TCP Congestion Window Adaptation Through ... - Semantic Scholar

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IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, VOL. 59, NO. 9, NOVEMBER 2010

TCP Congestion Window Adaptation Through Contention Detection in Ad Hoc Networks Xin Ming Zhang, Member, IEEE, Wen Bo Zhu, Na Na Li, and Dan Keun Sung, Senior Member, IEEE

Abstract—In multihop ad hoc networks over 802.11, the real bandwidth-delay product (BDP) cannot reach a value as large as in wired networks due to contention through wireless shared channels. As a result, conventional congestion-control algorithms cause an overshooting window problem and result in poor throughput in ad hoc networks. In this paper, we split the real round-trip time (RTT) into two parts: 1) congestion RTT and 2) contention RTT. We reveal that the contention RTT has nothing to do with the BDP and that the BDP is determined by only the congestion RTT if a link with the worst contention status does not lead to link breakage. An inadequate use of contention RTT causes a Transmission Control Protocol (TCP) congestion window overshooting problem. We propose a novel mechanism called congestion window adaptation through contention detection, which provides a more accurate method of estimating the contention status. Based on this mechanism, we present a congestion window adaptation method to limit the window size from overshooting. Simulation results show that our proposed mechanism outperforms the conventional TCP and the enhanced mechanisms called TCP with contention control and TCP with a maximum window. Index Terms—Ad hoc networks, bandwidth-delay product (BDP), congestion window, contention round-trip time (RTT).

I. I NTRODUCTION

A

N ad hoc network is a network with completely selforganizing and self-configuring capabilities, requiring no existing network infrastructure or administration. The Transmission Control Protocol (TCP) is a transport-layer protocol designed to provide a reliable end-to-end delivery of data over unreliable networks, and it performs well over conventional wired networks. However, TCP encounters some challenges in multihop ad hoc networks [1], [2]. Due to the instability and shared wireless channels, ad hoc networks may suffer from impairments, e.g., route failures, drops due to Medium Access Control (MAC) contentions and interference, and random chanManuscript received June 24, 2009; revised June 19, 2010; accepted August 10, 2010. Date of publication August 30, 2010; date of current version November 12, 2010. This work was supported in part by the National Natural Science Foundation of China under Grant 61073185 and Grant 60673171 and by the National Grand Fundamental Research 973 Program of China under Grant 2006CB303006 and by the open research fund of National Mobile Communications Research Laboratory, Southeast University (No. 2010D15). The review of this paper was coordinated by Dr. T. Taleb. X. M. Zhang is with the School of Computer Science and Technology, University of Science and Technology of China, Hefei 230027, China, and also with the National Mobile Communications Research Laboratory, Southeast University, Nanjing 210096, China (e-mail: [email protected]). W. B. Zhu and N. N. Li are with the School of Computer Science and Technology, University of Science and Technology of China, Hefei 230027, China (e-mail: [email protected]; [email protected]). D. K. Sung is with the Department of Electrical Engineering, Korea Advanced Institute of Science and Technology, Daejeon 305-701, Korea (e-mail: [email protected]). Digital Object Identifier 10.1109/TVT.2010.2070522

nel bit errors. In theory, TCP should work without considering the implementation at lower layers, but the performance of TCP significantly degrades in such unreliable networks. Route failures, which may significantly affect the network performance, have been considered an important research issue for a long time. We have also investigated this problem, which includes an optimization of the TCP protocol, considering route failures in dynamic ad hoc networks [3]. In this paper, we focus on the effect of contention and interference factors on the network performance. Multihop ad hoc networks that adopt IEEE Standard 802.11 MAC layer suffer from contention and the hidden-node problem. A contention problem in wireless networks occurs when multiple adjacent nodes contend for a shared channel to transmit their packets. Another problem is the hidden-node terminal problem. When two nodes communicate with each other, other nodes that are within the interference area of these two nodes cannot access the channel. As a result, when a node attempts to transmit a packet, it should contend with the neighbor nodes that are not adjacent to access the wireless channel. The extended hidden-terminal problem [4] is a representative issue that results from the aforementioned property. In this problem, some node may not reply to request-to-send (RTS) packets from a neighbor node, because it cannot access the channel, which has been occupied for communication with some other neighbor. If an RTS sender cannot receive a clear-to-send (CTS) reply within a maximum number of retransmissions (seven times in general), it regards this situation as a link failure, and drops the data packets. A TCP congestion-control method is designed to increase the amount of segments up to network capacity, which is represented as bandwidth-delay product (BDP), and Chen et al. [5] analyzed the BDP in both wired and wireless networks. In conventional networks, segments can pass through links back to back, and then, these segments can chock up the whole network pipe. However, a receiver should start to forward a segment after completely receiving it from the sender in multihop ad hoc networks. In addition, considering the channel contention and channel interference problem, the BDP of a TCP connection is much smaller than in wired networks. The value of the TCP congestion window (cwnd) should be proportional to the BDP, and a congestion-control algorithm in wired networks attempts to keep the value of cwnd value near the BDP. However, as aforementioned, the real BDP in multihop ad hoc networks is much smaller than in wired networks. If we still adopt the original method [6] to aggressively control the cwnd, which always tends to go beyond the real BDP, the whole network is overloaded and operates under a bad

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ZHANG et al.: TCP CONGESTION WINDOW ADAPTATION THROUGH CONTENTION DETECTION IN AD HOC NETWORK

Fig. 1.

TCP cwnd overshooting problem.

congestion environment. This case is one example of a TCP cwnd overshooting problem, and this problem significantly degrades the network performance. Fig. 1 shows a cycle of the TCP cwnd overshooting problem. During a cwnd upgrade and normal data transfer step, cwnd overshooting (phase 1) causes a TCP network to be overloaded soon (phase 2). In this situation, a large number of data segments need to be transferred, and severe MAC contentions may accordingly occur. As a result, many segment losses may occur (phase 3), and these segment losses trigger retransmission timeouts (RTOs; phase 4) and subsequent slow start (phase 5) at the TCP source node. Data segments again start to be injected into the network (phase 6), with a lower transmission rate. However, soon, an increase in the cwnd will exceed an appropriate level in accordance with the real BDP, and it causes a return to phase 1. The TCP cwnd value overshoots and frequently resets in the problem cycle, and a large variation in the cwnd significantly reduces the throughput. Fu et al. [7] analyzed the effect of MAC contentions on routing as a supplement. In Fig. 1, after a frame loss occurs due to MAC contention, a routing agent infers a route failure (phase 7) and orders the source node to reestablish a route (phase 8). If the route is reestablished through route discovery, more control packets pass through the network, and it makes the congestion status even worse. To solve the aforementioned TCP congestion window overshooting problem, we propose a novel mechanism called congestion window adaptation through contention detection (CWA–CD) in this paper. The main contribution of this paper is listed as follows. 1) We split the real round-trip time (RTT) into two parts: 1) congestion RTT and 2) contention RTT. We reveal that the contention RTT has nothing to do with the BDP and that the BDP is determined by only the congestion RTT if a link with the worst contention status does not lead to link breakage. An inadequate use of the contention RTT causes a TCP congestion window overshooting problem. 2) We define a variable, variance of contention RTT per hop (V CRH), to evaluate the degree of link contentions. First, it can represent the degree of link contention. Second, the variance is a random variable that reflects the contention situation observed during the recent observation window. Third, the variance can also reflect the status of a bottleneck.

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3) We make a modification of the TCP congestion window adaptation mechanism. The CWA–CD adapts the cwnd value based on not only RTO and acknowledgement (ACK) but also the V CRH. It is timely and accurate, and thus, it is effective in limiting the congestion window size from overshooting. The rest of this paper is organized as follows. Section II introduces the related work. Section III describes a TCP congestion window overshooting problem with some new insight. Section IV proposes a TCP CWA–CD mechanism and describes differences between the proposed and the conventional mechanisms. Section IV compares, through simulations, the performance of four mechanisms: 1) the original protocol; 2) TCP contention control; 3) an adaptive setting of the TCP maximum window; and 4) the proposed CWA–CD. Finally, Section VI presents concluding remarks and future work. II. R ELATED W ORK The TCP congestion window overshooting problem has been studied, and the overshooting problem occurs due to the following two aspects: 1) the severe contention in the MAC layer and 2) the inaccurate adaptation of congestion window in the TCP layer. Based on these reasons, previous studies could be classified into four categories: 1) the reduction of intraflow contention; 2) the reduction of interflow contention; 3) the measurement of the region capacity; and 4) adaptive congestion control mechanisms. Intraflow contention refers to the contention between the packets that belong to the same TCP connection. It includes two major parts: 1) the contention between data packets and 2) the contention between data and ACK packets. Fu et al. [7] analyzed the impact of multihop wireless channel on TCP throughput. They presented two important conclusions. First, for a given network topology and TCP connection mode, there is a special TCP congestion window W∗ . Second, in a static wireless ad hoc network, the major reasons of packet losses are conflict and interference caused by link-layer contentions. Simultaneously, based on the results of simulation, Fu et al. indicated that the value of congestion window may not be maintained at the range around W∗ during the practical work of TCP, but it varies until it reaches a value much larger than W∗ . Based on these two important conclusions, they proposed an adaptive pacing scheme. In the scheme, a node that transmits a packet should wait for a certain time after the backoff time. We can observe that adaptive pacing can mitigate the intraflow contention problem, but the waiting time is not precise. In addition, Luo et al. [8] proposed a paced TCP mechanism in which the pace time between packets is adjusted according to varying RTT values. Elrakabawy et al. [9] proposed a new TCP congestioncontrol algorithm in wireless ad hoc networks, which is called TCP with adaptive pacing (TCP–AP). TCP–AP measures the change of round-trip delay and determines the network congestion status based on the delay. TCP–AP estimates the appropriate transmission rate according to varying round-trip delays and the four-hop delay, and the algorithm also introduces rate control during the congestion window adjusting to avoid

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outburst flows. The implementation of TCP–AP is rather simple, because it only depends on the end-to-end delay without requiring the information of the routing and link layers. Shen et al. [10] proposed a mechanism that tries to deal with the intraflow contention through a rigorous arrangement of transmission at the MAC layer. They set a variable n to indicate the number of the packets that have already been transmitted. When successfully receiving an ACK, the value of n increases until it reaches the maximum, and then, it is forbidden to transmit. If there is a failure in receiving an ACK, it is also not appropriate to no longer transmit. This way, all nodes obtain a certain right to use the channel. The mechanism makes arrangements for accessing the channel in the MAC layer, but it does not control the transmission rate in the transport layer. Interflow contention refers to the contention between the packets that belong to different TCP connections. Ye et al. [11] presented a mechanism that extends the routing mechanism to separate the TCP flows. It is called congestion-aware routing (CAR). In the CAR mechanism, Ye et al. are concerned with the interaction between the TCP flows and the congestion mechanism. At first, they evaluated the effect of spatial reuse in a network with a central control function through simulation. Then, they considered a distributed work environment for practical applications. Each node computes its local congestion weight to indicate the local situation and broadcasts the value to its neighbors. They modified the routing layer protocol. In the route discovery phase, the route is chosen based on the average value of congestion weights; in other words, the route with the smallest congestion weight is selected to transmit packets. Experimental results show that the CAR mechanism yields better performance than the shortest path-first routing mechanism. However, there is still much space for mitigating contention conflicts and interference. Zhai et al. [12] also made some achievements on this issue. They considered both intraflow contention and interflow contentions. For intraflow contentions, they provided a higher priority to the nodes that have just received packets in accessing the channel. The approach can not only deliver each packet to the destination quickly but can also prevent the source from injecting too many segments to the network. For interflow contentions, Zhai et al. also proposed an effective solution. In their solution, all transmission nodes, including the source, should know the congestion information of the network, and when the network is in congestion, its transmission rate should be controlled to a very small value. This way, when a TCP flow is in congestion, its transmission rate is decreased, its contention state is also mitigated, and thus, other TCP flows can have more bandwidth. Rangwala et al. [13] presented a rate control mechanism based on additive increase and multiplicative decrease. In the mechanism, the congestion on wireless channel is considered a problem at a region but not at a node. Simultaneously, they proposed a distributed rate control mechanism. The mechanism estimates the available bandwidth for each region, and then, the available bandwidth is allocated to the competitive flows in the region. In the mechanism, the bandwidth estimation is very important. It needs to ensure high accuracy, and its bandwidth

allocation must also be reasonable. Through this mechanism, the network performance is improved. There have been several mechanisms for improving the TCP performance by controlling the TCP transmission rate according to the network capacity. Fu et al. [7] indicated that, in wireless ad hoc networks, a small TCP congestion window can help obtain better performance. Inspired by the research, there are more studies on this issue. Chen et al. [5] analyzed the BDP in a multihop ad hoc network in detail, and they attempted to set the congestion window limit (CWL) according to the upper bound of BDP. This method is simple but effective. Because the real BDP is still below the BDP upper bound, aggressive upgrading for cwnd causes the congestion window to stay near the CWL. However, a typical overshooting problem still exists in their proposed method [5], i.e., ⎞ ⎛ m n di + dj ⎠ (4dmax ) (1) BDP _U B = S × ⎝ i=0

j=0

where BDP _U B represents the upper bound of BDP in ad hoc networks, and S is the segment size. The remaining numerator is the sum of per-hop delays through forward path (di ) and return path (dj ), i.e., RTT, and it shows that the BDP is proportional to path length. dmax is the maximum perhop delay among di and dj , and it proves that the BDP is tightened by the bottleneck link, which suffers from the worst contention. The coefficient 1/4 is determined from a simplified but representative chain node model in which the maximum spatial reuse is 1/4. This derivation concludes an ideal upper bound of the BDP. Triantafyllidou et al. [14] proposed a related mechanism and introduced a time-based expression for the BDP, which can be used for dynamic adaptation of the value of CW N Dmax , i.e., CW N Dmax =

packet_length × RT TT CP 2(n − 1) × M AX{di }

(2)

where di is the delay at node i. In wired networks, BDP is the product of bandwidth and RTT. It represents the load capacity of the link. However, in wireless networks, the load capacity depends on several factors, e.g., transmit power, node density, and buffer size. Thus, in real networks, due to complicated contention situations, it is hard to measure the real BDP. Hamadani and Rakocevic [15] proposed a TCP contention control mechanism to alleviate the cwnd overshooting problem. They defined two parameters for estimating the throughput and contention status through the path, and cwnd adaptation is determined by four possible combination results of these two parameters. Although the monitoring method on links is somewhat complicated, it is still not precise enough to represent the network situation. Moreover, it cannot steadily work due to inconstant cwnd adaptation. Our proposed mechanism [16] adopted a similar idea to the TCP contention control mechanism [15] with two parameters for estimating throughput and contention, and it is more accurate. However, there is still a problem in this mechanism, because these two parameters are defined according to the status at the bottleneck link without considering the case of the whole


path. The bottleneck is, indeed, an important factor in case of congestion. On the other hand, contentions cause quite a different situation. We will explain this contention problem in the next section. Fu et al. [7] presented a contention problem in 802.11 without considering the TCP congestion window, and their scheme drops packets with some probability according to the contention status. This active packet drop scheme results in slow start and alleviates the contention, but this type of reset may impair the stability of the TCP cwnd. In traditional TCP mechanisms, congestion control includes slow start, congestion avoidance, fast retransmission, and fast recovery. In wireless ad hoc networks, this coarse adjustment is no longer comfortable. Currently, many studies have been dedicated to modify the approach to adjust the congestion window. Nahm et al. [17] proposed a modified cwnd adaptation mechanism, in which the TCP congestion window is allowed to increase at a certain fractional rate for every RTT. Papanastasious et al. [18] proposed a slow congestion avoidance (SCA) scheme. At the congestion avoidance in the traditional TCP mechanism, the cwnd value linearly increases, i.e., when the ACK packets of all data packets are received, the cwnd value is increased by one maximum segment size (MSS). In the SCA scheme, there exists a variable ca_increase_thresh for indicating the number of ACKs received before congestion window adaptation. When the number of ACKs is small than ca_increase_thresh, the value of cwnd value keeps unchanged. Once the number reaches ca_increase_thresh, the cwnd value is increased by one MSS. This way, the cwnd value slowly increases. Nahm et al. [19] proposed a fractional window increment (FeW) mechanism that adjusts the congestion window to reduce the overshooting problem. They assumed that the current congestion window is W and that the sender sends W packets and receives W ACKs in each RTT. Once an ACK is received, W is updated according to the following formula: W new = W current + a/W current. Here, a is a parameter between (0,1), and it is related to the round-trip delay. This way, the congestion window of TCP slowly increases, and it becomes less aggressive. The aforementioned mechanisms for adjusting the congestion window attempt to change the cwnd value with much finer granularity, but they do not calculate the cwnd value according to the network capacity. In the aforementioned four categories of mechanisms, the reduction of intraflow and interflow contentions attempt to mitigate the contention problem at the MAC layer without lessening the TCP load. However, the overshooting problem still exists. The most effective mechanisms belong to the third category, i.e., the measurement of the region capacity. However, the link-layer status has not been exactly measured, and the granularity of cwnd adaptation is rough. The fourth category, i.e., adaptive congestion-control mechanisms, has no idea of the link layer status and sets the cwnd value in the TCP layer, which is blind. Our ultimate target is to alleviate the TCP congestion window problem from overshooting by steadily adapting the congestion window to a real BDP level for a long time. The aforementioned mechanisms have a common deficiency in the accuracy of

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Fig. 2. Congestion RTT and contention RTT.

estimating link contention. We need to find a cross-layer enhancement method with the following features: 1) more precise estimation of link contention status and 2) more steady control of TCP cwnd to an appropriate level. III. C ONGESTION W INDOW OVERSHOOTING In this section, we focus on RTT and BDP, and we thoroughly illustrate a congestion window overshooting problem with respect to RTT and BDP. A. Congestion Window Overshooting Problem BDP is a key factor in determining the transmission rate of segments, because it can be obtained through the direct measurement of the network status. We consider a network pipe. The width of the pipe represents the bandwidth at a bottleneck, and the length represents the RTT. As a result, the BDP is the product of the bottleneck bandwidth and RTT, which is given in (1), regardless of the coefficient 1/4. In conventional networks, packets could continuously flow through the pipe. In ad hoc networks with link contention, a node should access a channel before sending data segments. It needs to defer transmission for a period of contention delay, for this reason, at each link, and then, data segments cannot continuously flow through the network pipe. If we eliminate this halt time of flow by leaving only the time of continuous data flow, this approach is not different from the conventional BDP. In multihop ad hoc networks, the BDP is determined by the time of continuous flow of data segments. Based on the aforementioned result, we split the real RTT into two parts—congestion RTT and contention RTT—as shown in Fig. 2. The contention RTT is the sum of contention delays through the path, which is a specific but essential factor in multihop ad hoc networks. On the other hand, the remaining part in RTT is the congestion RTT, which is made up of the endto-end transfer delay of all the links through the path. Note that this end-to-end transfer delay of link contains queuing delay, transmission delay, and processing delay but no contention delay, and we will call it the link transfer delay in this paper. The duration of continuous segment flow in the pipe is determined by the only congestion RTT. Therefore, BDP is determined by the congestion RTT and not the contention RTT. However, in a path with severe contention, the total transmission rate of segment flow decreases to a large extent, resulting in reduced throughput. The contention RTT is not related to BDP, and there is no bottleneck effect in the contention RTT. In other words, a contention in a path is not determined by a link with the worst

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node to the next hop, considering the contention delay. The remaining terms 1/4 ∗ RT Treal in (1) correspond to the link transfer delay, which is the irrationality in (1). In addition, (1) is restricted in the aforementioned chain topology, and the modified BDP equation (3) is more general. IV. CWA–CD We propose a new mechanism called CWA–CD. In this section, we introduce a new parameter called the V CRH and then explain the reason that this parameter can be used to estimate the degree of MAC contentions. Based on this parameter, we improve the TCP congestion window adaptation mechanism to solve the overshooting problem. Fig. 3. Typical chain topology.

contention status. However, this conclusion has an important precondition that the link with the worst contention status does not lead to link breakage. However, the bottleneck link with the worst contention status should not completely be neglected, because as the contention becomes worse at an intermediate node, there is a higher possibility of a link failure. We now investigate the TCP congestion window overshooting problem. An increase in the congestion window allows an increase in the amount of segments up to the level of BDP. If the original congestion-control mechanism [6] is directly applied over 802.11, the TCP congestion window is adjusted according to the real RTT (directly measured at the TCP agent). However, the congestion RTT, which is related to the network pipe volume, is smaller than the real RTT. As a result, the congestion window is likely to exceed the level of the BDP. Furthermore, the higher the ratio of the contention RTT to the congestion RTT is, the greater the overshooting problem becomes. B. Understanding the BDP Equation Based on the aforementioned insight, we present a modified equation of BDP as follows: BDP = (S/Dcongestionmax ) × RT Tcongestion

(3)

where Dcongestionmax is the maximum link transfer delay. We revisit (1), which is originally given in [5]. Fig. 3 shows the network scenario with a typical chain topology, where the transmission and interference ranges are 250 and 550 m, respectively. In this scenario, when node D receives packets from node C, all nodes that remain in the range of interference (Ri) of node D should be blocked. In other words, when the CD link is under transmission, the DE, EF, and FG links are under contention. Assuming that the transfer delay per hop is the same for all links, the contention delay is three times longer than the link transfer delay. Through the whole path, the congestion RTT is one fourth of the real RTT. The coefficient 1/4 in (1) is derived from the aforementioned analysis result. However, the conclusion about the bandwidth in (1) is different from ours. dmax in (1) is the per-hop transfer delay, which includes the link transfer delay and the contention delay, and thus, S/dmax is the rate of packet sent from a

A. V CRH We define a parameter called the V CRH. First, the value of the contention RTT is gathered through packet forwarding. In the MAC agent, the contention delay is measured as the interval between a packet arrival at the head of line of the queue and the delivery time to the physical layer. We set a time stamp in the fragment (frame) so that it can keep track of the contention delay of the fragment in the current node. The contention delay is accumulated hop by hop and recorded in the fragment, and finally, the TCP destination copies the sum from the segment into the ACK. We should note the following two points here: 1) the delayed ACK function [20] should be disabled and 2) we disable the fragmentation function in simulation to simplify the fragment sampling of the contention delay. Thus, the MAC agent could copy the sum of the contention delay directly from the fragment to the packets. In real implementation, the MAC agent could choose the contention sample in the last fragment during the fragmentation phase and copy it from the packet. The sample value of the contention delay is also recorded in the ACK, and the TCP source obtains the contention RTT from the newly received ACK. Second, the deviation of the contention RTT of the latest n segments can be figured out at the source node, and it is called the variance of contention RTT (V CR). Finally, the V CRH is estimated as the V CR divided by the number of hops in a given route. There are three reasons that we adopt the V CR to evaluate the degree of link contentions. First, it can represent the degree of link contention. If the possibility of channel contentions is larger, the MAC contention window needs to be larger, and the backoff time is selected in a much wider range; thus, a higher contention probability results in a larger variation of the contention delay. We evaluate this jittery through variance, and it could directly reflect the contention possibility. Second, the variance is a random variable that reflects the contention situation observed during the recent observation window. Third, the variance can also reflect the status of a bottleneck. Supposing that there is a bottleneck in one of the two paths, the path with the bottleneck has a larger V CR. If there is a bottleneck link due to severe contentions, there is a high probability of link breakage. In this mechanism, three details should be explained. First, we eliminate the effect of path length. After obtaining the


contention RTT, we can calculate the variance and then divide it by the number of hops. Then, we can obtain the deviation for each hop. Second, we consider a round-trip path instead of a forward path used in the conventional method [15], because ACKs in the backward route are also an important factor for detecting link contention. Third, we need to set an appropriate value of n, i.e., the required number of samples for estimating the V CR. If n is very large, it increases the memory size and calculation cost of nodes. However, it slowly responds to a change due to a long-term average effect. On the other hand, if n is very small, it is very sensitive to a small change and may cause a large value of V CRH on different RTTs. In the implementation, we use the following recursive equations to update the V CR once the source receives a new ACK: Ek Vk Ek Vk

Ek−1 × (k − 1) + CRnew for k < n = k 2 2 Vk−1 + Ek−1 × (k − 1) + CRnew − Ek2 = k for k < n CRnew − CRold for k >= n = Ek−1 + n 2 2 2 Vk−1 + Ek−1 × n + CRnew − CRold − Ek2 = n for k >= n

(4)

(5) (6)

(7)

where k is the sampling sequence of newly received ACKs, n is the maximum number of samples, and Ek and Vk are the expectation and the variance of CR (contention RTT) from the latest k (when k < n) or n (when k >= n) ACKs. CRnew is the newly obtained CR value, and CRold is the old CR value. If k < n, Vk is obtained from (4) and (5), because the number of sample entries k is different from n. These two equations are used during the short transient time right after the TCP connection initialization or the timeout. In this case, CRold is not needed. If k >= n, Vk is obtained from (6) and (7). In this case, a new CR sampling value contained in a new ACK pushes out an old entry n times ago, and we can update the V CR according to the new CR value itself. When Vk is newly obtained, we can obtain the V CRH by dividing Vk by the number of hops. B. TCP Congestion Window Adaptation Mechanism We set a threshold parameter V CRH_th, and if the V CRH exceeds this threshold, the degree of contention in the network is regarded to be severe. Whenever a TCP source receives a new ACK, it updates the value of the V CRH before checking whether this value is larger than or equal to the V CRH_th value. If it is larger, cwnd is decreased by one MSS instead of an increase in the congestion window. This approach could effectively restrain the congestion window from overshooting. If the RTO expires, which implies that the network is in a bad congestion or contention status, we need to check whether the V CRH is larger than or equal to V CRH_th before halving the congestion window threshold(ssthresh) [6]. If the V CRH is larger, the network status is regarded to be very bad, and we reset the cwnd to 2 ∗ MSS and enable the slow-start step. Otherwise,

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Fig. 4. Grid network.

the contention status of the network is not so bad, and we just halve the cwnd. We should notice that the V CRH sampling should be reset after an RTO, and thus, the subsequent slow start of cwnd is not affected by the low value of V CRH obtained before the RTO expires. This new mechanism regards a large variation of contention RTT as an evidence of contention status in contrast with [15]. This mechanism is more accurate, because it evaluates the contention from a series of contention RTT values. This mechanism is timelier, because it eliminates the outmoded values long before, but in the conventional TCP contention control, the outmoded contention information affects the calculation of V CRH. On the other hand, our congestion window adaptation mechanism is simpler and more stable. First, upon reception of a new ACK, the V CRH result indicates how we can adjust the value of cwnd, and even if the estimation on contention is different from reality, the resulting cwnd is just slightly modified. However, in the conventional TCP contention control, once the estimation on throughput and contention is worse, the cwnd is reset. Second, if a packet loss occurs, we determine whether we can minimize the cwnd, depending on the contention situation. If the contention status is not severe, it is beneficial for alleviating the large variation of cwnd and increasing the throughput by just halving the congestion window. Our new mechanism is more robust and more accurate. V. S IMULATION R ESULTS We implement the original TCP, the conventional TCP with contention control mechanism [15], the adaptive setting of TCP maximum window [10], and our proposed TCP CWA–CD mechanism in the ns-2 network simulator [21], and we compare the performance of these four mechanisms. To highlight the effects of contentions and interference and to minimize the effect of route failures as much as possible, we focus on a grid topology as a static scenario. We analyze the network performance and characterize the congestion window among the four mechanisms. We also present simulation results in a dynamic random topology. A. Grid Topology Fig. 4 shows a static grid network as our experiment topology with m2 nodes. In a stationary environment without mobility, we can investigate the behavior of contentions in this grid

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TABLE I EXPERIMENT PARAMETERS IN GRID TOPOLOGY

Fig. 5. TCP throughput versus the V CRH_th.

network. The distance between two adjacent nodes is set to be 150 m, and the transmission and interference radii are set to 250 and 550 m, respectively. In the experiment, we generate a different scale of grid networks, with m ranging from 4 to 9. Because we assume that there are 2m connections in the grid, this topology causes a large number of contentions among these connections. In each row, a TCP connection is assumed to set up from the left end node to the right end, and similarly, in each column, a TCP connection is assumed to set up from the bottom end node to the top end node. All these TCP connections are of the same parameters, i.e., a segment size of 512 B and a maximum window size of 32. In the experiment, we randomly choose ten connections, and thus, each data point in the figures takes the expectation of ten sample values. V CRH_th is an important parameter in our mechanism. We first investigate the performance for varying this parameter value to obtain the best V CRH_th value. We choose n = 6 in the V CRH, which means that the latest six segments are considered to evaluate the contention status at most. The simulation time is 500 s. The V CRH_th values are set from 0.4 to 0.9, with an interval of 0.05. Fig. 5 shows the throughput performance for varying V CRH_th values. In the implementation of our mechanism, we choose V CRH_th = 0.6 based on Fig. 5, because in most scenarios, very good throughput performance is achieved with this value. We now investigate the characteristics of TCP congestion window among the four mechanisms: 1) the original TCP; 2) TCP contention control; 3) TCP with maximum window; and 4) TCP with CWA–CD. We set the experiment parameters according to Table I. Fig. 6 shows the TCP cwnd value of a connection during a period of time. In this figure, the y-axis indicates the cwnd value with the unit of segments, each of which has 512 B. First, if we compare our proposed TCP CWA–CD mechanism with the original TCP, the proposed mechanism effectively decreases the times of cwnd reset. In other words, the frequent reset problem shown in the original cwnd is alleviated, and this result is clearly shown in the time interval ranging from 170 s to 210 s in Fig. 6. In this range, the proposed mechanism reaches the capability of the network pipe after a period of cwnd increases along with the conventional TCP, but later, the cwnd of the normal TCP still aggressively

Fig. 6.

TCP cwnd adaptation of the four mechanisms.

goes up. The proposed mechanism slightly updates the cwnd according to the route contention status, and it maintains the cwnd near a certain value for even more than 30 s. Second, we investigate how TCP contention control works. As analyzed in the previous section, the cwnd value of this mechanism is always very small and extensively fluctuates. This result shows that this mechanism can indeed restrain the cwnd values from excessive increase, but this adaptation mechanism lacks a stable estimation on the contention status. It directly maps the fluctuant round-trip contention information to the adaptation of a new cwnd value, and thus, the adaptation is quickly switched between an increase and a decrease in the cwnd values. Third, in the TCP with maximum window mechanism, an increase in the cwnd value is slow, but the cwnd values frequently vary, because RT TT CP is not the real RTT and could not reflect the actual network state. We can see in Fig. 6 that the cwnd value of the TCP with CWA–CD is more stable. When receiving a new ACK, the node adjusts the cwnd value based on the V CRH value. Although the estimation on the contention is different from reality, the resulting cwnd is just slightly modified. If a segment loss occurs, we determine whether we can minimize the cwnd, depending on the contention situation. If the contention status is severe, it is beneficial for alleviating the large variation of cwnd and increasing the throughput by just halving the congestion window. In the experiment, the throughput is evaluated in terms of the total number of TCP segments received by the destinations in a given time duration of 500 s. Fig. 7 shows the throughput


Fig. 7.

TCP throughput of the four mechanisms in the grid topology.

performance of the four mechanisms in the grid topology. The proposed CWA–CD mechanism gains approximately 15.9%, 25.9%, and 55.2% improvements compared with the TCP mechanism with maximum window, the TCP mechanism with contention control, and the original TCP mechanism, respectively. From the viewpoint of the original TCP mechanism, our proposed mechanism effectively limits the TCP congestion window from overshooting. The TCP mechanism with CWA–CD evaluates the contention from a series of contention RTT values and adjusts the cwnd values based on not only segment loss but the contention situation as well, thus gaining an improvement in throughput. From the viewpoint of the TCP mechanism with contention control, the improvement is still considerable, because the TCP congestion window in this mechanism is very conservative to grow due to the fallacious estimation on the contention status. In other words, the estimation of the contention status through the V CRH in the TCP mechanism with CWA–CD is more accurate and timelier. From the viewpoint of the TCP mechanism with a maximum window, the classification of the contention RTT and congestion RTT is more accurate, and the proposed cwnd adaptation mechanism is more flexible. The results of the experiment illustrate that, in the proposed CWA–CD mechanism, the contention detection is more accurate, and the congestion window is properly adapted. Fig. 8 shows the TCP end-to-end delay of the four mechanisms in the grid topology, and this result is another important performance factor of TCP. The TCP CWA–CD mechanism yields approximately 44.6% reduction compared with the original TCP mechanism, and it shows that the proposed mechanism reduces the end-to-end delay to a large extent and improves the network performance. As shown in Fig. 1, whenever the amount of segments exceeds the upper bound of the BDP, link contentions become severe, and segments have difficulty passing through the channel. In this case, it takes a longer time for packets to pass the links, and it may result in a link breakdown. The TCP CWA–CD mechanism attempts to maintain the number of segments at a proper level according to the upper bound of the BDP and contention status. This improvement reduces the number of collisions at links and, subsequently, the transfer delay. The performance levels of the

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Fig. 8. TCP end-to-end delay of the four mechanisms in the grid topology.

TCP with maximum window, the TCP contention control, and the TCP CWA–CD mechanisms are similar in the sense that the mechanisms efficiently alleviate the contention problem. Because of a very small congestion window, the network load in the TCP contention control mechanism is the lowest, and certainly, the end-to-end delay is not high. However, because this mechanism does not utilize network resources well, the throughput performance is not good. Our proposed mechanism achieves higher throughput without sacrificing the end-to-end delay performance, and its improvement is very significant. B. Dynamic Random Topology We consider a conventional random waypoint mobility model in our experiment topology. In this model, a node randomly picks up a location within a simulation area and starts to move toward the destination with a random speed that ranges from zero to maxspeed. Whenever the node reaches the destination, it pauses for 1 s. The parameter maxspeed values can be varied with 5, 7.5, 10, 12.5, 15, 17.5, and 20 m/s in different experiments. We initialize a set of 50 nodes that were randomly distributed in an area of 500 m by 500 m. There are 50 TCP connections between randomly selected sources and destinations. In a definite value of speed, we randomly set up ten different network scenarios as experiment samples and obtain the end-to-end delay and throughput data after taking the expectation of ten sample values, respectively. In total, there are 60 different network scenarios for varying node speeds. Table II lists the simulation parameters. Fig. 9 shows the performance of the TCP end-to-end delay of the four mechanisms in the random dynamic topology. The proposed TCP CWA–CD mechanism yields approximately 68.3%, 70.1%, and 90.4% reductions, compared with the TCP with maximum window, the TCP contention control, and the original TCP mechanisms, respectively. This result also shows more improvement than the case in the previous static scenario, and thus, it illustrates that the alleviation of congestion window overshooting still effectively works in the dynamic scenario. However, a mobility factor also plays an important role, except for the contention factor in the dynamic environment, and our

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TABLE II EXPERIMENT PARAMETERS IN THE RANDOM DYNAMIC TOPOLOGY

Fig. 10. TCP throughput of the four mechanisms in the random dynamic topology.

precise than the CD (contention delay) in the TCP contention control. The CWA–CD mechanism adapts the cwnd value based on not only RTO and ACK but on the V CRH as well. It is timelier and more accurate than TCP mechanism with maximum window, and it is effective in limiting the congestion window size from overshooting. On the other hand, in the dynamic scenario, because node mobility is another important factor in contrast with contentions, controlling the congestion window cannot totally fix packet losses. VI. C ONCLUSION Fig. 9. TCP end-to-end delay of the four mechanisms in the random dynamic topology.

new method focuses on contentions and does not consider handling the link breakage from mobility. The improvement is more remarkable, because during link breakdown from mobility, fewer packets are dropped as the congestion window becomes smaller. Thus, shorter end-to-end delays are achieved on the average. Fig. 10 illustrates the throughput performance of the four mechanisms in the random dynamic topology. The proposed TCP mechanism with CWA–CD gains approximately 6.8% and 13.9% improvements compared with the TCP with maximum window and the TCP contention control mechanisms, respectively, whereas it shows similar performance to the original TCP mechanism. In dynamic scenarios, link breakdowns may frequently occur because of link mobility, and the shrinking of the congestion window is useless in this case. Based on the results of the experiment, we can observe that the proposed mechanism attempts to fix the adverse effect of link contentions in multihop ad hoc networks. Monitoring the link contention status, we can effectively alleviate the TCP congestion window from overshooting and keep it in an effective range. The results in the previous static grid topology prove the effectiveness of the proposed CWA–CD mechanism. We split the real RTT into two parts, i.e., 1) the congestion RTT and 2) the contention RTT, and we define a variable V CRH to evaluate the degree of link contentions. This approach is more

When the conventional TCP congestion-control mechanism was utilized on top of the MAC 802.11 protocol in multihop ad hoc networks, the update of cwnd is so aggressive that it soon exceeds an appropriate value according to the real BDP. It may result in a severe contention, segment losses, and a restart of the congestion window. In this situation, TCP connections cannot stably work and yield very low throughput, which has been a major factor for reducing the network performance. Previous studies have given some modified TCP mechanisms. However, there is still space to improve the TCP performance. In our proposed CWA–CD mechanism, we have split the real RTT into two parts—the congestion RTT and the contention RTT—and revealed that the contention RTT has nothing to do with the BDP and that the BDP is determined by only the congestion RTT. We obtained the contention RTT information from forward data and backward ACK at the MAC layer and estimated the contention status through the deviation of the contention RTT. Then, we made a modification of the window adaptation mechanism, in which the cwnd value was changed according to several factors such as the V CRH and timeout. The deviation of the contention RTT reflects the direct indication of the contention situation, and this mechanism is timelier and more precise. Furthermore, the relevant congestion window adaptation mechanism is simple and steady, and it does not blindly reset the cwnd but adjust the cwnd value based on the contention status. The experiment shows that the proposed mechanism is more precise and much stable, and it significantly improves the throughput in static scenarios. We have considered


an overshooting problem of TCP within the multihop network in this paper. In addition, this mechanism can be used in the connection of the ad hoc network with the normal Internet, on the condition that any node with contention in the connection uses our mechanism to contribute the measurement of the V CR and the receiver feedbacks the recorded V CRH. We have used a segment-driven method to sample and calculate the V CRH, which is easy to implement. However, a small problem occurs when the amount of segments is small. In this case, the time span between segments is large, and thus, some segments as part of the V CRH calculation may be outmoded to some extent. This problem degrades the accuracy in detecting the contention. We can choose another timestampdriven method to alleviate this problem. In other words, every time a new segment arrives, the timestamp of the old segments is checked to determine whether we can remove some old segments before calculating the V CRH. However, the latter method is more complicated. We can combine the packet- and timestamp-driven methods to improve the stability of cwnd updating for further work. In addition, we will investigate the adaptation of CWA–CD in other well-known TCP versions. Our proposed mechanism focuses on link contentions and does not consider the mobility factor. Link failures due to mobility are part of the main sources of link unreliability in mobile ad hoc networks (MANETs), which we have previously investigated. In our future work, we will give a comprehensive consideration of these factors to improve the performance of the network. R EFERENCES [1] G. Holland and N. Vaidya, “Analysis of TCP performance over mobile ad hoc networks,” ACM Wireless Netw., vol. 8, no. 2, pp. 275–288, Mar. 2002. [2] Z. Fu, X. Meng, and S. Lu, “How bad TCP can perform in mobile ad hoc networks,” in Proc. IEEE ISCC, 2002, pp. 298–303. [3] W. B. Zhu, X. M. Zhang, and N. N. Li, “Improve TCP performance with link-aware warning method in mobile ad hoc networks,” in Proc. IEEE WICOM, 2008, pp. 1–4. [4] J. Li, C. Blake, D. D. Couto, H. Lee, and R. Morris, “Capacity of ad hoc wireless networks,” in Proc. ACM MobiCom, Jul. 2001, pp. 61–69. [5] K. Chen, Y. Xue, S. H. Shah, and K. Nahrstedt, “Understanding bandwidth-delay product in mobile ad hoc networks,” Comput. Commun., vol. 27, no. 10, pp. 923–934, Jun. 2004. [6] V. Jacobson, “Congestion avoidance and control,” Comput. Commun. Rev., vol. 18, no. 4, pp. 314–329, Aug. 1988. [7] Z. Fu, H. Luo, P. Zerfos, S. Lu, L. Zhang, and M. Gerla, “The impact of multihop wireless channel on TCP throughput and loss,” in Proc. IEEE INFOCOM, 2003, pp. 1744–1753. [8] C. Y. Luo, N. Komuro, K. Takahashi, and T. Tsuboi, “PACED TCP: A dynamic bandwidth probe TCP with pacing in ad hoc networks,” in Proc. IEEE Pers., Indoor, Mobile Radio Commun., 2007, pp. 1–5. [9] S. M. Elrakabawy, A. Klemm, and C. Lindemann, “TCP with adaptive pacing for multihop wireless networks,” in Proc. 6th ACM Int. Symp. Mobile Ad Hoc Netw. Comput., 2005, pp. 288–299. [10] M. Shen and D. M. Zhao, “Opportunistic link scheduling for multihop wireless networks,” IEEE Trans. Wireless Commun., vol. 8, no. 1, pp. 234–244, Jan. 2009. [11] Z. Ye, S. V. Krishnamurthy, and S. K. Tripathi, “Use of congestionaware routing to spatially separate TCP connections in wireless ad hoc networks,” in Proc. 1st IEEE Int. Conf. Mobile Ad Hoc Sensor Syst., 2004, pp. 389–397. [12] H. Zhai, X. Chen, and Y. Fang, “Alleviating intraflow and interflow contentions for reliable service in mobile ad hoc networks,” in Proc. IEEE Mil. Commun. Conf., 2004, pp. 1640–1646. [13] S. Rangwala, A. Jindal, K. Y. Jang, K. Psounis, and R. Govindan, “Understanding congestion control in multihop wireless mesh networks,” in Proc. 14th ACM Int. Conf. Mobile Comput. Netw., 2008, pp. 291–302.

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[14] D. Triantafyllidou, K. Al Agha, and V. A. Siris, “Adaptive setting of TCP’s maximum window in ad hoc multihop networks with a single flow,” in Proc. IEEE WCNC, 2009, pp. 1–6. [15] E. Hamadani and V. Rakocevic, “TCP contention control: A cross-layer approach to improve TCP performance in multihop ad hoc networks,” in Proc. 5th Int. Conf. Wired/Wireless Internet Commun., 2007, pp. 1–16. [16] X. M. Zhang, N. N. Li, W. B. Zhu, and D. K. Sung, “TCP transmission rate control mechanism based on channel utilization and contention ratio in ad hoc networks,” IEEE Commun. Lett., vol. 13, no. 4, pp. 280–282, Apr. 2009. [17] K. Nahm, A. Helmy, and C. J. Kuo, “Cross-layer interaction of TCP and ad hoc routing protocols in multihop IEEE 802.11 networks,” IEEE Trans. Mobile Comput., vol. 7, no. 4, pp. 458–469, Apr. 2008. [18] S. Papanastasiou and M. Ould-Khaoua, “TCP congestion window evolution and spatial reuse in MANETs,” Wireless Commun. Mobile Comput., vol. 4, no. 6, pp. 669–682, Sep. 2004. [19] K. Nahm, A. Helmy, and C. J. Kuo, “TCP over multihop 802.11 networks: Issues and performance enhancement,” in Proc. ACM Mobihoc, 2005, pp. 277–287. [20] E. Altman and T. Jimenez, “Novel delayed ACK techniques for improving TCP performance in multihop wireless networks,” in Proc. Pers. Wireless Commun., 2003, pp. 237–253. [21] NS-2 With Wireless and Mobility Extensions. [Online]. Available: http://www.monarch.cs.cmu.edu

Xin Ming Zhang (M’08) received the B.E. and M.E. degrees in electrical engineering from China University of Mining and Technology, Xuzhou, China, in 1985 and 1988, respectively, and the Ph.D. degree in computer science and technology from the University of Science and Technology of China, Hefei, China, in 2001. Since 2002, he has been with the faculty of the University of Science and Technology of China, where he is currently an Associate Professor with the School of Computer Science and Technology. He is also with the National Mobile Communications Research Laboratory, Southeast University, Nanjing, China. From September 2005 to August 2006, he was a visiting Professor with the Department of Electrical Engineering and Computer Science, Korea Advanced Institute of Science and Technology, Daejeon, Korea.

Wen Bo Zhu received the B.E. degree in electronic science and technology and the M.E. degree in computer science and technology from the University of Science and Technology of China, Hefei, China, in 2006 and 2009, respectively.

Na Na Li received the B.E. degree in computer science and technology from Jiangsu University, Zhenjiang, China, in 2007 and the M.E. degree in computer science and technology from the University of Science and Technology of China, Hefei, China, in 2010.

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Dan Keun Sung (S’80–M’86–SM’00) received the B.S. degree in electronics engineering from Seoul National University, Seoul, Korea, in 1975 and the M.S. and Ph.D. degrees in electrical and computer engineering from the University of Texas at Austin in 1982 and 1986, respectively. Since1986, he has been with the faculty of the Korea Advanced Institute of Science and Technology (KAIST), Daejon, Korea, where he is currently a Professor with the Department of Electrical Engineering. From 1996 to 1999, he was the Director of the Satellite Technology Research Center, KAIST. He was the Division Editor of the Journal of Communications and Networks. He is the holder of several patents and the 2010 Patent Award from the Korea Intellectual Property Office. His research interests include mobile communication systems and networks, with special interest in resource management, machine to machine communications, smart grid networks, wireless local area networks, wireless personal area networks, high-speed networks, next-generation internet protocol-based networks, traffic control in wireless and wireline networks, signaling networks, intelligent networks, performance and reliability of communication systems, and microsatellites. Dr. Sung is a member of the National Academy of Engineering of Korea. He is the Editor of the IEEE Communications Magazine. He was the recipient of the 1992 National Order of Merits, the Dongbaek Medal, the 1997 Research Achievement Award, the 1997 MoMuc Paper Award, the 2000 Academic Excellence Award, the Best Paper Award at the 2000 Asia-Pacific Conference on Communications, the 2004 This Month’s Scientist Award from the Ministry of Science and Technology and the Korea Science and Engineering Foundation, and the Best Paper Award at the 2005 Next-Generation PC International Conference.