4.6 Article

Performability of Network Service Chains: Stochastic Modeling and Assessment of Softwarized IP Multimedia Subsystem

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IEEE COMPUTER SOC
DOI: 10.1109/TDSC.2021.3082626

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IP multimedia subsystem; performance analysis; availability analysis; stochastic reward networks; redundancy optimization

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Service provisioning mechanisms in 5G infrastructures utilize the concept of network service chain, coupled with NFV paradigm. The IP Multimedia Subsystem (IMS) is a key infrastructure of 5G networks, characterized by performance and availability aspects. Through a designed testbed, softIMS architecture is assessed in terms of performance and availability using stochastic analysis, optimizing resource allocation and minimizing deployment costs.
Service provisioning mechanisms implemented across 5G infrastructures take broadly into use the network service chain concept. Typically, it is coupled with Network Function Virtualization (NFV) paradigm, and consists in defining a pre-determined path traversed by a set of softwarized network nodes to provide specific services. A well known chain-like framework is the IP Multimedia Subsystem (IMS), a key infrastructure of 5G networks, that we characterize both by a performance and an availability perspective. Precisely, supported by a designed from scratch testbed realized through Clearwater platform, we perform a stochastic assessment of a softwarized IMS (softIMS) architecture where two main stages stand out: i) a performance analysis, where, exploiting the queueing network decomposition method, we formalize an optimization problem of resource allocation by modeling each softIMS node as an M/G/c system; ii) an availability assessment, where, adopting the Stochastic Reward Net methodology, we are able to characterize the behavior of softIMS in terms of failure/repair events, and to derive a set of optimal configurations satisfying a given availability requirement (e.g., five nines) while minimizing deployment costs. Two routines dubbed OptCNT and OptSearchChain have been devised to govern the performance and availability analyses, respectively.

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