Performance Evaluation of IMS-Based Core Networks in Presence of Failures

Abstract

In order to evaluate performance of mobile networks, it is necessary to consider the occurrence of random failures causing performance degradation and the consequent repair actions. This approach is especially suitable for next generation networks based on the Third Generation Partnership Project (3GPP) IP Multimedia Subsystem (IMS), as a consequence of the very high Quality of Service levels required by telecommunication operators' subscribers. IMS core network signalling servers can be modeled as multi-state elements, where server states correspond to different performance levels. The number of sessions handled by a single server per time unit is one of the performance figure that can be considered. Given a demand profile, some redundancy techniques must be adopted to meet the typical requirements for a telecommunication network in terms of service availability and, in this paper, a redundancy optimization problem is solved by using a Universal Generating Function approach.

Availability Evaluation of Multi-Tenant Service Function Chaining Infrastructures by Multidimensional Universal Generating Function

“…Recall that, under the assumption of adopting load balancing techniques for parallel nodes [22], a subsystem constituted by multi-state components with flow dispersion is obtained. According to [21], the u-function of subsystem m with L m parallel nodes is expressed by the π operator that represents the product of the UGFs for each node, namely…”

“…In order to meet the "five nines" availability requirement for the vIMS, we set A 0 = 1 − 10 −5 and solve numerically the optimization problem (21) by an exhaustive search approach, having imposed a uniform limitation of 4 redundant nodes for each server. A routine (available upon request for non commercial use), written in Mathematica R , implements the proposed MUGF approach: it evaluates the steady-state availability of the vIMS system (9) in every redundancy configuration by computing the MUGF (19) via parallel and series operators (16) and 18, respectively.…”

End-to-End Reliability and Optimization of Intra and Inter-Domain IMS-based Communication Networks

“…The simulation results of end-to-end availability were shown to significantly improve when having a redundancy of the S-CSCF unit, especially for long distance communication. Besides, performance optimization of the IMS core network with parallel redundancy was evaluated by using the CTMC and Universal Generating Function (UGF) [17].…”

“…The Markov model can take into account some detailed working states and system parameters such as failover and recovery rates. Besides, redundancy effect can also be included into the model for an evaluation [8,[15][16][17].…”

“…For example, state-space methods such as Queuing Network Model (QNM) [9][10][11], Queuing Petri Nets (QPN) [12], and the Markov model [8,[13][14][15][16][17] were applied for performance and reliability evaluation of the IMS network. The QNM is normally applied to analyze the processing delay.…”