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On Resource Description Capabilities of On-Board Tools for Resource Management in Cloud Networking and NFV Infrastructures
Blekinge Institute of Technology, Faculty of Computing, Department of Communication Systems.ORCID iD: 0000-0003-4814-4428
Blekinge Institute of Technology, Faculty of Computing, Department of Communication Systems.
Blekinge Institute of Technology, Faculty of Computing, Department of Communication Systems.
CityNetwork Webbhotell AB.
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2016 (English)In: 2016 IEEE INTERNATIONAL CONFERENCE ON COMMUNICATIONS WORKSHOPS (ICC), 2016, p. 442-447Conference paper, Published paper (Refereed)
Abstract [en]

The rapid adoption of networks that are based on "cloudification" and Network Function Virtualisation (NFV) comes from the anticipated high cost savings of up to 70% in their build and operation. The high savings are founded in the use of general standard servers, instead of single-purpose hardware, and by efficiency resource sharing through virtualisation concepts. In this paper, we discuss the capabilities of resource description of "on-board" tools, i.e. using standard Linux commands, to enable OPEX savings. We put a focus on monitoring resources on small time-scales and on the variation observed on such scales. We introduce a QoE-based comparative concept that relates guest and host views on "utilisation" and "load" for the analysis of the variations. We describe the order of variations in "utilisation" and "load" by measurement and by graphical analysis of the measurements. We do these evaluations for different host operating systems and monitoring tools.

Place, publisher, year, edition, pages
2016. p. 442-447
Series
IEEE International Conference on Communications Workshops, ISSN 2164-7038
National Category
Communication Systems
Identifiers
URN: urn:nbn:se:bth-11902ISI: 000386326800074ISBN: 978-1-5090-0448-5 (electronic)OAI: oai:DiVA.org:bth-11902DiVA, id: diva2:930028
Conference
IEEE International Conference on Communications (ICC), Kuala Lumpur
Note

Held in conjunction with the IEEE International Conference on Communications (ICC 2016)

Available from: 2016-05-21 Created: 2016-05-21 Last updated: 2019-08-09Bibliographically approved
In thesis
1. Towards Secure Collaborative AI Service Chains
Open this publication in new window or tab >>Towards Secure Collaborative AI Service Chains
2019 (English)Licentiate thesis, comprehensive summary (Other academic)
Abstract [en]

At present, Artificial Intelligence (AI) systems have been adopted in many different domains such as healthcare, robotics, automotive, telecommunication systems, security, and finance for integrating intelligence in their services and applications. The intelligent personal assistant such as Siri and Alexa are examples of AI systems making an impact on our daily lives. Since many AI systems are data-driven systems, they require large volumes of data for training and validation, advanced algorithms, computing power and storage in their development process. Collaboration in the AI development process (AI engineering process) will reduce cost and time for the AI applications in the market. However, collaboration introduces the concern of privacy and piracy of intellectual properties, which can be caused by the actors who collaborate in the engineering process.  This work investigates the non-functional requirements, such as privacy and security, for enabling collaboration in AI service chains. It proposes an architectural design approach for collaborative AI engineering and explores the concept of the pipeline (service chain) for chaining AI functions. In order to enable controlled collaboration between AI artefacts in a pipeline, this work makes use of virtualisation technology to define and implement Virtual Premises (VPs), which act as protection wrappers for AI pipelines. A VP is a virtual policy enforcement point for a pipeline and requires access permission and authenticity for each element in a pipeline before the pipeline can be used.  Furthermore, the proposed architecture is evaluated in use-case approach that enables quick detection of design flaw during the initial stage of implementation. To evaluate the security level and compliance with security requirements, threat modeling was used to identify potential threats and vulnerabilities of the system and analyses their possible effects. The output of threat modeling was used to define countermeasure to threats related to unauthorised access and execution of AI artefacts.

Place, publisher, year, edition, pages
Karlskrona: Blekinge Tekniska Högskola, 2019. p. 146
Series
Blekinge Institute of Technology Licentiate Dissertation Series, ISSN 1650-2140 ; 11
National Category
Telecommunications
Identifiers
urn:nbn:se:bth-18531 (URN)978-91-7295-381-9 (ISBN)
Presentation
2019-09-10, Karlskrona, 00:00 (English)
Opponent
Supervisors
Available from: 2019-08-09 Created: 2019-08-09 Last updated: 2019-08-09Bibliographically approved

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Tutschku, KurtAhmadi Mehri, VidaCarlsson, Anders

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