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\title{A Comprehensive Analysis of Congestion Control Using Random Early Discard (RED) Queue}
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\begin{document}

             \author[1]{Dr. Md. Abdullah al  mamun}

             \author[2]{Md.  Rubel}

             \author[3]{Mridul Kanti  Das}

             \affil[1]{  }

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\date{\small \em Received: 26 August 2011 Accepted: 19 September 2011 Published: 2 October 2011}

\maketitle


\begin{abstract}
        


Normally all the congestion control method discard the received packet when the queue is full but it is a great problem for speed of data transfer at present. There are many ways to solve this problem. Random Early Detection (RED) algorithm is one of the most famous and powerful method to improve the performance for TCP Connection. In terms of queue management RED drops packet in considered router buffer to adjust the network traffic behavior according to the queue size. We want to investigate how high priority user datagram protocol (UDP) traffic affects the performance of lower priority Transmission Control Protocol (TCP) and proof that RED is the better for controlling the Traffic when they share the same bottleneck link with one or two classes of service.

\end{abstract}


\keywords{IETF, RED, AQM, BW, TCP Variants, NS-2, TCL and OTCL.}

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\let\tabcellsep& 	 	 		 
\section[{INTRODUCTION}]{INTRODUCTION}\par
Random Early Detection (RED) is the first active queue management algorithm proposed for deployment in TCP/IP networks. The basic idea behind an active queue management algorithm is to convey congestion notification early to the TCP end points so that they can reduce their transmission rates before queue overflow and sustained packet loss occur. "It is now widely accepted that the RED controlled queue performs better than a drop-tail queue. It is an active queue management algorithm" \hyperref[b0]{[1]}. "The tail drop algorithm, a router buffer as many packets as it can, and drops the packet when it cannot buffer. If buffers are constantly full, the network is congested" \hyperref[b2]{[2]}. RED addresses these issues. It monitor the average queue size and drops packets based on statistical probabilities. If the buffer is almost empty, all incoming packets reaccepted. As the queue grows, the probabilities for dropping incoming packet are dropped too. RED is more fair than trail drop in the sense of it does not possess a bias against burst traffic that use only a small portion of the bandwidth. The more the more a host transmits, likely it is that packets are dropped. The most common technique of queue management is a trail drop. In this method packets are accepted as long as there is space in the buffer when it becomes full, incoming packets are dropped. This approach results in dropping large number of packets in the time congestion. This can result in lower throughput and TCP synchronization \hyperref[b3]{[3]}. However TCP includes eleven variants (Tahoe, FullTcp, TCP/Asym, Reno, Reno/Asym, Newreno/Asym, Sack1, DelAck and Sack1/DelAck) as source and five (TCPSink, TCPSink/Asym, Sack1, DelAck and Sack1/DelAck) as destination, implementation in NS-2 \hyperref[b4]{[4,} {\ref 5]}. The base TCP has become known as TCP Tahoe. TCP Reno attaches one novel mechanism called Fast Recovery to TCP Tahoe \hyperref[b4]{[4]}. In addition, TCP Newreno employs the most recent retransmission mechanism of TCP Reno. \hyperref[b5]{[6]}. The use of Sacks allows the receiver to stipulate several additional data packets that have been received out-of-order within one dupack, instead of only the last in order packet received  {\ref [5]}. TCP Vegas offers its own distinctive retransmission and congestion control strategies. TCP Fack is Reno TCP with forward acknowledgment \hyperref[b6]{[7]}. Transmission Control Protocol (TCP) Variants Reno, NewReno, Vegas, Fack and Sack1 are implemented in NS-2. RED supervises the average queue size and drops packets based on statistical likelihoods \hyperref[b3]{[3]}. 
\section[{II.}]{II.}\par
RANDOM EARLY DETECTION a) RED Parameter Setting Average queue size avg is formulated \hyperref[b0]{[1]} as:\par
Where, wq is the queue weight, q is current queue size. wq should have lower value for bustier traffic; more weight is given in this case for the historic A III.  We that when threshold increase then variation course in received among various TCP variants and all arriving packets are received when average queue size exceeds max threshold or less than minimum threshold then packets are dropped which is shown in above all tables and corresponding figure. We found that Newreno TCP variants is the best because mean number of received packet is high mean number of dropped packet is low.    
\section[{PERFORMANCE ANALYSIS OF RED MODEL a) Variation in Threshold Value}]{PERFORMANCE ANALYSIS OF RED MODEL a) Variation in Threshold Value}\begin{figure}[htbp]
\noindent\textbf{}\includegraphics[]{image-2.png}
\caption{\label{fig_0}Figure1:Figure4:}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{}\includegraphics[]{image-3.png}
\caption{\label{fig_1}}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{}\includegraphics[]{image-4.png}
\caption{\label{fig_2}Figure5:Figure6:}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{1} \par 
\begin{longtable}{}
\end{longtable} \par
  {\small\itshape [Note: Number received packet for various TCP variants with respect to threshold for simulation time 70s]} 
\caption{\label{tab_0}Table 1 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{2} \par 
\begin{longtable}{}
\end{longtable} \par
 
\caption{\label{tab_1}Table 2 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{3} \par 
\begin{longtable}{}
\end{longtable} \par
 
\caption{\label{tab_2}Table 3 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{4} \par 
\begin{longtable}{P{0.2255663430420712\textwidth}P{0.3864886731391586\textwidth}P{0.060517799352750805\textwidth}P{0.05914239482200648\textwidth}P{0.05914239482200648\textwidth}P{0.05914239482200648\textwidth}}
2011\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \\
October\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \\
46\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \\
TCP variants\tabcellsep 15\tabcellsep 20\tabcellsep 25\tabcellsep 30\tabcellsep 35\\
Reno\tabcellsep 854\tabcellsep 1185\tabcellsep 845\tabcellsep 711\tabcellsep 733\\
Newreno\tabcellsep 721\tabcellsep 763\tabcellsep 752\tabcellsep 774\tabcellsep 741\\
Vegas\tabcellsep 821\tabcellsep 777\tabcellsep 685\tabcellsep 686\tabcellsep 625\\
Fack\tabcellsep 800\tabcellsep 721\tabcellsep 713\tabcellsep 644\tabcellsep 761\\
Sack1\tabcellsep 864\tabcellsep 870\tabcellsep 749\tabcellsep 813\tabcellsep 786\\
TCP variants\tabcellsep 15\tabcellsep 20\tabcellsep 25\tabcellsep 30\tabcellsep 35\\
Reno\tabcellsep \multicolumn{5}{l}{1452 1532 1333 1778 1398}\\
Newreno\tabcellsep \multicolumn{5}{l}{1458 1465 1501 1631 1538}\\
Vegas\tabcellsep \multicolumn{5}{l}{1345 1578 1350 1498 1538}\\
Fack\tabcellsep \multicolumn{5}{l}{1412 1754 1252 2379 1422}\\
Sack1\tabcellsep \multicolumn{5}{l}{1501 1339 1595 1358 1179}\\
\multicolumn{2}{l}{TCP variants 15}\tabcellsep 20\tabcellsep 25\tabcellsep 30\tabcellsep 35\\
Reno\tabcellsep \multicolumn{5}{l}{2659 2635 2376 1946 2300}\\
Newreno\tabcellsep \multicolumn{5}{l}{2701 2546 2032 2169 2303}\\
Vegas\tabcellsep \multicolumn{5}{l}{2254 2255 2301 2432 2178}\\
Fack\tabcellsep \multicolumn{5}{l}{2802 2462 2897 2131 2376}\\
Sack1\tabcellsep \multicolumn{5}{l}{2269 2416 2201 2554 2082}\\
TCP variants\tabcellsep 15\tabcellsep 20\tabcellsep 25\tabcellsep 30\tabcellsep 35\\
Reno\tabcellsep 3142\tabcellsep 3403\tabcellsep 3312\tabcellsep 3323\tabcellsep 2902\\
Newreno\tabcellsep 3383\tabcellsep 3220\tabcellsep 3204\tabcellsep 3265\tabcellsep 2928\\
Vegas\tabcellsep 2624\tabcellsep 2749\tabcellsep 2778\tabcellsep 2538\tabcellsep 2799\\
Fack\tabcellsep 3545\tabcellsep 3088\tabcellsep 2856\tabcellsep 2681\tabcellsep 4298\\
Sack1\tabcellsep 3888\tabcellsep 3216\tabcellsep 3051\tabcellsep 3232\tabcellsep 3409\end{longtable} \par
  {\small\itshape [Note: © 2011 Global Journals Inc. (US) Global Journal of Computer Science and Technology Volume XI Issue XVIII Version I]} 
\caption{\label{tab_3}Table 4 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{5} \par 
\begin{longtable}{P{0.10323886639676112\textwidth}P{0.7467611336032388\textwidth}}
\tabcellsep and TCP\\
\multicolumn{2}{l}{Times 70s 140s 210s 280s}\\
U\tabcellsep 15 675 1294 1996 2586\\
\tabcellsep 20 797 1222 1803 2694\\
D\tabcellsep 25 758 1187 2127 2633\\
\tabcellsep 30 795 1484 2085 2794\\
P\tabcellsep 35 749 1336 1963 2783\\
T\tabcellsep 15 566 1352 2725 2457\\
\tabcellsep 20 665 1606 2374 3284\\
C\tabcellsep 25 637 1438 2425 3694\\
\tabcellsep 30 548 1656 2247 2832\\
P\tabcellsep 35 834 1614 2413 3438\end{longtable} \par
 
\caption{\label{tab_4}Table 5 :}\end{figure}
 			\footnote{A Comprehensive Analysis of Congestion Control Using Random Early Discard (RED) Queue} 			\footnote{© 2011 Global Journals Inc. (US)} 		 		\backmatter  			 \par
From the aforementioned comparison of the performance it is found that TCP is better than UDP because packet received is higher in it with respect to UDP. That is why packet loss is lower in TCP. In case of packet drop, it is clear those packet drop is higher in UDP than TCP and also occur more congestion in it. It is possible to control congestion in TCP using RED model.\par
IV. CONCLUSION 8.			 			  				\begin{bibitemlist}{1}
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\bibitem[Islam et al. ()]{b2}\label{b2} 	 		\textit{An experimental analysis of random early discard (RED) queue for congestion control},  		 			M D Islam 		,  		 			M D Morshed 		,  		 			M D Islam 		,  		 			Mejbahul Azam 		.  		2011.  	 
\bibitem[Lang ()]{b5}\label{b5} 	 		\textit{Evaluation of different TCP versions non-wireline environments},  		 			Tanja Lang 		.  		2002.  		 			The University of South Australia, Institute for Telecommunications Research 		 	 
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\end{bibitemlist}
 			 		 	 
\end{document}
