学位论文详细信息
Voice Over IP Performance Diagnosis
SNMP;Voice over IP;self-similarity;clock synchronization
Adhikari, Akshay Arun ; Dr. George N. Rouskas, Committee Member,Dr Wushow Chou, Committee Member,Dr. Douglas S. Reeves, Committee Chair,Adhikari, Akshay Arun ; Dr. George N. Rouskas ; Committee Member ; Dr Wushow Chou ; Committee Member ; Dr. Douglas S. Reeves ; Committee Chair
University:North Carolina State University
关键词: SNMP;    Voice over IP;    self-similarity;    clock synchronization;   
Others  :  https://repository.lib.ncsu.edu/bitstream/handle/1840.16/1098/etd.pdf?sequence=1&isAllowed=y
美国|英语
来源: null
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【 摘 要 】

We investigate a framework for assessing the readiness of a network to support Voice over IP (VoIP) at the pre-deployment stage. In this framework, VoIP traffic is synthesized on the network, while simultaneously monitoring the health of network devices and links using the Simple Network Management Protocol(SNMP). Using this framework, we try to understand whether SNMP can be used to detect which network links or devices, if any, cause poor VoIP quality. First, we investigate the limitations of the end-to-end VoIP quality measurement, and SNMP measurement framework used in lab experiments. We quantify the errors in end-to-end VoIP quality measurements, and in SNMP measurements, so that these errors can be taken into account depending on the application at hand. Next, we use our lab experiments to understand how VoIP performance metrics like delay and loss are affected by offered load on a link. From our initial experiments with faulty synthetic traffic generators, we find that even at low utilization, bursty network traffic can significantly degrade VoIP quality, and small timescale measurements, which are impractical with SNMP, are required to detect the problems. However, using realistic emulation of network traffic in the lab, we find that when network problems are severe and last for long periods of time, they can be easily detected using SNMP. We also present a case study of VoIP assessment data collected from a real network, where we again successfully used SNMP to detect the network links that caused poor quality

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