A note on tools and techniques for end-to-end QoS monitoring in Internet of Things

doi:10.1016/j.jpdc.2019.05.004

Journal of Parallel and Distributed Computing

Volume 132, October 2019, Pages 160-163

https://doi.org/10.1016/j.jpdc.2019.05.004 Get rights and content

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Acknowledgments

We would like to thank the authors and all the reviewers for their hard work in helping us put together this special issue. We would also like to thank the Editor-in-Chief, and acknowledge the support of the JDPC editorial staff.

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Cited by (1)

Design and performance evaluation of QoE/QoS-oriented scheme for reliable data transmission in Internet of Things environments
2022, Computer Communications
Citation Excerpt :
This communication requires the use of different protocols, disparate network algorithms, heterogeneous communication systems, and different communication channels, which each have different QoS requirements. Thus, looking for solutions to guarantee QoS in the IoT environment is important [4–6]. A comprehensive definition of QoS includes a set of factors that include users, media players, and file specification.
Internet of things (IoT) technology has become the focus of many researchers, and quality of service (QoS) is considered one of the most important challenges for IoT technology. Additionally, the expectations of end users in the IoT environment are of great importance, which means that quality of experience (QoE) evaluations are significant. Therefore, this paper proposed a scheme to guarantee QoS in IoT environments. For this scheme, the most efficient QoS methodology was selected based on the data and network types in the IoT environment. The proposed QoS scheme classified the data transmitted through IoT systems into two main statuses. In the first status, called “individual”, the data were exchanged through one type of large-scale network at a time. In the second status, “overlapped”, the data passed through an area that comprised a mixture of different networks. The proposed scheme handled the QoS issue for both statuses. A QoE scheme evaluating the IoT data using different layers was also proposed. The proposed QoS and QoE schemes were then combined to create a more generalized QoE/QoS-oriented scheme, which was used to adapt the QoS scheme to achieve the highest efficiency. The performance of the QoE/QoS-oriented scheme was measured in a simulation environment that was constructed using an NS-3 package. First, the performance of the proposed QoS scheme was measured by two groups of metrics. The first group was general and comprised throughput, delay, and energy consumption. The second group was particular to the proposed QoS scheme and comprised transformation between individual and overlapped statuses, usage percentages for each QoS model, and the degree of complexity of the overlapped areas. The first group of metrics showed that the proposed QoE/QoS scheme had a higher efficiency than that of the previous individual QoS models. The second group of metrics showed that the features of the proposed QoS scheme worked efficiently. Finally, delay, energy consumption, throughput, and jitter were improved after the QoS methodologies were adapted using the proposed QoE scheme.

Rajiv Ranjan is a Professor in Computing Science at Newcastle University, United Kingdom. Prior to that, he was a Senior Research and Julius Fellow at CSIRO, Canberra, where he was working on projects related to Cloud and big data computing. He has been conducting leading research in the area of Cloud and big data computing developing techniques for: (i) Quality of Service based management and processing of multimedia and big data analytics applications across multiple Cloud data centers (e.g., CSIRO Cloud, Amazon and GoGrid); and (ii) automated decision support for migrating applications to data centers. He has published about 110 papers that include 60+ journal papers. He serves on the editorial board of IEEE Transactions on Computers, IEEE Transactions on Cloud Computing, IEEE Cloud Computing, and Future Generation Computer System Journals. He is one of the highly cited authors (top 0.09%) in computer science and software engineering worldwide (h-index=43, g-index=94, and 11,000+ google scholar citations).

Ellis Solaiman is a Lecturer at the School of Computing, Newcastle University. He previously received his Ph.D. in Computing Science also from Newcastle University, where he subsequently worked as a Research Associate and Teaching Fellow. His research interests are mainly in the areas of Dependability and Trust in Distributed Systems such as the Cloud and the Internet of Things. He is also interested in the automated monitoring of these systems using technologies such as Smart Contracts. He is a Fellow of the UK Higher Education Academy (FHEA) since 2016.

Massimo Villari an associate professor of computer science at the University of Messina. His research interests include cloud computing, Internet of Things, big data analytics, and security systems. Villari has a Ph.D. in computer engineering from the University of Messina. He’s a member of IEEE and IARIA boards. Contact him at .

Paul Watson is a profess or of computer science at Newcastle University. His research interests include scalable computing systems, data-intensive problems, and cloud computing. Watson has a Ph.D. in computer science from Manchester University. Contact him at .

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EditorialA note on tools and techniques for end-to-end QoS monitoring in Internet of Things

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Acknowledgments

J. Parallel Distrib. Comput.

J. Parallel Distrib. Comput.

J. Parallel Distrib. Comput.

J. Parallel Distrib. Comput.

J. Parallel Distrib. Comput.

Editorial
A note on tools and techniques for end-to-end QoS monitoring in Internet of Things