Performance Analysis and Enhancement of TCP in Presence of Jitter in Wireless Networks
Author(s) -
Goudru N.G,
Vijaya Kumar B P
Publication year - 2016
Publication title -
international journal of computer network and information security
Language(s) - English
Resource type - Journals
eISSN - 2074-9104
pISSN - 2074-9090
DOI - 10.5815/ijcnis.2016.06.02
Subject(s) - jitter , computer science , tcp friendly rate control , packet loss , network congestion , throughput , tcp westwood plus , transmission control protocol , quality of service , tcp global synchronization , cubic tcp , computer network , real time computing , wireless network , tcp tuning , network packet , control theory (sociology) , wireless , telecommunications , control (management) , artificial intelligence
In wireless networks two types of losses namely congestion loss and transmission loss are significant. One of the important transmission losses is jitter. Variation in inter-arrival time is called jitter. When jitter value is greater than half of the average round trip time cause timeout loss and sender window size falls to one packet resulting reduction in throughput and degradation in the quality of service (QoS). In this paper, we are discussing a new model for transmission control protocol (TCP) which is capable of changing its window size based on the feedback. In the new model TCP is added with intelligence so that it can distinguish the type of losses. If the loss is due to congestion, congestion control algorithm is invoked and loss is due to jitter immediate-recovery algorithm is invoked to recover from the throughput loss. The technique also provides an endto-end congestion control. The performance of TCP is further enhanced by discussing stability. Time-delay control theory is applied for the analysis of asymptotic stability. The stability boundaries of random early detection (RED) control parameter Pmax and jitter control parameter β are derived. Using the characteristic equation of Hermite matrix an approximate solution of q(t) (queue length) which converges to a given target value is derived. The results are analyzed based on graphs and statistical data using Matlab R2009b.
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