International Journal of Multidisciplinary Research
and Modern Education
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Effect of Internet Path Selection in Congested Network
for High Level Data Transmission
J. Britto Dennis*, C. Namasivayam** & A. Dinesh Kumar***
* Assistant Professor, Department of Information Technology, Dhanalakshmi Srinivasan
Engineering College, Perambalur, Tamil Nadu, India.
** PG Scholar, Department of Networking Engineering, Dhanalakshmi Srinivasan
Engineering College, Perambalur, Tamil Nadu, India.
*** Assistant Professor, Department of Mathematics, Dhanalakshmi Srinivasan
Engineering College, Perambalur, Tamil Nadu, India.
Abstract:
This Paper presents the Effect of internet path selection in congested Network. And
increase the Delivery Ratio of High-Priority Data. To provide more importance to the high
priority data by degrading the performance of low priority data. Internet Path selection
work is a best-effort packet delivery model. Address differentiated data delivery in the
presence of congestion in wireless networks. Congestion-Aware Adaptive Routing (CAR)
schemes only use channel-based information to identify the congestion status. Propose a
class of algorithms that enforce differentiated routing based on the congested areas of a
data priority network. We propose Path congestion- aware adaptive routing (PCAR). This
routing method based on following techniques. 1) Path-congestion-aware selection
strategy that concurrently considers switch congestion and channel congestion 2) Increase
the switching device buffer size. 3) Assign the high level priority to important data .4)
Choose the alternate virtual path. The proposed result PCAR scheme can achieve a high
saturation throughput with a development of 20.4%–50.7% compares to existing routing
schemes. The PCAR method also includes a VLSI architecture, it has higher area efficiency
with an development of compared with the existing router designs. We deployed SIFR on
Planet Lab nodes and compared the performance of SIFR to the default Internet routing.
SIFR outperforms IP-path selection by providing higher on-screen perceptual video
quality.
Index Terms: Adaptive Routing, Congestion Prediction, Video QoE & Path Selection
1. Introduction:
Multimedia streaming over IP networks is poised to be the dominant Internet
traffic in the coming decade. Industry forecasts that the sum of all forms of video [TV,
video on demand, Internet, and peer-to-peer (P2P)] will be approximately 86% of global
consumer traffic by 2016. As multimedia service providers deploy services on top of
packet-switched networks that compete with cable-based content providers, there is an
ever-growing need to provide superior quality of experience (QoE) .There are various
reasons to expect current Internet path selection policies to be suboptimal in assuring
superior QoE. Current wide area routing protocols choose paths solely based. On hop
count and autonomous system (AS) connectivity and are, as such, not optimized for
QoE. For reasons of scalability, connectivity information between AS is further filtered
during routing advertisements. As a result, a video source has limited routing options
when sending its packets, especially during times of an outage. However, the Internet
itself comprises billions of interconnections, and the probability that there are alternate
paths that can perform better is high. An empirical understanding of QoE degradations
along an Internet path, and simple alternative path selection strategies that go beyond
default IP-routing, would help us overcome some of these limitations.
This paper presents a large-scale measurement-based study on the effects of
Internet path selection on video-QoE and investigates ways to improve it using
application-specific policies and redundant Internet paths. We seek answers to the
following questions: 1) what degrades video QoE in the Internet, and where in the path
do these outages frequent? 2).
References:
1. Senthil Kumar P, Abirami R & Dinesh Kumar A, “Fuzzy Model for the Effect of
rhIL6 Infusion on Growth Hormone”, International Conference on Advances in
Applied Probability, Graph Theory and Fuzzy Mathematics, Page Number 246252, 2014.
2. Senthil Kumar P, Dinesh Kumar A & Vasuki M, “Stochastic Model to Find the
Effect of Gallbladder Contraction Result Using Uniform Distribution”, Arya Bhatta
Journal of Mathematics and Informatics, Volume 6, Issue 2, Page Number 323328, 2014.