In-service monitoring for cell loss quality of service violations in ATM networks

This chapter aims to report on the performance of voice and video traffic over two popular backbone network technologies, namely Gigabit Ethernet (GbE) and Asynchronous Transfer Mode (ATM). ATM networks are being used by many universities and organizations for their unique characteristics such as scalability and guaranteed Quality of Service (QoS), especially for voice and video applications. Gigabit Ethernet matches ATM functionality by providing higher bandwidth at much lower cost, less complexity, and easier integration into the existing Ethernet technologies. It is useful to be able to compare these two technologies against various network performance metrics to find out which technology performs better for transporting voice and video conferencing. This chapter provides an in-depth performance analysis and comparison of GbE and ATM networks by extensive OPNET-based simulation. The authors measure the Quality of Service (QoS) parameters, such as voice and video throughput, end-to-end delay, and voice jitter. The analysis and simulation results reported in this chapter provide some insights into the performance of GbE and ATM backbone networks. This chapter may help network researchers and engineers in selecting the best technology for the deployment of backbone campus and corporate networks.

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Quality of Service Monitoring, Diagnosis, and Adaptation for Service Level Management

Engineering Reliable Service Oriented Architecture - Advances in Web Technologies and Engineering ◽

10.4018/978-1-60960-493-6.ch003 ◽

2011 ◽

pp. 41-58

Author(s):

Guijun Wang ◽

Changzhou Wang ◽

Haiqin Wang ◽

Rodolfo A. Santiago ◽

Jingwen Jin ◽

...

Keyword(s):

Quality Of Service ◽

Real Time ◽

Service Level ◽

Management Framework ◽

Qos Management ◽

Service Monitoring ◽

Service Level Management ◽

Qos Monitoring ◽

Monitoring Service

A key requirement in Service Level Management (SLM) is managing the Quality of Services (QoS) demanded by clients and offered by providers. This managing process is complicated by the globalization and Internet scale of enterprise services and their compositions. This chapter presents two contributions to the QoS management task for SLM. First, instead of considering monitoring as an isolated service, it incorporates a monitoring service as an integral part of a comprehensive QoS management framework for SLM. Second, it includes a diagnosis service as an integral part of the QoS management framework. Using the data fed from monitoring service, diagnosis service detects system condition changes and reasons about the causes of detected degradation in networked enterprise system. With condition detection and situation understanding, the QoS management framework can then proactively activate adaptation mechanisms to maximize the system’s ability to meet QoS contract requirements of concurrent clients. Using this framework, enterprise systems can provide real time automated QoS management to optimize system resources in meeting contract requirements. This approach is validated using QoS management services integrated in a publish/subscribe style of SOA. Benefits of QoS monitoring, diagnosis, and adaptation services for responsiveness SLM are demonstrated via experiments.

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