Metric Indexing for Efficient Data Access in the Internet of Things

2018 ◽  
Author(s):  
Christian Beecks ◽  
Alexander Grass ◽  
Shreekantha Devasya
Keyword(s):  
Internet Of Things ◽  
Data Access ◽  
The Internet ◽  
Efficient Data ◽  
The Internet Of Things

scholarly journals Multistage Dynamic Packet Access Mechanism of Internet of Things

2018 ◽  
Vol 2018 ◽  
pp. 1-16
Author(s):  
Yi Meng ◽  
Chen QingKui ◽  
Zhang Gang
Keyword(s):  
Internet Of Things ◽  
Resource Competition ◽  
Data Access ◽  
The Internet ◽  
Network Access ◽  
Feature Maps ◽  
Control Command ◽  
Packet Access ◽  
Low Efficiency ◽  
The Internet Of Things

In the scenario of mass control commands requesting for network access, confined by the best-effort network service mode, it is easy to bring about resource competition and thus a phenomenon of access failure on major and urgent service request at the data access center for the Internet of Things. In this event, the dynamic diversification of control command is unable to access the necessary resources on a comparatively fair basis, causing low efficiency in heterogeneous resource utilization at the access center. This paper defines the problem of group request dynamic resource allocation and further converts it into the problem of 0-1 integer and linear programming and proposes a multistage dynamic packet access strategy. This strategy works first on dynamic group division on the users’ mass control requests using the high ability of self-organizing feature maps and then searches for the optimized matching resources based on the frog-leaping algorithm which has a better capacity for global searching for the best resources. This paper analyzes the feasibility of this strategy and its astringency. The experimental results demonstrate that the strategy can effectively improve the success rate of access to the data center for the Internet of Things and reduce network blockage and response delay.

Data replication techniques in the Internet of Things: a systematic literature review

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Xianke Sun ◽  
Gaoliang Wang ◽  
Liuyang Xu ◽  
Honglei Yuan
Keyword(s):  
Internet Of Things ◽  
Literature Review ◽  
Data Processing ◽  
Data Replication ◽  
Primary Data ◽  
The Internet ◽  
Content Type ◽  
The Future ◽  
Efficient Data ◽  
The Internet Of Things

PurposeIn 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/approachProgress 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.FindingsThe 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/implicationsThe 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 implicationsTo 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 implicationsIn 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/valueThis 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.

scholarly journals Algorithm and Distributed Computing for the Internet of Things

Sensors ◽  
2020 ◽  
Vol 20 (16) ◽  
pp. 4513
Author(s):  
Juan A. Gómez-Pulido ◽  
Jorge Sá Silva ◽  
Takahiro Hara
Keyword(s):  
Internet Of Things ◽  
Distributed Computing ◽  
The Internet ◽  
Special Issue ◽  
Efficient Data ◽  
Multiple Services ◽  
Algorithmic Techniques ◽  
The Internet Of Things ◽  
Modern Technologies ◽  
Real World Problems

The ongoing generalization of Internet of Things and its presence and application in multiple fields is generating a large amount of data that can be used to extract knowledge, among other purposes. In this context, algorithmic techniques and efficient computer systems provide an opportunity to successfully address efficient data processing and intelligent data analysis. As a result, multiple services can be improved, resources can be optimized and real-world problems of interest can be solved. This Special Issue on Algorithm and Distributed Computing for the Internet of Things gives the opportunity to know recent advances in the application of modern technologies hardware and software to the Internet of Things.

scholarly journals Trust Management in Internet of Things Applications

2019 ◽  
Vol 8 (2S8) ◽  
pp. 1750-1753
Keyword(s):  
Internet Of Things ◽  
Cyber Security ◽  
Trust Management ◽  
Energy Use ◽  
User Authentication ◽  
Data Access ◽  
The Internet ◽  
Security Measures ◽  
Management Models ◽  
The Internet Of Things

More connected devices bring amazing benefits to people and enterprises. However, they also create more digital doorways. The risk in IoT is not just financial. IoT connecting medical devices, running city infrastructure and even the houses we sleep in. Connected gadgets and sensors in our homes and working environments known as the Internet of Things-offer gigantic potential for improving how internet live and move around. We can quantify wellbeing information, travel propensities and vitality use. In any case, as more gadgets become associated, vulnerable they are to complex digital security dangers. Connected devices and sensors in our homes and workplacesknown as the Internet of Things-offer huge potential for improving how we live and move around. We can measure health data, travel habits and energy use. But as more devices become connected, the more vulnerable they are to sophisticated cyber security threats. There exist a few application security issues; for example, data access and user authentication, data protection, decimate and track of information stream, IoT platform stability, middleware security, the executives stage, etc. An effective trust management model is to be used in each IoT framework to ensure the framework against malevolent assaults and consequently ensuring dependable and secure data transmission. To achieve this objective, various trust management models are used to enforce different security measures in a social IoT system. Two different trust management models namely dynamic model and machine learning based model are clarified and correlation of model are expressed and along these lines the benefit of one model over the other is comprehended.. Appropriately in this paper, a detailed study of each model is done with other pinpoints thus leading to a thorough study of two diverse trust management models.

Secure and efficient data transmission in the Internet of Things

2015 ◽  
Vol 62 (1) ◽  
pp. 111-122 ◽  
Author(s):  
Fagen Li ◽  
Zhaohui Zheng ◽  
Chunhua Jin
Keyword(s):  
Internet Of Things ◽  
Data Transmission ◽  
The Internet ◽  
Efficient Data ◽  
The Internet Of Things
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