Simplified Agent-Based Resource Sharing Approach for WSN-WSN Interaction in IoT/CPS Projects

Yıldırım, Güngör; Tatar, Yetkin

doi:10.1109/access.2018.2884741

Cited by 25 publications

(24 citation statements)

References 26 publications

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“…For instance, Kouvelas et al in [94] introduced an interesting theoretical foundation for resource sharing among IoT devices by exploiting graph theory. Furthermore, Yildirim and Tatar [95] present the two ways of sharing resources in WSNs: WSN virtualization and Middleware Based Server Systems (MBSSs), and discuss all advantages and disadvantages of both. Importantly, Vo et al [96] spot the huge potential in integrating WSN into 5G, providing interesting point of views.…”

Section: The Era Toward 5g (2016-)mentioning

confidence: 99%

“…Recently, [25,95] studied how virtualization can be applied in the IoT ecosystem. Due to the fact that IoT networks suffer from resource constraints, virtualization seems to provide many opportunities in their deployment and operation.…”

Section: B Sharing Techniquesmentioning

confidence: 99%

“…In their survey on virtualization techniques in the context of IoT resource management, Zahoor and Mir in [25] see virtualization as the approach that can play an important role in maximizing resource utilization and managing the resources. Yildirim and Tatar [95] propose Node-based Virtualization (NoBV) and Network-based Virtualization (NeBV) as a way to apply virtualization into WSNs, and these specific use cases are further elaborated in the Section VI. In the latter part of this subsection we refer to other techniques listed in the Table II.…”

Section: B Sharing Techniquesmentioning

confidence: 99%

See 2 more Smart Citations

Sharing Distributed and Heterogeneous Resources toward End-to-End 5G Networks: A Comprehensive Survey and a Taxonomy

Slamnik-Kriještorac

Kremo

Ruffini

et al. 2020

IEEE Commun. Surv. Tutorials

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Regardless of the context to which it is applied, sharing resources is well-recognized for its considerable benefits. Since 5G networks will be service-oriented, on-demand, and highly heterogeneous, it is utmost important to approach the design and optimization of the network from an end-to-end perspective. In addition, in order to ensure end-to-end performance, this approach has to entail both wireless and optical domains, altogether with the IoT, edge, and cloud paradigms which are an indispensable part of the 5G network architecture. Shifting from the exclusive ownership of network resources toward sharing enables all participants to cope with stringent service requirements in 5G networks, gaining significant performance improvements and cost savings at the same time. The main objective of this paper is to survey the literature on resource sharing, providing an in-depth and comprehensive perspective of sharing by recognizing the main trends, the techniques which enable sharing, and the challenges that need to be addressed. By providing a taxonomy which brings the relevant features of a comprehensive sharing model into focus, we aim to enable the creation of sharing models for more efficient future communication networks. We also summarize and discuss the relevant issues arising from network sharing, that should be properly tackled in the future.

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Section: The Era Toward 5g (2016-)mentioning

confidence: 99%

Section: B Sharing Techniquesmentioning

confidence: 99%

Section: B Sharing Techniquesmentioning

confidence: 99%

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Sharing Distributed and Heterogeneous Resources toward End-to-End 5G Networks: A Comprehensive Survey and a Taxonomy

Slamnik-Kriještorac

Kremo

Ruffini

et al. 2020

IEEE Commun. Surv. Tutorials

View full text Add to dashboard Cite

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“…[20] for time-constrained servers in cloud computing. Reference [21] developed an agentbased server system approach that improves the resource sharing between heterogeneous wireless sensor networks (WSNs) in IoT/CPS providers.…”

Section: Related Workmentioning

confidence: 99%

Real-time task processing method based on edge computing for spinning CPS

Shi-yong

Bao

et al. 2019

Front. Mech. Eng.

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Spinning production is a typical continuous manufacturing process characterized by high speed and uncertain dynamics. Each manufacturing unit in spinning production produces various real-time tasks, which may affect production efficiency and yarn quality if not processed in time. This paper presents an edge computing-based method that is different from traditional centralized cloud computation because its decentralization characteristics meet the high-speed and high-response requirements of yarn production. Edge computing nodes, real-time tasks, and edge computing resources are defined. A system model is established, and a real-time task processing method is proposed for the edge computing scenario. Experimental results indicate that the proposed real-time task processing method based on edge computing can effectively solve the delay problem of real-time task processing in spinning cyber-physical systems, save bandwidth, and enhance the security of task transmission.

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“…Geliştirilen test platformu farklı teknolojili heterojen düğümlerden ve kaynaklardan oluşmaktadır. [26,27]. Bu servis TinyOS tabanlı "Agilla" arakatman yazılımı (middleware-MW) ile sağlanmaktadır [28,29].…”

Section: Geli̇şti̇ri̇len Test Platformu Modeli̇ Ve Si̇stem Alt Yapisi (Theunclassified

Uzak kullanıcı destekli bir IoT-WSN sanal laboratuvarı ve test platformu: FıratWSN

Yıldırım¹,

Tatar²

2019

Gazi Üniversitesi Mühendislik-Mimarlık Fakültesi Dergisi

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 WSN Virtualization  Virtual WSN Testbed  WSN laboratory In this study, the implementation and development of a virtual WSN testbed platform, called FiratWSN, which enables the running of remote test applications for academic studies, is introduced. Unlike the other similar studies in the literature, with the help of Agilla middleware, the testbed can allow a certain number of different user applications to be run concurrently on the same programmable physical WSN nodes. The testbed also provides an infrastructure for heterogeneous application tests. Users can remotely connect to the system over the internet and test their WSN applications in a flexible lab environment, which this provides an important cost and installation time saving to them. Figure A. The node based virtualization backbone of the IoT-WSN testbed Purpose: The aim of the study is to develop a virtual IoT-WSN testbed platform that provides multi-remote user support. This will allow more users to use the same shared WSN resources simultaneously. Theory and Methods: The basic idea behind this platform is based on three concepts. These are node based WSN virtualization, heterogeneity, and remote user support. The node-based virtualization support is done by the Agilla middleware, and the developed two software, AUY, and AICF. A screenshot from the virtualization backbone is presented in Fig.A. Also, the testbed platform includes heterogeneous WSN technologies in terms of hardware, sensors, actuators, and stack. Multi-remote user support is maintained via worldwide web. The platform utilizes CoAP and RESTful for IPv6 applications. Results: The developed platform has successfully provided all infrastructure supports expected from it. While the success rate for CoAP-based tests is between 90 and 100%, the success rate in the virtual node applications is between 85 and 100 %. Conclusion: Designed so as to be a part of large scale WSN projects, the FiratWSN testbed platform, which is compatible with the Client / Server structure, can collaborate with other WSN research laboratories located in different locations to create a broader virtual WSN testing environment over the internet. Hereby, it is clear that it will provide great opportunities.

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Simplified Agent-Based Resource Sharing Approach for WSN-WSN Interaction in IoT/CPS Projects

Cited by 25 publications

References 26 publications

Sharing Distributed and Heterogeneous Resources toward End-to-End 5G Networks: A Comprehensive Survey and a Taxonomy

Sharing Distributed and Heterogeneous Resources toward End-to-End 5G Networks: A Comprehensive Survey and a Taxonomy

Real-time task processing method based on edge computing for spinning CPS

Uzak kullanıcı destekli bir IoT-WSN sanal laboratuvarı ve test platformu: FıratWSN

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