Authors:
(1) Rashmi Yadav, Department of Electrical Engineering, Indian Institute of Technology Kanpur, India (Email: [email protected]);
(2) Rashmi Kamran, Department of Electrical Engineering, Indian Institute of Technology Bombay, India (Email: [email protected]);
(3) Pranav Jha, Department of Electrical Engineering, Indian Institute of Technology Bombay, India (Email: [email protected]);
(4) Abhay Karandikar, Department of Electrical Engineering, Indian Institute of Technology Bombay, India and Secretary to the Government of India, Department of Science & Technology, New Delhi, India (Email: [email protected]).
Table of Links
- Abstract and Introduction
- Proposed Signalling Service-Based Architecture
- System Model
- Performance Evaluation
- Convergence of 3GPP 5G and N3BN in SSBA
- Conclusion, Acknowledgement, and References
IV. PERFORMANCE EVALUATION
In this section, we present the performance evaluation of both the proposed SSBA and the 3GPP 5G architecture using the Eclipse plug-in tool [9]. The evaluation is based on several parameters, such as the number of MBS sessions established per unit time, average response time (ART), and processor utilization. These parameters are significant in evaluating the network’s scalability, one of the key aspects we consider. The MBS session establishment rate measures the rate at which MBS sessions are established with respect to specific actions, such as reconf ig representing RRC reconfiguration (PDU session modification command). This specific action represents the completion of the MBS session establishment call flow. ART evaluates the average waiting time for UE’s MBS session establishment process. Processor utilization evaluates the NF’s processor capacity utilization during the entire process.
Fig. 3 and 4 illustrate the number of MBS sessions established per unit time for both architectures under two different configurations, denoted as b1 and b2. It is observed that the proposed SSBA achieves a higher saturation point than the
3GPP 5G architecture. In the basic configuration (b1), the 3GPP 5G architecture saturates at 14,000 users, while the proposed SSBA saturates at 30,000 users. Similarly, in the scaled configuration (b2), the 3GPP 5G architecture saturates at 42,000 users, while the proposed SSBA saturates at 90,000 users. The saturation point indicates the maximum number of UEs served by the network before it becomes overloaded.
The comparative analysis of processor utilization of both the 3GPP 5G and the proposed SSBA for the basic configuration is shown in Fig. 5. It shows that the BCCP (BCC Processor), for instance, reaches its maximum processor utilization, explaining the saturation point for the number of MBS session establishments. Other NFs, however, are not fully utilized at this point. This signifies that the processing chain fails if an NF becomes a bottleneck in the consecutive chain. Fig. 6 presents the processor utilization results for both architectures for the scaled configuration. The results demonstrate that processors in the 3GPP 5G architecture saturate earlier than the proposed SSBA due to the higher number of messages in the 3GPP 5G architecture.
Based on the obtained results for the MBS session rate, ART, and processor utilization, the scalability is evaluated
using the equation provided in [18]. The scalability results are plotted in Fig. 7 for configurations b1 and b2. The proposed SSBA outperforms the 3GPP 5G architecture, as it can serve more concurrent users with the same scaling configuration. It is evident from the results that the proposed SSBA is more scalable and performs better than the 3GPP 5G architecture.
This paper is available on arxiv under CC 4.0 license.