A Comprehensive Evaluation of the Impact of ATM QoS Mechanisms on Network Performance for Multimedia and Data Applications

TL;DR

This paper evaluates how ATM QoS mechanisms ($CBR$, $VBR$, $ABR$, $UBR$) influence network performance for mixed voice, video, and data traffic. An OPNET-based ATM network model quantifies metrics including end-to-end delay ($E2E$), packet delay variation ($PDV$), and jitter for voice and video, plus download response time for data transfers. Results indicate that $CBR$ (and to a lesser extent $VBR$) delivers the best performance for delay-sensitive applications, while $ABR$ and $UBR$ incur higher latency and variability. These findings provide practical QoS parameter guidelines for deploying ATM in multi-service networks and point to future work integrating emerging technologies such as 5G, software-defined networking (SDN), and network function virtualization (NFV).

Abstract

The Asynchronous Transfer Mode (ATM) network is crucial due to its ability to efficiently transmit data, provide reliable connections, and support various service classes with specific Quality of Service (QoS) requirements. In this paper, we utilize the OPNET network simulation software to model an ATM network and analyze the impact of QoS classification on network performance. We investigate the effects of Constant Bit Rate (CBR), Variable Bit Rate (VBR), Available Bit Rate (ABR) and Unspecified Bit Rate (UBR) models on various network traffic types such as voice, video and data. For voice traffic, we examine key QoS parameters including Jitter, Packet Delay Variation and End-to-End Delay. For video traffic, we evaluate Packet Delay Variation and End-to-End Delay. Additionally, we analyze Download Response Time for data traffic to assess the influence of QoS on the ATM network. Our results demonstrate that CBR and VBR are preferred for real-time traffic like voice and video, providing low delay and jitter. The simulation approach enables us to test various configurations and gain insights not possible in hardware tests. Our findings can help network operators determine the optimal QoS settings and tradeoffs when deploying ATM for modern multi-service networks.

Figures (9)

• Figure 1: The network topology.
• Figure 2: The SubNet topology.
• Figure 3: Packet delay variation for 4 services.
• Figure 4: Packet End-to-End Delay for 4 services.
• Figure 5: Jitter for 4 services.