International Journal of Computer Applications (0975 – 8887) Volume 65– No.6, March 2013 1 A Comparative Analysis of Queue Management Techniques using NS-2 Simulator P. T. Mahida Department of IT, SVMIT, Bharuch Kinjal Patel Department of IT, SVMIT, Bharuch Nayan Vanza Department of IT, SVMIT, Bharuch Siddharth Patel Department of It, SVMIT, Bharuch ABSTRACT Effectively and fairly allocating resources to the competing users in a network is a major issue to meet the demand for higher performance nowadays. Queue management enhances the efficiency of transfers and cooperates with Transmission Control Protocol (TCP) in adapting the intense flow of the congestion in the network. The shared resources of a network are bandwidth of the link and queues on the routers and switches. As too many packets are queued awaiting transmission, the queues overflow and the packets have to be dropped which results into congestion. The queue management algorithm, which is applied to a router, plays an important role in providing Quality of Service (QoS). In this paper, we have presented a simulation based comparison and evaluation of four popular queue management schemes: Stochastic Fair Queuing (SFQ), Random Early Detection (RED), Random Exponential Marking (REM) and Droptail in terms of packet drop rate and delay. Simulation is done using Network Simulator (ns2.34) Our Simulation results indicate that REM performed better in terms of packet drop rate and RED performs better in terms of end-to-end delay. Keywords RED, SFQ,REM, Droptail,, Packet drop rate, ns2. 1. INTRODUCTION The Internet traffic generates stream of data packets in the network with different traffic profiles and leads to congestion. Congestion refers to a network state where a node or link carries so much data that it may decrease network service quality, resulting in queuing delay, frame or data packet loss and blocking of new connections [1]. Congestion is an important issue which researchers focus on in the TCP network environment. To control the congestion, there are two types of algorithms: Source-side Algorithm and Sink side Algorithm. Source side Algorithm is sender side and another is sink side algorithm. To keep the stability of the whole network, congestion control algorithms have been extensively studied. Queue management method employed by the routers is one of the important issues in the congestion control study. During congestion, large number of packets, face delay or even get dropped due to queue overflow. As a result congestion results in degradation of the throughput and large packet loss too. Due to very high traffic load, the performance degrades completely and almost no packets are delivered to sink nodes. To resolve the problem, many congestion control algorithms [2,3] are proposed. Many of the algorithms are based on the evaluation of the feedback from the congested network. Some algorithms detect congestion from warn packets sent back to the source while in other sources observe change in few network parameter like delay, packet drop and detect congestion[4]. In queue management algorithms there are three different types of algorithms, active, passive and proactive like DropTail, SFQ, RED and REM. Drop Tail is the most widely used queue management method in today’s IP networks. RED is mostly the default method implemented in the routers nowadays. RED monitors the average queue size and drops packets based on statistical probabilities. SFQ is a simple implementation of the fair queuing algorithms family. It's less accurate than others, but it also requires less calculation while being almost perfectly fair. REM is an active queue management scheme that aims to achieve both high utilization and negligible loss and delay in a simple and scalable manner [5, 6]. We have analyzed performance of different queue management algorithms by applying them on different simulation scenario at different transfer rate of packets. In this paper, we will compare popular Queuing Management Techniques, Random Early Detection [7], DropTail, Random Exponential Marking (REM)[3] and Stochastic Fair Queuing (SFQ) in different aspects , such as delay and Packet Drop Rate. In section II, we have given overview of Queue management techniques. Section III describes OPNET implementation and simulation model and topology. Section IV gives performance comparisons with various queue management techniques by simulation in ns2. Conclusion is presented in section VI. 2. QUEUE MANAGEMENT TECHNIQUES Queue management is defined as the algorithm that manages the length of packet queues by dropping packets when necessary or required to be dropped. From the point of dropping packets, queue management can be classified into three categories as in the figure [7]. Fig 1: Queue Managment Techniques