming works. In two key classifications, various parameters dependent on the analysis of the prevalent approaches are considered. The pros and cons associated with chosen strategies have been explored, and the essential problems of them have been presented to boost the future of more effective data replication strategies. We have also discovered gaps in papers and provided solutions for them. Design/methodology/approach: Progress in Information Technology (IT) growth has brought the Internet of Things (IoT) into life to take a vital role in our everyday lifestyles. Big IoT-generated data brings tremendous data processing challenges. One of the most challenging problems is data replication to improve fault-tolerance, reliability, and accessibility. In this way, if the primary data source fails, a replica can be swapped in immediately. There is a significant influence on the IoT created by data replication techniques, but no extensive and systematic research exists in this area. There is still no systematic and full way to address the relevant methods and evaluate them. Hence, in the present investigation, a literature review is indicated on the IoT-based data replication from papers published until 2021. Based on the given guidelines, chosen papers are reviewed. After establishing exclusion and inclusion criteria, an independent systematic search in Google Scholar, ACM, Scopus, Eric, Science Direct, Springer link, Emerald, Global ProQuest, and IEEE for relevant studies has been performed, and 21(6 paper analyzed in section 1 and 15 paper analyzed in section 3) papers have been analyzed. Findings: The results showed that data replication mechanisms in the IoT algorithms outperform other algorithms regarding impressive network utilization, job implementation time, hit ratio, total replication number, and the portion of utilized storage in percentage. Although a few ideas have been suggested that fix different facets of IoT data management, we predict that there is still space for development and more study. Thus, in order to design innovative and more effective methods for future IoT-based structures, we explored open research directions in the domain of efficient data processing. Research limitations/implications: The present investigation encountered some drawbacks. First of all, only certain papers published in English were included. It is evident that some papers exist on data replication processes in the IoT written in other languages, but they were not included in our research. Next, the current report has only analyzed the mined based on data replication processes and IoT keyword discovery. The methods for data replication in the IoT would not be printed with keywords specified. In this review, the papers presented in national conferences and journals are neglected. In order to achieve the highest ability, this analysis contains papers from major global academic journals. Practical implications: To appreciate the significance and accuracy of the data often produced by different entities, the article illustrates that data provenance is essential. The results contribute to providing strong suggestions for future IoT studies. To be able to view the data, administrators have to modify novel abilities. The current analysis will deal with the speed of publications and suggest the findings of research and experience as a future path for IoT data replication decision-makers. Social implications: In general, the rise in the knowledge degree of scientists, academics, and managers will enhance administrators' positive and consciously behavioral actions in handling IoT environments. We anticipate that the consequences of the present report could lead investigators to produce more efficient data replication methods in IoT regarding the data type and data volume. Originality/value: This report provides a detailed literature review on data replication strategies relying on IoT. The lack of such papers increases the importance of this paper. Utilizing the responses to the study queries, data replication's primary purpose, current problems, study concepts, and processes in IoT are summarized exclusively. This approach will allow investigators to establish a more reliable IoT technique for data replication in the future. To the best of our understanding, our research is the first to provide a thorough overview and evaluation of the current solutions by categorizing them into static/dynamic replication and distributed replication subcategories. By outlining possible future study paths, we conclude the article.