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On Resource Description Capabilities of On-Board Tools for Resource Management in Cloud Networking and NFV Infrastructures
Blekinge Tekniska Högskola, Fakulteten för datavetenskaper, Institutionen för kommunikationssystem.ORCID-id: 0000-0003-4814-4428
Blekinge Tekniska Högskola, Fakulteten för datavetenskaper, Institutionen för kommunikationssystem.
Blekinge Tekniska Högskola, Fakulteten för datavetenskaper, Institutionen för kommunikationssystem.
CityNetwork Webbhotell AB.
Vise andre og tillknytning
2016 (engelsk)Inngår i: 2016 IEEE INTERNATIONAL CONFERENCE ON COMMUNICATIONS WORKSHOPS (ICC), 2016, s. 442-447Konferansepaper, Publicerat paper (Fagfellevurdert)
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.

sted, utgiver, år, opplag, sider
2016. s. 442-447
Serie
IEEE International Conference on Communications Workshops, ISSN 2164-7038
HSV kategori
Identifikatorer
URN: urn:nbn:se:bth-11902ISI: 000386326800074ISBN: 978-1-5090-0448-5 (digital)OAI: oai:DiVA.org:bth-11902DiVA, id: diva2:930028
Konferanse
IEEE International Conference on Communications (ICC), Kuala Lumpur
Merknad

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

Tilgjengelig fra: 2016-05-21 Laget: 2016-05-21 Sist oppdatert: 2019-08-09bibliografisk kontrollert
Inngår i avhandling
1. Towards Secure Collaborative AI Service Chains
Åpne denne publikasjonen i ny fane eller vindu >>Towards Secure Collaborative AI Service Chains
2019 (engelsk)Licentiatavhandling, med artikler (Annet vitenskapelig)
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.

sted, utgiver, år, opplag, sider
Karlskrona: Blekinge Tekniska Högskola, 2019. s. 146
Serie
Blekinge Institute of Technology Licentiate Dissertation Series, ISSN 1650-2140 ; 11
HSV kategori
Identifikatorer
urn:nbn:se:bth-18531 (URN)978-91-7295-381-9 (ISBN)
Presentation
2019-09-10, J1620, Campus Gräsvik, Karlskrona, 12:30 (engelsk)
Opponent
Veileder
Tilgjengelig fra: 2019-08-09 Laget: 2019-08-09 Sist oppdatert: 2019-09-03bibliografisk kontrollert

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