scholarly journals IP Packet Delay Variation Metric for IP Performance Metrics (IPPM)

2002 ◽  
Author(s):  
C. Demichelis ◽  
P. Chimento
Keyword(s):  
Performance Metrics ◽  
Packet Delay ◽  
Ip Packet ◽  
Delay Variation

Accuracy of the IP packet delay variation estimation

2009 ◽  
Author(s):  
Andrey Sokolov
Keyword(s):  
Packet Delay ◽  
Ip Packet ◽  
Delay Variation

scholarly journals Defining Quantiles for Estimating IP Packet Delay Variation in NGN Core Networks

2011 ◽  
Vol 1 (03) ◽  
Author(s):  
Dao Ngoc Lam ◽  
Le Nhat Thang ◽  
Le Huu Lap
Keyword(s):  
Network Performance ◽  
Estimation Method ◽  
Packet Delay ◽  
Distribution Functions ◽  
Estimation Accuracy ◽  
Core Network ◽  
Approximate Methods ◽  
Core Networks ◽  
Ip Packet ◽  
Delay Variation

Traffic delay is one of the important metrics used for evaluating network performance. Delay and delay variation characteristics of IP packets transferred over multi-section networks can be derived, estimated or composed from component distributions of IP package delay in each network section. Approximate methods are needed in the cases of unknown or complicated delay distribution functions, which are unavailable or unusable in practice. The ITU-T has proposed a method for estimating IP packet delay variation. One of noticeable factors affecting the estimation accuracy is the packet delay population quantile which has not been adequately considered. The objective of this paper is to examine the optimal range of quantiles used for estimating the IP packet delay variation in the NGN (Next Generation Network) core networks. The paper is composed from the following ideas. Firstly, several concepts and mathematical formulas related to delay metrics based on probability and statistics theory are defined. The approximate method of ITU-T for estimating the IP packet delay variation in a multi-section network is revised. Then, another method based on convolution for composing the empirical IPTD distribution functions is proposed for the same target as the first one. Secondly, a number of test cases are implemented to measure the IP packet delay on several sections of an NGN core network. Sample data are used for computing and estimating the IP packet delay variation for multi-section networks by two methods with certain hypotheses. Finally, these methods are compared and evaluated both theoretically and empirically in regards to the estimation accuracy versus quantiles of the IP packet transfer delay. The best range of quantiles is determined to ensure the accuracy of the estimation method applied for the NGN core network.

scholarly journals EVALUATING PERFORMANCE OF HYBRID NETWORKS BY USING LATENCY AND PDV

2013 ◽  
pp. 72-76
Author(s):  
ANUSHRI DIXIT ◽  
JINAL KOTHARI ◽  
ASHWINIKSHIRSAGAR ASHWINIKSHIRSAGAR ◽  
PROF. RAJESH KOLTE
Keyword(s):  
Routing Protocol ◽  
Routing Protocols ◽  
Performance Metrics ◽  
Packet Delay ◽  
Hybrid Networks ◽  
Hybrid Network ◽  
Simulation Tool ◽  
Different Types ◽  
Packet Tracer ◽  
Delay Variation

Hybrid networks are widely used in networking sector. They combine the finest features of both Wired and Wireless networks to give optimum results. Using different types of routing protocols, the capabilities of a hybrid network will be demonstrated using certain performance metrics. In this paper, we will be simulating real-time scenarios of three networks of different sizes. Each of these networks will be implemented with single routing protocol i.e. Enhanced Interior Gateway Routing Protocol (EIGRP). The networks will be simulated using Cisco Packet Tracer simulation tool. Furthermore, we have evaluated the performance of the networks by considering performance metrics like network latency and packet delay variation.

Packet Delay Variation Correction for Time Sensitive Networking with Frame Preemption

2020 ◽  
Author(s):  
Silviu Adrian Sasu ◽  
Achim Autenrieth ◽  
Jim Zou ◽  
Jorg-Peter Elbers
Keyword(s):  
Packet Delay ◽  
Delay Variation

scholarly journals The effects of Packet Delay Variation on the perceptual quality of video

2010 ◽  
Author(s):  
Selim Ickin ◽  
Karel De Vogeleer ◽  
Markus Fiedler ◽  
David Erman
Keyword(s):  
Packet Delay ◽  
Perceptual Quality ◽  
Delay Variation

scholarly journals Artificial Intelligence Enabled Routing in Software Defined Networking

2020 ◽  
Vol 10 (18) ◽  
pp. 6564 ◽  
Author(s):  
Yan-Jing Wu ◽  
Po-Chun Hwang ◽  
Wen-Shyang Hwang ◽  
Ming-Hua Cheng
Keyword(s):  
Artificial Intelligence ◽  
Performance Metrics ◽  
Packet Delay ◽  
Software Defined Networking ◽  
Dynamic Routing ◽  
Learning Ability ◽  
Control Plane ◽  
Monitoring Period ◽  
Data Plane ◽  
The Impact

Software defined networking (SDN) is an emerging networking architecture that separates the control plane from the data plane and moves network management to a central point, called the controller. The controller is responsible for preparing the flow tables of each switch in the data plane. Although dynamic routing can perform rerouting in case of congestion by periodically monitoring the status of each data flow, problems concerning a suitable monitoring period duration and lack of learning ability from past experiences to avoid similar but ineffective route decisions remain unsolved. This paper presents an artificial intelligence enabled routing (AIER) mechanism with congestion avoidance in SDN, which can not only alleviate the impact of monitoring periods with dynamic routing, but also provide learning ability and superior route decisions by introducing artificial intelligence (AI) technology. We evaluate the performance of the proposed AIER mechanism on the Mininet simulator by installing three additional modules, namely, topology discovery, monitoring period, and an artificial neural network, in the control plane. The effectiveness and superiority of our proposed AIER mechanism are demonstrated by performance metrics, including average throughput, packet loss ratio, and packet delay versus data rate for different monitoring periods in the system.

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