THE Internet has evolved dramatically in the past several

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1 IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS, VOL. 22, NO. 10, DECEMBER Improving Protocol Capacity for UDP/TCP Traffic With Model-Based Frame Scheduling in IEEE Operated WLANs Hwangnam Kim, Student Member, IEEE, and Jennifer C. Hou, Senior Member, IEEE Abstract In this paper, we develop a model-based frame scheduling scheme, called MFS, to enhance the capacity of IEEE operated wireless local area networks (WLANs) for both transmission control protocol (TCP) and user datagram protocol (UDP) traffic. In MFS each node estimates the current network status by keeping track of the number of collisions it encounters between its two consecutive successful frame transmissions, and computes accordingly the current network utilization. The result is then used to determine a scheduling delay to be introduced before a node attempts to transmit its pending frame. MFS does not require any change in IEEE , but instead lays a thin layer between the LL and medium access control (MAC) layers. In order to accurately calculate the current utilization in WLANs, we develop an analytical model that characterizes data transmission activities in IEEE operated WLANs with/without the request to send/clear to send (RTS/CTS) mechanism, and validate the model with ns-2 simulation. All the control overhead incurred in the physical and MAC layers, as well as system parameters specified in IEEE , are figured in. We conduct a comprehensive simulation study to evaluate MFS in perspective of the number of collisions, achievable throughput, intertransmission delay, and fairness in the cases of TCP and UDP traffic. The simulation results indicate that the performance improvement with respect to the protocol capacity in a WLAN of up to 300 nodes is 1) as high as 20% with the RTS/CTS and 70% without the RTS/CTS in the case of UDP traffic and 2) as high as 10% with the RTS/CTS and 40% without the RTS/CTS in the case of TCP traffic. Moreover, the intertransmission delay in MFS is smaller and exhibits less variation than that in IEEE ; the fairness among wireless nodes in MFS is better than, or equal to, that in IEEE Index Terms IEEE , performance analysis, protocol enhancement, wireless local area network (WLAN). I. INTRODUCTION THE Internet has evolved dramatically in the past several years, and in particular, IEEE operated wireless local area networks (WLANs) has been proposed as an extension to the Internet [1], [4], [5], [8], [12], [15]. As a result, the capacity of wireless networks, e.g., the throughput as allowed in a given wireless channel, will start to influence Internet applications. Even though IEEE [12] is compatible with the current best effort service model in wired networks, it cannot achieve theoretical capacity bound [8] and suffers from variant Manuscript received September 1, 2003; revised April 15, This paper was presented in part at ACM MOBICOM 2003, San Diego, CA. The authors are with the Department of Computer Science, University of Illinois at Urbana Champaign, Urbana, IL USA ( hkim27@ cs.uiuc.edu; jhou@cs.uiuc.edu). Digital Object Identifier /JSAC transmission delay, both of which are caused by collisions and subsequent retransmission. This is a result of the fact that IEEE employs a carrier sense multiple access with collision avoidance (CSMA/CA) mechanism, called distributed coordination function (DCF), as the basic access method. Even with the floor acquisition mechanism, called request to send/clear to send (RTS/CTS), DCF cannot completely eliminate collisions [5], [15], [16]. Prior research efforts that focus on making throughput improvement or service differentiation in IEEE DCF achieve their objectives by either modifying the backoff functions or fine tuning certain system parameters (such as interframe spacing or contention window increasing factor) [1], [4], [5], [8], [16], [17]. (We will provide a summary in Section II-B.) Different from the existing work, we propose in this paper a model-based frame scheduling scheme, called MFS, that is positioned between the logical link (LL) and medium access control (MAC) layers, collects information on the network status, and schedules frames according to current network utilization. Specifically, each node makes use of the collision statistics collected from the MAC layer, computes the current network utilization, and estimates an appropriate scheduling delay before which it will not attempt to transmit its pending frame. The objective is to reduce idle spacing due to the backoff mechanism, as well as the number of collisions and to improve the system throughput. In order to determine the current network utilization, we derive an analytic model that fully characterizes the data transmission activities in IEEE operated WLANs. The derived model takes into consideration of protocol details (e.g., the system parameters specified in the IEEE standard and the throughput overhead imposed by the physical and MAC layers), includes both cases in which the RTS/CTS mechanism is and is not employed, and characterizes faithfully the binary backoff window behavior. In addition, the derived model does not rest on any assumption on the input traffic. We also validate the model by comparing the numerical results against simulation results in ns-2. Based on the derived model, each node can compute the current utilization and determine an adequate scheduling delay that avoids potential collisions. We have implemented MFS in ns-2, and conducted a comprehensive simulation study to evaluate its performance in terms of the number of collisions incurred, achieved throughput, variance of intertransmission delay, and fairness. The simulation results indicate that the performance improvement with respect to protocol capacity for user datagram protocol (UDP) traffic /04$ IEEE

2 1988 IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS, VOL. 22, NO. 10, DECEMBER 2004 in a WLAN of up to 300 nodes can be as high as 20% with the RTS/CTS and 70% without the RTS/CTS when the number of retransmissions is limited to seven, and that for transmission control protocol (TCP) traffic can be as high as 10% with the RTS/CTS and 40% without the RTS/CTS. 1 Moreover, the intertransmission delay in MFS is smaller and exhibits less variation than that in IEEE , and at the same time, the fairness among wireless nodes in MFS is better than or at least equal to the fairness achieved in IEEE The rest of the paper is organized as follows. In Section II, we first describe succinctly the operations of IEEE which pertain to this study, and then give a summary of related work in the literature from two perspectives: throughput analysis and performance improvement on the IEEE MAC protocol. In Section III, we provide an overview of our analysis in WLANs, followed by a detailed description of the analytical model. Then, we discuss in Section IV how to derive the attempt rate used in the analytical model, and validate the model with ns-2 simulation in Section V. Following that, we propose in Section VI MFS and evaluate its performance in Section VII with a comprehensive simulation study with respect to the number of collision, throughput, intertransmission delay, and fairness. Finally, we draw conclusions for this paper in Section VIII. II. PRELIMINARIES A. Operations of IEEE IEEE has become the standard MAC and physical layer (PHY) specification WLANs [12]. It provides two access methods: 1) the DCF, also known as the basic access method, is a CSMA/CA protocol and 2) the point coordination function (PCF) is an access method similar to a polling system and uses a point coordinator to arbitrate the access right among nodes. In addition, the standard includes a floor acquisition mechanism, called RTS/CTS, to resolve the hidden terminal problem. As DCF is the basic access method in both wireless infrastructure and infrastructure-less environments, we focus henceforth on the IEEE protocol that implements DCF. DCF operates as follows. Before initiating a transmission, a node senses the channel to determine whether or not another node is transmitting. If the medium is sensed idle for a specified time interval, called the distributed interframe space (DIFS), the node is allowed to transmit. If the medium is sensed busy, the transmission is deferred until the ongoing transmission terminates. A slotted binary exponential backoff technique is used to arbitrate the access: a random backoff interval is uniformly chosen in and used to initialize the backoff timer, where is the maximum contention window. The backoff timer is decreased as long as the channel is sensed idle, stopped when a transmission is in progress, and reactivated when the channel is sensed idle again for more than DIFS. The time immediately following an idle DIFS is slotted, with each slot equal to the time needed for any node to detect the transmission of a 1 In [14], we have also observed that the performance improvement, especially for cases without the RTS/CTS, varies with the number of retransmissions. The improvement becomes more pronounced when the number of retransmissions is five. packet from any other node. When the backoff timer expires, the node attempts for transmission at the beginning of the next slot time. Finally, if the data frame is successfully received, the receiver initiates the transmission of an acknowledgment frame after a specified interval, called the short interframe space (SIFS), that is less than DIFS. 2 If an acknowledgment is not received, the data frame is presumed to be lost, and after extended interframe space (EIFS), a retransmission is scheduled. The value of is set to in the first transmission attempt, and is doubled at each retransmission up to a predetermined value. According to the standard, a maximum number of retransmissions ( 7 as default) are allowed before the frame is dropped. B. Related Work We categorize existing work into those that derive analytic models to characterize the transmission activities in IEEE and those that aim to improve system throughput and/or provide service differentiation. Analytic models for IEEE : Several analytical models for IEEE MAC DCF protocol have been proposed [5], [8], [9], [11], [18]. Bianchi [5] models the binary backoff counter behavior of a tagged station as a discrete Markov chain model. In particular, it determines the transmission probability and analyzes the saturation throughput based on a constant and independent collision probability. Bianchi validates the model via simulation only in the case of saturated throughput. Bianchi s work captures all the protocol details, and motivates a significant amount of subsequent analysis work. However, it does not give any specific algorithm to determine the value of. Neither does it consider in its discrete Markov model the effect of the deferred time of the backoff counter that occurs when the transmission medium is busy due to other data activities. In other words, the probability that the binary counter remains at the current value is not specifically derived. Calí et al. [8] derive a theoretical throughput bound by approximating IEEE with a -persistent version of IEEE They show that with the current parameter settings of IEEE , it can hardly achieve the theoretical capacity bound. As such, they suggest to incorporate a parameter tuning method in IEEE so as to achieve the capacity bound. However, they only deal with IEEE DCF without the RTS/CTS mechanism, and assume that all the stations always have packets ready for transmission (which is termed as the asymptotic condition in [8]). Foh and Zukerman [9] analyze, by leveraging the throughput analysis by Bianchi [5], the saturation throughput with a Markov chain with a single server. They assume that the number of active stations increases according to a Poisson process and decreases according to the state dependent service process. Wu et al. [18] also exploit the analysis by Bianchi to modify IEEE DCF for reliable transport protocol over IEEE WLANs. Ho and Ken [11] analyze the throughput under the assumption that traffic sources are Poisson processes. Their analysis on the retransmission activities after collision is perhaps oversimplified. 2 The necessity of returning an acknowledgment is due to the inability of WLANs to listen while transmitting, since usually only one antenna is available for both transmitting and receiving.

3 KIM AND HOU: IMPROVING PROTOCOL CAPACITY FOR UDP/TCP TRAFFIC 1989 Fig. 1. Timing structure of a MAC fluid in IEEE (a) DCF in conjunction with the RTS/CTS mechanism. (b) DCF. All of the throughput analysis models reported above neglect the EIFS parameter that should be used after abnormal procedures such as collisions or frame errors. Also, as individually pointed out above, some of the models do not take into account of the throughput overhead imposed by the physical and MAC layers, while others make assumptions on the input traffic. Work that aims to improve system throughput or support differentiated services: Several research efforts have been made to improve the throughput and/or to support differentiated services by either modifying the backoff mechanism or fine tuning the various interframe spacing times [1], [6], [7], [15] [17]. Weinmiller et al. [17] propose a slot selection mechanism, in which each competing station with pending frames chooses a slot time from with the same probability (in order to reduce access delay), where is an upper bound and is the number of slots elapsed until a winning station in previous cycle started transmitting. On the other hand, a station that newly enters the WLAN chooses probabilistically a slot time from. Weinmiller et al. [16] show via simulation that it is feasible to tune IEEE to provide time bounded delivery in spite of existence of many high-priority sources. Bharghavan [4] proposes two MAC schemes, called dual channel collision avoidance (DCCA) and fair collision resolution algorithm (FRCA), respectively. The former employs two channels for signaling and data in order to efficiently avoid collisions in all the cases of hidden/exposed receivers and senders. The latter seeks to fairly resolve collisions by considering spacial locality of stations and backoff advertisement, so as to provide better channel utilization and delay properties than IEEE In conjunction with their analytic model work [8], Calí et al. [7] propose a method that estimates the number of active stations via the number of empty slots and exploits the estimated value to tune the contention window value based on their analytical model. Aad et al. [1] suggest a scaled binary backoff mechanism. Instead of multiplying the contention window by two at each retransmission, they propose to scale the contention window by the priority factor of each node. Additionally, they also propose that each priority level be given a different value of DIFS or different maximum frame length. Similarly, Veres et al. [15] develop a delay model with the channel utilization as the input, and propose to tune the contention window size, such as its initial and maximum values, for service differentiation. In order to estimate the utilization, they propose two methods, one of which emulates MAC (virtual MAC) and the other emulates applications (virtual source). As mentioned in Section I, all the work directly modulate parameters specified in the IEEE DCF standard to improve protocol capacity or provide service differentiation. In contrast, MFS achieves the objective of improving the protocol capacity, by introducing a thin layer on top of IEEE that monitors the network status and calculates a scheduling delay for each pending frame. It does not require any change in, and is backward compatible with, IEEE III. DERIVATION OF ANALYTICAL FLUID MODELS In this section, we develop an analytic model to analyze the characteristics of an IEEE operated WLAN. The analytical model will be used in Section VI to devise a model-based frame scheduling scheme. A. An Overview of Analysis We define two important analytical components: the fluid chunk and the MAC fluid. Afluid chunk is a sequence of collision periods followed by a successfully transmission frame, where a collision period is composed of idle slots (due to binary exponential backoff) and a collided frame or a RTS, depending on whether or not the floor acquisition mechanism is used. Fig. 1 shows how IEEE DCF operates with [Fig. 1(a)] and without [Fig. 1(b)] the RTS/CTS mechanism, and the corresponding timing structure of a fluid chunk. A MAC fluid consists of a sequence of consecutive fluid chunks. Let represent the probability with which a node sends a frame (note that this probability depends on the backoff timer of the node), and the number of active nodes. The condition under which a frame can be successfully transmitted is that only

4 1990 IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS, VOL. 22, NO. 10, DECEMBER 2004 Fig. 2. Frame service time and its components. one node attempts to send its frame. Hence, the probability of successful transmission in the WLAN, can be expressed as and the probability that there is no transmission activities (idle periods) is If we assume that is large enough, then by using the approximation, the time till the next transmission attempt can be approximated as a random variable with the exponential distribution. As the transmission probability of a backlogged node is determined by the backoff timer, we approximate the time till a transmission attempt with a random variable with the exponential distribution whose rate depends on the current set of backoff windows. Specifically, the attempt rate at a given time is given as where is the current number of active nodes and is the current backoff window size of node. is randomly chosen from the uniform distribution, where is the current maximum contention window of node. Alternatively, we can compute the average backoff window size as and express the average attempt rate as As will be seen, the analytic components, the fluid chunk and the MAC fluid, are expressed by functions of the parameter, (1) (2) which in turn is a function of the number of active nodes in (2). (The details on how to derive the attempt rate will be given in Section IV.) Therefore, the proposed model-based frame scheduling operates in the way that it estimates the current number of active nodes to determine the current available utilization, and then it schedules the current pending frame according to the current utilization. B. Derivation of the Frame Service Time As described in Section III-A, a MAC fluid is composed of a sequence of consecutive fluid chunks, each of which in turns consists of zero or more collision periods followed by a successful frame transmission. We define the length of a fluid chunk, i.e., the time it takes to successfully transmit a frame, as the frame service time. The frame service time plays an important role for the overall analysis, and is depicted in Fig. 2. To facilitate analysis of,wedefine below several random variables (r.v.) and express their relation in both the cases in which the RTS/CTS mechanism is and is not employed. : the r.v. representing the total length of collision periods in a fluid chunk; : the r.v. representing the number of collisions in a fluid chunk; : the r.v. representing the total number of idle periods in a frame service time or a fluid chunk; note that ; : the r.v. representing the th collision period; : the r.v. representing the number of idle slots before the th collision or the successful transmission; : the r.v. representing the size of a collided frame; : the r.v. representing the time it takes to successfully transmit a frame; : the r.v. representing the size of a frame (note that the distribution of is the same as that of );

5 KIM AND HOU: IMPROVING PROTOCOL CAPACITY FOR UDP/TCP TRAFFIC 1991 TABLE I IEEE SYSTEM PARAMETERS in the case that the RTS/CTS mechanism is not used, and (7) Note that the last equality of (7) results from the fact that,, are mutually independent of one another. Since the transform of is, (7) can be rewritten as DIFS, SIFS, EIFS, and ACK: the system parameters whose values are given in Table I; : another system parameter defined as bits Mb/s. In the case that DCF employs the RTS/CTS mechanism, we have Now, what is left is to derive. By (3), we have in the case that the RTS/CTS mechanism is used, or and (3) where and are obtained from system parameters specified in Table I as bits Mb/s, and bits Mb/s. In the case that the RTS/CTS mechanism is not employed, all the above equations remain valid except (3), (4) which should be modified as follows: and Note that we implicitly include PHY overhead (preamble and header) and MAC header in the equations according to Table I. Under both cases, we have 1) and are independent of each other; 2),, are independent of each other; and 3) and are independent of each other. Let,,,,, and denote, respectively, the Laplace transform of the probability density function associated with,,,,, and. Then, we have (4) in the case that the RTS/CTS mechanism is not used. Since,wehave in the case that the RTS/CTS mechanism is used, or in the case that the RTS/CTS mechanism is not used, where and are, respectively, the expectation of and. Note that the distribution of is the same as that of and is given. To derive the distribution of, we note that whether or not each node attempts to transmit in a time slot is determined by its current backoff window size. Each slot is either idle or used, but the number of consecutive idle slots is bounded by the maximum contention window size, (Table I) within each frame service time. In other words, the number of idle slots before each collision or a successful transmission in a fluid chunk cannot exceed. We will derive based on this observation. Given that the number of slots till a transmission attempt is approximated as a random variable with exponential distribution [whose rate is determined by (2)], the probability that there is no transmission attempt in slots is. Given that the maximum contention window size of, we can derive the expected number of idle slots before each collision or successful transmission as (8) (9) (5) in the case that the RTS/CTS mechanism is used, or (6)

6 1992 IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS, VOL. 22, NO. 10, DECEMBER 2004 Fig. 3. MAC fluid structure. C. Derivation of the Length of a MAC Fluid Recall that a fluid chunk is made up of zero or more collision periods followed by a successful frame transmission, and a sequence of consecutive fluid chunks constitute a MAC fluid. Fig. 3 gives the structure of a MAC fluid. 1) Total Number of Idle Slots in a Fluid Chunk: We first derive the total number of idle slots in a frame service time. Since the number of idle slots before the th collision or the successful frame transmission is independently and identically distributed with each other, the Laplace transform of the probability density function associated with can be expressed as, has the same distribution of. Moreover, conditioned on,, and, we have. Hence Under the observation that the number of transmission attempts is Poisson distributed [see (2) and related explanations], we have Additionally, since the transform of is,wehave Unconditioning on,we have The expected value of can be obtained as follows: Finally, unconditioning on, we have 2) Length of a MAC Fluid: Let denote the random variable that represents the length of a MAC fluid,, the random variable of the th frame service time,, the total number of idle slots in,, and the total number of transmission attempts in. To derive, wefirst consider. The condition that totally attempts for transmission in implies that there will be at least fluid chunks by the end of this MAC fluid. During the execution of a subsequent fluid chunk, new attempts may be made, thus, spawning off more fluid chunks. Let the frame service time in which the th packet is successfully transmitted be denoted as, and the number of transmission attempts in be denoted as. The fact that transmissions are attempted implies another fluid chunks are generated. Let the sum of and the frame service times that are spawned off as a result of transmission attempts in be denoted as. It can be shown that Recall that and, hence As,wehave (10) where (the second equality results from and ),,

7 KIM AND HOU: IMPROVING PROTOCOL CAPACITY FOR UDP/TCP TRAFFIC 1993 and. Finally, we have Rearranging (11), we have (11) (12) The terms needed in (12), i.e., the expected frame service time, the expected total number of idle slots in a frame service time, and the expected time to successfully transmit a packet, can be obtained as follows: where is given in (8) or (9) in the case that the RTS/CTS mechanism is employed, or IV. DERIVATION OF THE ATTEMPT RATE To calculate numerical results from the model derived in Section III, we need to know the value of the attempt rate.in this section, we explain how we determine the attempt rate,. Recall that in (2), we express, where is the number of nodes and is the average backoff window size. To determine, we take an iterative approach to determine based on. Succinctly, in each iteration we calculate, based on the average backoff window size calculated from the previous iteration, the probability of collision. This probability is then used to calculate (along with ) the new average backoff window size to be used in the next iteration. In what follows, we first derive the relationship between and. Then, we describe in detail how the iterative algorithm operates. A. Relationship Between,, and Let be the contention window after the th collision occurs, the probability that the current contention window size is, and the index for the maximum contention window size. Then, given the probability,, of collision, we have in the case that the RTS/CTS mechanism is not used, and Since,wehave where (13) With all the expressions properly plugged in, the expected length of a MAC fluid can be expressed as (14) or Let be the average backoff window when the contention window is. Then,. In addition, we have for. Thus, given the probability of collision,, the average backoff window size,, can be expressed as D. Length of an Idle Period An idle period separates consecutive MAC fluids. Since each MAC fluid is triggered by one or more transmission attempts and the time till a transmission attempt is exponentially distributed with rate (2), we estimate an idle time between two consecutive MAC fluid as follows: (15) Note that DIFS is needed in (15) since when a node senses the medium to be idle, it has to wait for DIFS time units before it can attempt to send its frame. E. Throughput Let denote the number of frame service times in a MAC fluid. Then, the expected throughput can be expressed as (17) At the point, we have derived the expression of as a function of. Conversely, given the value of (and, hence, the aggregate attempt rate ), the probability of collision can be determined to be (18) where can be approximated as (16) B. The Iterative Algorithm The iterative algorithm constructs the sequence as follows. The initial backoff window size is set to, where the average contention window

8 1994 IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS, VOL. 22, NO. 10, DECEMBER 2004 Fig. 4. Comparison between analytical and simulation results under IEEE with and without the RTS/CTS when the number of retransmissions is seven. (a) IEEE with the RTS/CTS. (b) IEEE without the RTS/CTS. size is determined by leveraging Goodman s work [10]. Specifically, Goodman et al. proved that the expected number of collisions in a binary backoff algorithm grows asymptotically with (Lemma 3 and Theorem 4 in [10]). Thus, the average contention window size is bounded by (19) where is the initial window size (whose default value is 32 in IEEE ) and is some arbitrary constant. 3 Given the value of calculated above, the attempt rate and the probability of collision, can be calculated using (2) and (18), respectively. Then, the average backoff window size for the next iteration can be calculated as the arithmetic mean of and the result calculated using (17). The rationale behind using the arithmetic mean is as follows; the input is the worst case backoff window size as the bound in (19) is used as the initial contention window size. On the other hand, the result is the best case backoff window size as the worst case backoff window size renders the smallest value of and. Hence, we use the arithmetic mean of both values. The iteration repeats until the difference between the average backoff window sizes in two consecutive iterations satisfies, for some predetermined value of. We prove in Theorem 1 that the iteration algorithm converges. Theorem 1: The iterative algorithm converges. Proof: See [14]. To use the equations derived in Section IV-A in the iterative algorithm, one modification has to be made. The rationale is as follows. All the nodes cannot send their frames in every time slot due to the binary backoff algorithm. Hence, in the case that the number of retransmissions is smaller than, or equal to the index for the maximum contention window size, we modulate 3 In our simulation study, we found that the value of K does not affect the performance of the iterative algorithm considerably. the number of nodes to transmit frame in a slot time as,as is the probability that at least one node attempts to transmit in that slot. In the case that is larger than, the more number of nodes would involve the collisions as the number of nodes in a WLAN increases, and come to use larger contention window sizes (by the factor of ). As a result, the number of nodes that intend to transmit frames in a time slot would be smaller, the collision probability and the attempt rate smaller, and the probability of successful transmissions larger. This is especially noticeable in the case of larger frame sizes without the RTS/CTS since the slightly increased probability of successful transmission affects throughput by a factor of the frame size used. (This comes in part from the fact that data frames are directly used for carrier sense; refer to results in Section V). On the other hand, when is less than, even if the number of active nodes is large, nodes cannot continuously use large contention windows due to the limited number of retransmissions, and the modification suffices. Based on the above discussion, we make the following adjustment: The expected number of collisions when the number of nodes is, is given in. As shown in [10], the expected number of collisions is upper bounded by and, hence, the number of nodes that leads to the same number of collisions is lower bounded by 10, where is given in (13). We assume that the minimum number of nodes to send frames in a slot time is 10 and the maximum number of nodes to send frames in a slot time is. Then, we use the average of both the minimum and maximum values as an approximation of the expected number of nodes to transmit frames in a slot. V. MODEL VALIDATION We have validated the analytical model presented in Sections III and IV with simulation. Fig. 4(a) and (b) depicts the throughput versus the number of nodes under IEEE with and without the RTS/CTS mechanism, when the

9 KIM AND HOU: IMPROVING PROTOCOL CAPACITY FOR UDP/TCP TRAFFIC 1995 packet size is 25 bytes (10 time slots), 125 bytes (50 time slots), 250 bytes (100 slot times), and 1000 bytes (400 time slots), respectively, and the number of retransmissions is seven. As shown in Fig. 4, the numerical results calculated by the derived model agree extremely well with the simulation results obtained in ns-2 simulation. VI. MODEL-BASED FRAME SCHEDULING As mentioned in Section I, the achievable throughput in IEEE operated WLANs is greatly affected by collisions (which in turn is a function of the number of nodes in the WLAN) [10]. In this section, we present a model-based frame scheduling scheme (MFS) that deliberately avoids such collisions so as to enhance the protocol capacity. The operations of the proposed scheme are as follows: Each node keeps track of the following parameters between its two consecutive successful transmissions: 1) the number of collisions encounters and 2) the time interval between its two successful transmissions. It then determines the number of currently active nodes by leveraging Goodman s work [10] in the same manner as in Section IV, calculates the network utilization with the throughput model derived in Section III, and computes a scheduling delay by which it will not access the wireless medium. The remaining procedure to access the wireless medium follows the operations defined in the IEEE protocol. Specifically, let denote the successful transmission rate measured in the interval. Then, the delay that a node artificially introduces before attempting for transmission of its pending frame is calculated as (20) where in the case that the RTS/CTS mechanism is used; and in the case that the RTS/CTS mechanism is not used. MFS is positioned between the LL and MAC (IEEE ) layers, and delays this amount of time,, before passing a frame to IEEE for transmission. This does not require any change to, and is backward compatible with, IEEE The parameter in (20) can be on-line measured by each node. The other parameter can be inferred as follows. The relationship between and the network utilization can be expressed as and, hence, can be expressed as (21) The network utilization in (21) can be calculated with (16) in Section III. In order to do so, we need to estimate the number of wireless nodes,. Again, we leverage the result of Goodman et al. [10]: is asymptotically bounded by, where is the number of collisions a node encounters between its two consecutive successful transmissions. That is, we estimate by keeping track of the number of collisions and using the following equation: (22) where is an arbitrary constant. In summary, a node on-line keeps track of the number of collisions it encounter, as well as time interval, between its two consecutive successful frame transmissions, estimates the number of currently active nodes with (22), calculates the current network utilization with (16), and obtains the current transmission rate with (21). The delay by which each node delays its attempt to transmit the current pending frame is then calculated with (20). VII. SIMULATION STUDY As we cannot gain access to the IEEE implementation without the support of vendors (e.g., the Agere ORiNOCO card [2] and the Intersil Prism II card [13]), we cannot implement the proposed MFS/IEEE in real systems. Instead, we conduct a through simulation-based performance study for MFS/IEEE (This simulation-based evaluation approach is also used by [1], [4], and [18].) We have implemented MFS in ns-2, and conducted a performance study to evaluate the throughput enhancement in IEEE operated WLANs. (As MFS is laid on top of IEEE , we use MFS/IEEE to refer to the proposed scheme.) The evaluation is made with respect to the number of collisions, achievable throughput, intertransmission delay, and fairness. We carry out experiments under two different IEEE operational modes: one with the RTS/CTS and the other without. We use CBR on top of UDP and file transfer protocol (FTP) on top of TCP as the traffic sources. The number of retransmissions is set to five and seven. However, due to the page limit, in what follows, we only present results obtained when the number of retransmissions is seven. The results in the case that the number of retransmissions is five exhibit the same trend, except that the performance improvement is even more pronounced [14]. All the simulations are conducted on Linux on a Pentium GHz PC with 1-GB memory and with 2-GB swap memory. The version of ns-2 is ns-2.1b9a, and each simulation run lasts for 80 simulation seconds. A. Modification to ns-2 To focus on the effect of data transmission-related activities on WLAN simulation and to filter out other second-order effects, we deliberately leave out several protocol operations in IEEE , e.g., power saving, beaconing, association and re-association between wireless nodes and access points, and hidden terminal effects. In addition, several modifications have been made in ns-2 [3] to accommodate MFS. First, we introduce a virtual wireless LAN node. 4 All the wireless nodes communicate with each other through this virtual node. Instead of using ad hoc routing protocols (such as DSDV, TORA, AODV, and DSR), this wireless LAN node uses a static routing algorithm, 4 This corresponds to the existing virtual LAN node in ns-2, and is used to construct a LAN among nodes [3].

10 1996 IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS, VOL. 22, NO. 10, DECEMBER 2004 Fig. 5. Network configuration and protocol stack. (a) Protocol stack. (b) Network configuration. Fig. 6. Position of MFS in the protocol stack. and also uses a static ARP table. Consequently, the routing control overheads are not considered in this simulation study. The control overhead is solely due to data transmission-related activities and includes RTS/CTS/ACK packets. Fig. 5 gives the protocol stack and the network configuration, and Fig. 6 shows where the proposed MFS module is positioned in the WLAN protocol stack. As shown in the figure, MFS is laid on top of the IEEE MAC layer, and collects the number of collisions incurred during the last intertransmission interval from the MAC layer in order to compute a scheduling delay. B. Performance Improvement in Terms of Collisions As mentioned in Section I, the achievable throughput is affected by the number of collisions, which causes binary backoff and subsequent retransmission in all the nodes that are involved in collisions. This section demonstrates the throughput improvement made by MFS/IEEE with respect to the number of collisions. Note that the number of collisions presented in this section is larger than the real number of collisions that occur in the WLANs. This is because each collision involves multiple wireless nodes, but the collision information is independently collected at each wireless node and then summed up to obtain the total number of collisions. UDP/CBR traffic: Fig. 7 depicts the number of collisions as the number of wireless nodes increases under IEEE and MFS/IEEE , when the packet size is 125 bytes (50 slot times) and 500 bytes (200 slot times), respectively, and when the RTS/CTS mechanism is employed. The number of collisions under MFS/IEEE is up to four times less than that under IEEE (In the cases with 1000 bytes, the number of collisions under MFS/IEEE is eight times less than that under IEEE [14].) Fig. 8 shows the simulation results under the same configuration as in Fig. 7, except that the RTS/CTS mechanism is not employed. The number of collisions under MFS/IEEE is up to two times less than that under IEEE TCP/FTP traffic: Fig. 9 presents the number of collisions under the configuration in Fig. 7, except that TCP/FTP applications are employed instead of UDP/CBR. The number of collisions under MFS/IEEE is again up to three times less than that under IEEE Fig. 10 shows the number of collisions under the same configuration as in Fig. 8, except that TCP/FTP rather than UDP/CBR is used as the traffic sources. The number of collisions under MFS/IEEE is again up to two times less than that under IEEE C. Performance Improvement in Terms of Throughput UDP/CBR traffic: As collisions delay data transmission activities in WLANs, we expect, based on the observation made in Section VII-B, the performance of MFS/IEEE should also be improved with respect to throughput. Fig. 11 depicts the throughput under as the number of wireless nodes increases under IEEE and MFS/IEEE , when the packet size is 125 bytes (50 slot times) and 500 bytes (200 slot times), respectively, and when the RTS/CTS mechanism is employed. As shown in the figure, the throughput improvement can be as high as 20%. An interesting observation is that when the number of wireless nodes is small (e.g., 5 or 10) and the packet size is large ( 500 bytes), the throughput under MFS/IEEE is slightly (about 1%) less than that under IEEE The reason can be explained by inspecting the data in Table II. Recall that a frame scheduling delay is artificially introduced before a node attempts to transmit its pending frame. When the number of nodes is small and the packet size is large, the intertransmission delay is larger than the interval required to send two consecutive frames due to the small number of

11 KIM AND HOU: IMPROVING PROTOCOL CAPACITY FOR UDP/TCP TRAFFIC 1997 Fig. 7. Number of collisions versus the number of wireless nodes under IEEE and MFS/IEEE with the RTS/CTS. (a) UDP packet size =125bytes (50 slot times). (b) UDP packet size =500bytes (200 slot times). Fig. 8. Number of collisions versus the number of wireless nodes under IEEE and MFS/IEEE without the RTS/CTS. (a) UDP packet size = 125 bytes (50 slot times). (b) UDP packet size = 500 bytes (200 slot times). collisions. To mitigate this anomaly, one could instrument MFS not to introduce an artificial delay when the estimated number of nodes is less than a given threshold. However, as will be shown in Section VII-D, even without the instrumentation, the variance in the intertransmission delay under MFS/IEEE is less than that under IEEE Fig. 12 gives the simulation results under the same configuration as in Fig. 11, except that the RTS/CTS mechanism is not employed. The throughput improvement is more pronounced than that when the RTS/CTS mechanism is employed, and can be as much as 70%. We also observe that the improvement varies with the number of retransmissions in the cases without the RTS/CTS. For example, when the number of retransmissions is five, the throughput improvement is as much as 150% in the same configuration. (Due to the page limit, the results corresponding to the case that the number of retransmissions is five are not shown. The interested reader is referred to [14] for a detailed account.) Note that we do not observe here the anomalous points shown in Fig. 11. This is because as there is no floor acquisition delay (i.e., RTS/CTS handshaking delay) in these cases, some portion of the scheduling delay which pertains to floor acquisition can be saved. TCP/FTP traffic: Fig. 13 presents simulation results under the configuration in Fig. 11, except that TCP/FTP, rather than UDP/CBR, is used as the traffic sources. As shown in the figure, the throughput improvement can be as high as 10%. Similar to what was observed in the UDP/CBR configuration, when the number of wireless nodes is small (e.g., 10) and the default TCP packet size is large (e.g. 1000), the throughput under MFS/IEEE is (approximately 4%) less than that under IEEE Fig. 14 shows simulation results under the same configuration as in Fig. 8, except that TCP/FTP, rather than UDP/CBR, is used. The throughput improvement can be as high as 40%. D. Performance Improvement in Intertransmission Delay The objective of MFS/IEEE is to allow only one node to transmit its frame at a time so that no collision occurs.

12 1998 IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS, VOL. 22, NO. 10, DECEMBER 2004 Fig. 9. Number of collisions versus the number of wireless nodes under IEEE and MFS/IEEE with the RTS/CTS in case that TCP/FTP applications are employed. (a) TCP default packet size =500bytes (200 slot times). (b) TCP default packet size = 1000 bytes (400 slot times). Fig. 10. Number of collisions versus the number of wireless nodes under IEEE and MFS/IEEE without the RTS/CTS in case that TCP/FTP applications are employed. (a) TCP default packet size = 500 bytes (200 slot times). (b) TCP default packet size = 1000 bytes (400 slot times). Fig. 11. The throughput versus the number of wireless nodes under IEEE and MFS/IEEE with the RTS/CTS. (a) UDP packet size =125bytes (50 slot times). (b) UDP packet size = 500 bytes (200 slot times).

13 KIM AND HOU: IMPROVING PROTOCOL CAPACITY FOR UDP/TCP TRAFFIC 1999 Fig. 12. Throughput versus the number of wireless nodes under IEEE and MFS/IEEE without the RTS/CTS. (a) UDP packet size =125bytes (50 slot times). (b) UDP packet size =500bytes (200 slot times). Fig. 13. Throughput versus the number of wireless nodes under IEEE and MFS/IEEE with the RTS/CTS in case that TCP/FTP applications are employed. (a) TCP default packet size = 500 bytes (200 slot times). (b) TCP default packet size = 1000 bytes (400 slot times). TABLE II AVERAGE INTERTRANSMISSION TIME MEASURED BY A TAGGED NODE WHEN THE NUMBER OF NODES IS FIVE However, since all the nodes in a WLAN schedule their transmission in a decentralized manner, collisions are inevitable, and the intertransmission interval varies. In this subsection, we evaluate MFS in terms of the variance of intertransmission intervals. We conduct this evaluation only with the UDP/CBR configuration, because it is difficult to distinguish the intertransmission delay that results from binary backoff and retransmission in the MAC layer from the delay incurred in the TCP layer (if TCP/FTP is used). Also, the simulation results about intertransmission delay partially show that fairness in MFS/IEEE is better than one in IEEE802.11, which is dealt with in Section VII-E. Figs depict the intertransmission delay trajectories of each tagged node under IEEE and MFS/IEEE , in both cases with the RTS/CTS and without. Fig. 15 presents the trajectories of intertransmission delays experienced in the tagged node, whose identifier is 0, in the case that the number of nodes is 10, the packet size is 125 bytes, and the RTS/CTS is used. We omit the intertransmission delays observed in the other nodes due to the page limit, but we have the same results from those nodes [14]. Fig. 16 shows another set of such the trajectories in the same configuration except that the RTS/CTS is not used. Node identifiers in both figures are numbered in the order that wireless nodes are created within the simulator. We can see that intertransmission delays in MFS/IEEE are less variant than those in IEEE , which means that each node in MFS/IEEE fairly access the wireless media to transmit its frames. The exact numerical

14 2000 IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS, VOL. 22, NO. 10, DECEMBER 2004 Fig. 14. Throughput versus the number of wireless nodes under IEEE and MFS/IEEE without the RTS/CTS in case that TCP/FTP applications are employed. (a) TCP default packet size =500bytes (200 slot times). (b) TCP default packet size = 1000 bytes (400 slot times). Fig. 15. Intertransmission delays in each tagged node under IEEE and MFS/IEEE (both with the RTS/CTS). The number of nodes is ten and the packet size is 125 bytes (50 slot times). (a) Node 0 in IEEE (b) Node 0 in MFS/IEEE results about average and variance in intertransmission delays appear in Section VII-E. Fig. 17 presents a set of the intertransmission delays measured in the tagged node, whose identifier is 40, when the number of nodes are 50, the packet size is 500 bytes, and the RTS/CTS is used. Fig. 18 presents another set of those delays in the same configuration except that the RTS/CTS is not used employed. In both cases, the same observation as made in the previous set of simulations is obtained. We made the same observation in the other nodes. Readers interested in another set of simulation results with respect to intertransmission delays are referred to [14]. E. Fairness MFS/IEEE improves the aggregate throughput of a WLAN by introducing an artificial delay according to the current utilization in order to avoid potential collisions. However, it is not clear if such an improvement impairs fairness. In this section, we investigate whether or not some nodes are favored than others as a result of the artificial delay introduced. Again, we measure the intertransmission delay at each wireless node. As discussed in the previous section, the intertransmission delays in MFS/IEEE are less variant than those in IEEE This implies no node in MFS/IEEE waits prohibitively longer (due to interference of other nodes) than the other nodes, and consequently each node in MFS/IEEE has an equal chance to transmit its frames than in IEEE Fig. 19 presents the average and the variance of intertransmission delays measured at each wireless node during a 80-s simulation run, when the number of nodes is 100, the packet size is 500 bytes, and the RTS/CTS mechanism is used. Both the average and the variance of intertransmission delays are less variant among nodes under MFS/IEEE than those under IEEE Fig. 20 shows the average and the variance of intertransmission delays at each wireless node in the same configuration except that the RTS/CTS is not employed. The same observation can be made.

15 KIM AND HOU: IMPROVING PROTOCOL CAPACITY FOR UDP/TCP TRAFFIC 2001 Fig. 16. Intertransmission delay under IEEE and MFS/IEEE (both without the RTS/CTS). The number of nodes is ten and the packet size is 125 bytes (50 slot times). (a) Node 0 in IEEE (b) Node 0 in MFS/IEEE Fig. 17. Intertransmission delay under IEEE and MFS/IEEE (both with the RTS/CTS). The number of nodes is 50 and the packet size is 500 bytes (200 slot times). (a) Node 40 in IEEE (b) Node 40 in MFS IEEE Fig. 18. Intertransmission delay under IEEE and MFS/IEEE (both without the RTS/CTS). The number of nodes is 50 and the packet size is 500 bytes (200 slot times). (a) Node 40 in IEEE (b) Node 40 in MFS IEEE

16 2002 IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS, VOL. 22, NO. 10, DECEMBER 2004 Fig. 19. Average and variance of intertransmission delays at each wireless node under IEEE and MFS/IEEE (both with the RTS/CTS). The number of nodes is 100 and the packet size is 500 bytes (200 slot times). (a) Average intertransmission delay. (b) Variance in intertransmission delays. Fig. 20. Average and variance of intertransmission delays at each wireless node under IEEE and MFS/IEEE (both without the RTS/CTS). The number of nodes is 100 and the packet size is 500 bytes (200 slot times). (a) Average intertransmission delay. (b) Variance in intertransmission delays. VIII. CONCLUSION In this paper, we have derived, for IEEE operated WLANs, an analytic model that characterizes data transmission activities to obtain the system throughput. The model takes into account of protocol details, such as the system parameters presented in the IEEE standard and the throughput overhead incurred in the physical and MAC layers. Also, it does not make any assumption on the input traffic and accommodates both the cases in which the RTS/CTS mechanism is and is not employed. We have also validated the model by comparing numerical results calculated from the model against simulation results obtained in ns-2. Based on the analytic model, we propose a model-based frame scheduling scheme, called MFS, to improve the achievable throughput in WLANs. In MFS, each node collects the duration, and the number of collisions it encounters, between its two consecutive successful transmission, and infers the number of currently active nodes. Then, with the use of the derived analytic model, it determines the current network utilization and computes a scheduling delay to be artificially introduced to defer transmission of the current pending frame so as to avoid prospective collisions. We have implemented MFS on top of IEEE in ns-2, and conducted a comprehensive simulation study to evaluate the performance in perspective of the number of collisions, achievable throughput, intertransmission delay, and fairness. The simulation results indicate that under the configuration that UDP/CBR is used as the traffic source and the number of retransmissions is limited to seven in a WLAN of up to 300 nodes, MFS/IEEE achieves, as compared with IEEE , up to 20% of performance improvement in the case that the RTS/CTS is used and up to 70% of improvement in the case that the RTS/CTS is not used. Under the same configuration except that TCP/FTP is used as the traffic source, MFS/IEEE also achieves up to 10% of performance improvement in the case that the RTS/CTS is used and up to 40% of improvement in the case that the RTS/CTS is not used.

17 KIM AND HOU: IMPROVING PROTOCOL CAPACITY FOR UDP/TCP TRAFFIC 2003 In both cases, we observe that the performance improvement varies with the number of retransmissions. Also, the delays incurred between two consecutive frame transmissions under MFS/IEEE is smaller and less variant than those under IEEE , and moreover fairness among wireless nodes is quite well supported. We have identified several avenues for future research. We will lay a MFS framework in which existing work that directly modified the IEEE standard for both capacity enhancement and quality assurance can be applied. This will provide deterministic quality assurance services for delay/jitter sensitive traffic, in addition to enhancing the system capacity. We will also take into account of the hidden/exposed terminal problem, external interference, self interference, and overlapping channels in the derived analytic model so as to extend the proposed work to mobile ad hoc networks. Moreover, we will implement the proposed model-based frame scheduling in an existing IEEE implementation and conduct an empirical study. REFERENCES [1] I. Aad and C. Castelluccia, Differentiation mechanism for IEEE , in Proc. IEEE INFOCOM 2001, Anchorage, AK, Apr. 2001, pp [2] Agere Systems, User s Guide for ORiNOCO PC Card, Sept [3] U. Berkeley. (2002, Apr.) LBL, USC/ISI, and X. PARC. The ns Manual. [Online]. Available: [4] V. Bharghavan, Performance evaluation of algorithms for wireless medium access, in Proc. IEEE Int. Computer Performance and Dependability Symp., 1998, pp [5] G. Bianchi, Performance analysis of the IEEE distributed coordination function, IEEE J. Select. Areas Commun., vol. 18, pp , Mar [6] G. Bianchi, L. Fratta, and M. Oliveri, Performance evaluation and enhancement of the CSMA/CA MAC protocol for wireless LANs, in Proc. 7th Int. Symp. Personal, Indoor, and Mobile Communication (PIMC), Oct. 1996, pp [7] F. Calí, M. Conti, and E. 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Campbel, and M. Barry, Supporting service differentiation in wireless packet networks using distributed control, IEEE J. Select. Areas Commun., vol. 19, pp , Oct [16] J. Weinmiller, M. Schlager, A. Festag, and A. Wolisz, Performance study of access control in wireless LANs IEEE DFWMAC and ETSI RES10 HIPERLAN, Mobile Networks and Applications (Special Issue on Channel Access), vol. 2, no. 1, pp , June [17] J. Weinmiller, H. Woesner, J. P. Evert, and A. Wolisz, Analyzing and tuning the distributed coordination function in the IEEE DFWMAC draft standard, in Proc. Int. Workshop Modeling MASCOT 96, Analysis and Simulation of Computer and Telecommunication Systems, San Jose, CA, Feb. 1996, pp [18] H. Wu, Y. Peng, K. Long, S. Cheng, and J. Ma, Performance of reliable transport protocol over IEEE wireless LAN: analysis and enhancement, in Proc. IEEE INFOCOM, New York, June 2002, pp Hwangnam Kim (S 04) received the B.E. degree in computer engineering from Pusan National University, Pusan, Korea, in 1992 and the M.S. degree in computer engineering from Seoul National University, Seoul, Korea, in He has been working towards the Ph.D. degree in computer science at the University of Illinois at Urbana Champaign since From 2000 to 2001, he was with Bytemobile, Inc., Mountain View, CA. From 1994 to 1999, he was with LG Electronics, Ltd., Seoul, Korea. His research interests are in wireline/wireless network modeling and its applications. Jennifer C. Hou (SM 93) received the Ph.D. degree in electrical engineering and computer science from the University of Michigan, Ann Arbor, in From 1993 to 1996, she was an Assistant Professor of electrical and computer engineering at the University of Wisconsin, Madison, and an Assistant/Associate Professor of Electrical Engineering at Ohio State University from 1996 to Since August 2001, she has been with the Department of Computer Science, University of Illinois at Urbana Champaign, where she is currently an Associate professor. She has published over 100 papers in archived journals and peer-reviewed conferences. Her most recent research focus is in the areas of network modeling and simulation, network measurement and diagnostics, and wireless sensor networks. Dr. Hou was a recipient of the Lumley Research Award from Ohio State University in 2001, the NSF CAREER Award from the National Science Foundation ( ), and the Women in Science Initiative Award from the University of Wisconsin-Madison ( ). She has been on the Technical Program Committee of several major networking, real-time, and distributed systems conferences/symposiums, and was the Technical Program Chair of the IEEE RTAS 2000 and the IEEE IPSN 2004, a Program Vice Chair of the IEEE ICDCS 2002, the IEEE ICPADS 2004, the IEEE RTSS 2004, and the General Co-Chair ofthe IEEE RTAS She is on the Editorial Board of the IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS, IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS, ACM/Kluwer Wireless Networks, Kluwer Computer Networks, and ACM Transactions on Sensor Networks. She is a member of ACM.