RED Tuning for TCP Performance on the Mobile Ad Hoc Networks

Transcription

1 RED Tuning for TCP Performance on the Mobile Ad Hoc Networks Shin-Jer Yang and Yung-Chieh Lin Dept. of Computer and Information Science, Soochow University, Taipei, Taiwan Abstract Mobile Ad Hoc NETworks (MANET) does not need the fixed base station to process the link operation. In the past several years, many researchers have focused on studies of Routing Protocol over the MANET. Currently, the pervasion of Internet causes TCP as the standard transmission protocol for most of the networking applications. The RED is one of congestion avoidance methods in TCP. Due to the unconstrained movement of the mobile nodes, TCP is unable to notice network congestion or link down to activate related controls on the MANET. The network will search and establish a new transmission path, when an unwarned link down occurs on the MANET. The average queue length of RED will be longer than MinThreshold, if the link re-establishment costs too much of time. Then, it will invoke the sender to perform relative congestion control. Hence, it may degrade the TCP performance before the link reestablish completely. The main purpose of this paper is to adjust related RED parameters for evaluating the performance through the simulation on the MANET. Consequently, we did propose the tuning strategies in RED to improve the TCP performance based on final simulation results. Keywords: Tuning 1. Introduction MANET, TCP, RED, Static/Dynamic MANET (Mobile Ad Hoc NETworks) is a wireless communication network environment, which consists of a group of autonomous mobile nodes. The property of this configuration is fast to implement, because it not requires a fixed wireless base station or access point to control the transmission of packets. Each mobile node has dual roles that act both a host and a router simultaneously. When a mobile node acts as a router, it needs to take care of the tasks for searching, establishing and maintaining the routing between source and destination nodes. Moreover, the arbitrary movement for each mobile node without any constraint causes the network topology constantly changing, and then hard to expect. The main purposes of this paper are to adjust related RED parameters in which affect the TCP performance, and to propose a novel method of dynamic tuning to apply on the MANET. Actually, the TCP protocol is originally designed for the wired network. But, the TCP congestion controls that are affected by the mobility of MANET is very difficult to determine whether the disconnection is caused by the network congestion or the unwarned wireless link down, while the TCP is applied to a wireless network. Therefore, the TCP performance will be degraded under that situation. On the other hand, the wireless network is sometimes required to connect Internet, which employs the TCP as transmission protocol for most of the existing network applications. The remainder of this paper is organized as follows. In Section 2, we describe the background and examine the problems of TCP on the MANET. In Section 3, we illustrate how to adjust RED parameters and propose the dynamic tuning approach of RED, which can be applied on the MANET. In Section 4, we analyze the result of the simulated experiment and then propose tuning guideline. Finally, Section draws the conclusion and indicates the future works. 2. Preliminaries and Related Studies In a wireless network, the movement of the mobile node leads to the link be disconnected and the ACK signal cannot be received by the sender. The mobile node that can move free and arbitrarily around the MANET will cause the unwarned link down of original transmission path. This situation produces that the congestion control of TCP misjudges the occurrence of network congestion and activates its control procedure to affect the transmission performance []. Many researchers have proposed some solutions for this misjudging issue of TCP

2 routing on the MANET. But, most of these solutions are trying to insert a feedback message in the routing protocol to notify sender about the link down of current transmission path [2, 4]. Although this approach can solve the problem of link down that cannot be detected by TCP, it is necessary to modify the existing TCP and routing protocol. Figure 1. RED Packet Drop Probability RED (Random Early Detection) is primarily running on a router and each router calculates their current occupied Average Queue Length (AvgLen) [3,11]. If the AvgLen is smaller than MinThreshold, the packet will be kept and sent to the queue waiting for the transmission; if the AvgLen is longer than MaxThreshold, all of packets will be dropped; if the AvgLen is between MinThreshold and MaxThreshold, the drop probability of the packet will be a linear function of a number between and MaxP (Max. Probability) as shown in Figure 1. The network will search and establish a new transmission path, when an unwarned link down occurs on the MANET. If the link re-establishment costs too much of time, the AvgLen will be longer than MinThreshold and causes the sender to perform relative congestion control mechanism. Hence, it may reduce the transmission speed in advance and then degrade the TCP performance before the link reestablish completely. 3. RED Tuning Approach for TCP Performance As stated in Section 2, we know that the TCP performance is affected by TCP congestion control. Actually, there are some influence parameters of TCP performance, including RTO (Retransmission TimeOut), Congestion Window, and related RED (Random Early Detection) parameters of congestion control. The parameters in RED have no standard value to conform and adjust resiliently. In this section, we introduce how to tune the value of RED parameters and to explain the static tuning approach. Also, we propose a novel method of dynamic tuning to apply on the MANET. All of these RED parameters settings for TCP performance can be tuned according to the simulation results listed in Section 4. The network congestion can be avoided by randomly dropping a few packets on a router with RED to notify the TCP sender for early detecting the congestion status. However, the unwarned link down occurs when the MANET employs RED, and the AvgLen increases rapidly and even exceeds than MinThreshold during the link reestablishment in routing. The subsequent arriving packets will be discarded when the AvgLen is over MaxThreshold, therefore it degrades the TCP performance. Hence, the related parameters of RED such as AvgLen, MinThreshold, and MaxThreshold can affect the overall performance. In this paper, we adjust these RED parameters as mentioned above and simulate these parameters with different mobility rate models to find out the static parameter combinations on the MANET. In addition, we propose a dynamic Self- Configuration method for tuning these parameters to tolerate the amount of packets increased by the link reestablishment. The similar methods of the RED dynamic tuning on the wired network have proposed by many researchers [7]. First, we briefly describe the content of RED parameters, which adjusted in this paper. The combination setting for the MinThreshold and MaxThreshold parameter is: MaxThreshold = MinThreshold * X (1) We take the suggestion of RED parameters, which discussed in the paper of Tao Ye and Shivkumar Kalyanaraman, and set the value of X to 3 [7]. The Equation 2 to calculating the AvgLen is as follow [3]: AvgLen = (1 Weight) * AvgLen + Weight * SampleLen (2) Equation 2 is a formula for computing low-pass filter, which avoids the abruptly increment for AvgLen that caused by a transient congestion in the network. In this equation, the value of Weight is between the range of and 1. If Weight is too large, the transient congestion cannot be filtered out. On the contrary, if Weight is too small, it cannot reflect the current real queue length instantly. Therefore, we need to set a proper Weight value according to the different network environments. In addition to adjusting MinThreshold and MaxThreshold parameters, we refine the proper weight value. The static parameter combinations of RED will be described in Section 4, and the TCP performance can be assessed with these parameters combinations for different mobility rate models. In addition to the static parameters setting, we also propose the dynamic tuning method on selfconfiguration parameters. As depicted in Figure 2, the

3 average queue length of f1 is rapidly increasing and exceeding the MinThreshold, when the movement of f2 causes the link down between f1 and f2. But, this situation will be eliminated after a new link rebuilt. If we adjust the value of MinThreshold properly and let it temporarily tolerate the abrupt packet increment, the discarding of all of subsequent packets can be avoided. If ( MinThreshold < minu ) MinThreshold + = *(min U min L ) ; Else { If ( Counter > ) { Counter - -; If ( MinThreshold > minl ) MinThreshold - = *(min U min L ) ; LastTId = CurTId ; END Figure 2. The Link Down in the MANET The operation flow of dynamic tuning for MinThreshold as depicted in Figure 3, the rationale describe as follows. When the packet on the top of queue keeps retained and do not deliver it out, the value of Counter increase 1. If this situation still exists and when Counter is larger than A (where A is a value of threshold), we can determine that the link is already downed and need to set the higher value of MinThreshold to temporarily accommodate the additional packets. If this situation not exists, the value of MinThreshold is gradually adjusted to its original value. In our procedure, MinThreshold can be adjusted in the range of min L ~ min U, where min L means the initial value of MinThreshold and min U means MaxThreshold. The number of packets to increase or to decrease on each time is * (min U - min L ), where the range of is ~ 1. In addition, CurTId represents the next packet to be transmitted and LastTId means to record the previous packet to be transmitted. As described above, the execution logic of this procedure is illustrated as follows: // Set initial value for the variables InitialValue( Counter, A, CurTId, LastTId, maxl, maxu, ) ; // When a new packet arrive, execute the procedure below Procedure DynamicAdjRED() BEGIN { // The next packet to be transmitted CurTId = PacketQueue.head ; If ( CurTId = = LastTId ) { Counter + + ; If ( Counter > A ) Figure 3. The Operation Flow of RED Dynamic Tuning 4. Simulation Design and Results Analysis In this section, we describe the simulation environment of MANET and then analyze and tune the performance of RED parameter on various mobility rates based on simulation results. 4.1 Simulation Environment and Design Issues Currently, ns-2 simulator already included many objects in which developed by Josh Broch et al. for MANET environment [1]. In this subsection, we illustrate the settings for each primitive parameter in ns-2 simulator used in this paper is listed in Table 1. We refer to the method proposed by Josh Broch and set the six different pause time. The simulation time of each run is seconds and each pause time generates 1 different movement models, so there are 6 different movement models in total. The second of pause time means constantly moving for any a node and seconds of pause time means existing in the standstill status for another a node.

4 Table 1. The Parameters of ns-2 Simulator # of Node 3 Active range 1m 1m Movement Model Random-walk Pause Time (sec.),, 1, 2, 3, Topology Flat Application Layer FTP Transport Layer TCP Packet Size 12 Bytes Max. TCP window 32 packets Routing Protocol DSDV Data Link Layer protocol RED queue, BSD ARP, MAC Antenna Omnidirectional, 4.2 Results Analysis and Tuning Guideline In this paper, we take Packet Delivery Ratio, Throughput, and Transmission Time as the metrics of the performance assessment. We describe the computation of Packet Delivery Ratio first, the equation is: Preceived PDi, Hop h (3) Psend PD i means the Packet Delivery Ratio of the i-th transmission pair when Hop equals h, P send means the number of packets delivered by the sender, and P received means the number of packets received by the receiver. The equation of Throughput is: Pj j TPi, Hop h (4) Tj j TP i means the Throughput of the i-th transmission pair when Hop equals h, T j means the required time to transmit the j-th packet (Pj). In order to evaluate the performance of RED effectively, we select the transmission pair whose Hop is larger than 2 for computing. The Average Throughput (ATP p ) of certain movement model is the average of TP i, the equation is: ATP p = Average ( TP i ) i = 1 ~ n () Furthermore, the equation of total transmission time for each transmission pair to transfer n packets when Hop equals h as follow: TTi n Tj j 1, Hop h (6) The equations of Average Transmission Time for each packet and a certain movement model are as follows: TTi TTpi, Hop h (7) Ptotal ATT p = Average( TTp i ) i = 1 ~ n (8) Owing to the mobile node can free moving without any constraint, its transmission link varies often. To assess the influence made by link change, we use 6 different mobility rates to generate the movement model for the simulation of each parameter setting, and then compare the Packet Delivery Ratio, Throughput, and Average Transmission Time of each parameter combinations to find out the better combination for improving TCP performance on the MANET. Next, we will analyze the simulation results for static tuning of RED parameters, as well as the RED dynamic tuning. As described in Section 3, the RED static parameter settings listed in Table 2. R11 means Weight =.2, MinThreshold = 1, MaxThreshold = 3 and so on. The Weight value is definitely related to the average queue length in RED, so we justify the suitable Weight value that it can respond actual queue length as average queue length. In [3], they proposed that the value of Weight set to.2. However, this value is appropriate usage in a general wired network. In order to observe TCP performances of different movement models clearly, we set Weight to.2,.2,.2, and 1 based on the characteristics of MANET. Table 2. RED Static Parameter Combinations Weight Min = 1 Min = Min = 1 Min = Max = 3 Max = Max = 3 Max = 4.2 R11 R12 R13 R14.2 R21 R22 R23 R24.2 R31 R32 R33 R34 1 R41 R42 R43 R44 In this simulation experiment, each Weight of the Packet Delivery Ratios has their different parameter combinations defined in Table 2 are presented in Figure 4 and Figure. When Wight equals.2 or.2, the difference between Packet Delivery Ratios of each parameter combinations is small. When Weight equals.2 or 1, the intense changing of average queue length and higher probability of exceeding MinThreshold enlarge the difference between Packet Delivery Ratios of each parameter combinations. At first, the Throughput for different parameter combinations is shown in Figure 6 and Figure 7. Since the traffic congestion or route bottleneck is not often occurred in the MANET, the queue length cannot feedback in time to cause a poor throughput when the value of Weight gets small. Moreover, the Average Transmission Time for different parameter combinations is shown in Figure 8 and Figure 9. The unstable of transmission route produces the longer transmission time when Hop is 3. Especially in the frequent movement environment, the Average Transmission Time will have up to ten times the value of the situation when Hop is equal to 2.

5 W Figure 4. The Packet Delivery Ratio when Weight =.2 &.2 Packet Delivery Ratio W Figure. The Packet Delivery Ratio when Weight =.2 & W Figure 6. Throughput when Weight =.2 & W Figure 7. Throughput when Weight =.2 & 1 Average Transmission Time (s) W Figure 8. The Average Transmission Time when Weight =.2 &.2 Average Transmission Time (s) 2 1 W Figure 9. The Average Transmission Time when Weight =.2 & 1 Table 3. The Assessment Grades of each Performance Metric Performance Metric Good Medium Poor Packet Delivery Ratio > 97% 97%~ 9% < 9% Throughput (Kbps) > ~ 22 < 22 Average Transmission Time (Sec.) < ~. >. According to the experiment s results, we set the assessment grade for each performance metric as listed in Table 3. Based on the grades defined in Table 3, we list the tuning rules of each performance metric for every RED parameter combinations in both frequent movement and less movement environments, as shown from Table 4 to Table 6. Also, all the Pause Time of Frequent movement and Less movement in Tables 4, and 6 are the ranges of to 1 seconds and 2 to seconds, respectively. Due to the dynamic properties of MANET different from a general wired network, static parameter combinations of each RED will have different TCP performances under different movement. Hence, we can select proper parameters in which depend on the constraints and applications of their real environments. For instance, in the application of meeting room, since the mobile nodes are standstill in most of time, we can choose R31 or R41 parameter settings according to our tuning rules.

6 Table 4. RED Static Parameter Tuning Rule the Packet Delivery Ratio Parameter combinations Frequent Movement Less Movement R11 Medium Medium R12 Good Medium R13 Medium Medium R14 Medium Good R21 Medium Medium R22 Good Good R23 Medium Good R24 Good Good R31 Poor Poor R32 Medium Good R33 Good Good R34 Good Good R41 Poor Poor R42 Medium Poor R43 Good Good R44 Poor Good Table. RED Static Parameter Tuning Rule Throughput Parameter combinations Frequent Movement Less Movement R11 Poor Medium R12 Poor Good R13 Medium Medium R14 Poor Medium R21 Good Medium R22 Good Poor R23 Medium Poor R24 Poor Poor R31 Good Good R32 Medium Medium R33 Medium Good R34 Medium Poor R41 Good Good R42 Good Medium R43 Poor Medium R44 Good Medium Table 6. RED Static Parameter Tuning Rule the Average Transmission Time Parameter combinations Frequent Movement Less Movement R11 Medium Medium R12 Good Good R13 Medium Medium R14 Medium Medium R21 Poor Good R22 Medium Poor R23 Medium Poor R24 Medium Poor R31 Poor Good R32 Medium Poor R33 Poor Medium R34 Medium Medium R41 Medium Good R42 Good Medium R43 Medium Medium R44 Poor Medium Figure 1. The Packet Delivery Ratio of RED Dynamic Tuning Throughput (Kbps) Figure 11. Throughput of RED Dynamic Tuning Average Transmission Time (s Figure 12. The Average Transmission Time of RED Dynamic Tuning Finally, according to the RED dynamic tuning stated in Section 3, we set the following parameters for this method: min L =, min U =, A =, and =.1. The performance metrics of Packet Delivery Ratio, Throughput, and Average Transmission Time generated by RED dynamic tuning and static parameter setting are shown from Figure 1 to Figure 12. Therefore, we can identify that the Packet Delivery Ratio, Throughput, or Average Transmission Time can get better performance under frequent movement environment. Hence, RED dynamic tuning can really improve the TCP performance on the MANET. However, according to the experiment s results, RED dynamic tuning method seems to only improve the TCP performance under frequent movement environment. Since dynamic tuning only performs on the Internet layer, we did not verify whether physical

7 layer is link down or network congestion. When the probability of link down is larger than the probability of network congestion, the dynamic parameter tuning of RED is only better for improving the performance under frequent movement and not for all environments on the MANET.. Conclusions and Future Works In this paper, we discussed some issues of TCP on the MANET environment, and refined some related parameters that influence the TCP performance. Based on the principle of standard TCP protocol, we can adjust some related parameters of RED in the congestion avoidance. Then, we proposed tuning strategies for RED static parameters under different TCP metrics. We can select the proper parameters of RED based on the constraints and applications of their real environments. Furthermore, we proposed a novel method of RED dynamic tuning that it is more appropriate for MANET. Through the simulation, the result indicates that RED dynamic tuning method can enhance the TCP performance, especially in the frequent movement on the MANET. In summary, static and dynamic tuning strategies in RED can improve the TCP performance and avoid the network congestion on the MANET based on final simulation results. In the future, we will assess different parameter values and tune other TCP parameters that affect the TCP performance on the MANET. The dynamic tuning of RED parameters can improve TCP performance for frequent movement on the MANET, but we did not verify whether the physical layer is link down or network congestion. However, we will further study on this issue and also propose a better tuning rule to improve the TCP performance for different mobility rate on the MANET environments Consequently, the proposed RED tuning approach can be the reference for further studies in QoS features and other applications on the MANET. 6. References [1] J. Broch, D. A. Maltz, D. B. Johnson, Y.Hu, and J. Jetcheva, A Performance Comparison of Multihop Wireless Ad Hoc Network Routing Protocols, In Proceedings of ACM/IEEE Int. Conf. OnMobile Computing and Networking, Oct. 1998, pp [2] K. Chandarn, S. Raghunathan, S. Venkatesan, and R. Prakash, A Feedback Based Scheme for Improving TCP Performance in Ad-Hoc Wireless Networks, In Proceedings of International Conference on Distributed Computing Systems, Amsterdam, 1998, pp [3] S. Floyd and V. Jacobson, Random Early Detection Gateway for Congestion Avoidance, IEEE/ACM Trans. on Networking, Vol. 1, No. 4, Aug. 1993, pp [4] G. Holland and N. H. Vaidya. Analysis of TCP Performance over Mobile Ad Hoc Networks, In Proceedings of th Annual International Conference on Mobile Computing and Networking MOBICOM, August [] Ruy de Oliveira and Torsten Braun, TCP in Wireless Mobile Ad Hoc Networks, Technical Report, IAM-2-3, July 22. [6] Larry L. Perterson and Bruce S. Davie, Computer Networks: A System Approach, 2nd Edition, Morgan Kaufmann Inc., 22. [7] Tad Ye and Shivkumar Kalyanaraman, Adaptive Tuning of RED Using On-line Simulation, In Proceedings of IEEE GLOBECOM, 22, Vol. 3, pp