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Survivability Assessment of 5G Network Slicing During Massive Outages

Gajic, Marija (author)
Norges teknisk-naturvitenskapelige universitet (NTNU),Norwegian University of Science and Technology (NTNU)
Lange, Stanislav (author)
Norges teknisk-naturvitenskapelige universitet (NTNU),Norwegian University of Science and Technology (NTNU)
Vatten, Trond (author)
Norges teknisk-naturvitenskapelige universitet (NTNU),Norwegian University of Science and Technology (NTNU)
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Furdek Prekratic, Marija, 1985 (author)
Chalmers tekniska högskola,Chalmers University of Technology
Heegaard, Poul (author)
Norges teknisk-naturvitenskapelige universitet (NTNU),Norwegian University of Science and Technology (NTNU)
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 (creator_code:org_t)
2023
2023
English.
In: Proceedings of 2023 13th International Workshop on Resilient Networks Design and Modeling, RNDM 2023.
  • Conference paper (peer-reviewed)
Abstract Subject headings
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  • Mobile networks support variety of heterogeneous services, including the emergency and mission-critical ones. The next generation of mobile networks introduces the concept of network slicing where different services can have a dedicated, logically separated virtual network running over a shared physical infrastructure. Each slice may have a specific set of functional and non-functional requirements including performance, security, resilience, and survivability. Given the importance of emergency services during massive outages caused by a natural disaster, the network operators need an efficient way to evaluate the performance of the sliced network in such adverse circumstances. In this paper, we describe how survivability quantification framework can be applied to assess and compare the performance of different slicing configurations during and after massive outages. We demonstrate our proposal in a simplified use-case scenario where the performance metric for each stage of the recovery is represented with delay and throughput of the clients at a sliced, shared bottleneck. The metrics are acquired from OMNeT++ simulations. Survivability is then obtained from an analytical model and the time until the critical services (for the first responders) are recovered is of particular interest. In the scenario we consider 8 application types, 4 priority levels, and 5 approaches to map clients to slices. The results show significant performance variations between different slicing configurations, both for the critical and non-critical applications and thus highlight the importance of having a slicing configuration optimally tailored to the use case.

Subject headings

TEKNIK OCH TEKNOLOGIER  -- Elektroteknik och elektronik -- Telekommunikation (hsv//swe)
ENGINEERING AND TECHNOLOGY  -- Electrical Engineering, Electronic Engineering, Information Engineering -- Telecommunications (hsv//eng)
TEKNIK OCH TEKNOLOGIER  -- Elektroteknik och elektronik -- Kommunikationssystem (hsv//swe)
ENGINEERING AND TECHNOLOGY  -- Electrical Engineering, Electronic Engineering, Information Engineering -- Communication Systems (hsv//eng)
TEKNIK OCH TEKNOLOGIER  -- Elektroteknik och elektronik -- Datorsystem (hsv//swe)
ENGINEERING AND TECHNOLOGY  -- Electrical Engineering, Electronic Engineering, Information Engineering -- Computer Systems (hsv//eng)

Keyword

network resilience
disaster recovery
SG network slicing
Survivability
critical infras-tructure

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Gajic, Marija
Lange, Stanislav
Vatten, Trond
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Heegaard, Poul
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and Electrical Engin ...
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ENGINEERING AND TECHNOLOGY
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