Adaptive Service Differentiation for QoS Provisioning in IEEE 802.11 Wireless Ad Hoc Networks A. Ksentini, M. Naimi1
A. Nafaa, M. gueroui
LICP, Université de Cergy-Pontoise 3, Avenue Adolph Chauvin 95302 Cergy-Pontoise +3313134256607
PRiSM, Université de Versailles 45, Avenue des Etats-Unis 78035 Versailles +33139254346
[email protected]
{anaf, mogue}@prism.uvsq.fr
ABSTRACT
The proposed IEEE 802.11e draft standard defines new MAC protocols for QoS support in wireless networks, namely HCF and EDCF. EDCF is a contention based channel access scheme and is part of HCF for infrastructure networks and may be used as a separate coordination function for wireless Ad-hoc networks. In this paper we propose to enhance EDCF with a dynamic traffic class’s management protocol, which allows firstly, a guarantee of QoS to the sensitive applications some as the network state. Secondly, a sliding QoS differentiation between the Traffic Classes (TC) according to the instantaneous channels fluctuations. This sliding differentiation is based on a dynamic tune of the IEEE 802.11 MAC’s parameters. The performances of the proposed scheme namely AMPA (Adaptive MAC Parameters), are extensively investigated by simulations. Results obtained indicate that AMPA scheme outperforms both DCF and EDCF.
Categories and Subject Descriptors C.2.1 [Computer-Communication Networks]: Network architecture and design; C.2.3 [Computer-Communication Networks]: Network Operation; C.2.5 [ComputerCommunication Networks]: Local and Wide-Area Networks.
General Terms Measurement, Performance, Design.
Keywords QoS, wireless LAN, ad hoc network.
1. INTRODUCTION Wireless communications are an emerging technology that became an essential feature of every day’s life. In this context the IEEE 802.11 WLAN standard [1] is being accepted for many different environments. IEEE 802.11 is now considered as a wireless version of Ethernet. This is favored by the development of a new wireless physical layer, 802.11g [2], providing a bandwidth (around 54 Mbps) five times bigger than the classical well known IEEE 802.11b (11Mbps). Hence, the IEEE 802.11 Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. PE-WASUN’04, October 7, 2004, Venezia, Italy. Copyright 2004 ACM 1-58113-959-4/04/0010...$5.00
can support the more demanding applications, while being a serious alternative to wired networks. Meanwhile, multimedia and interactive services are having an equivalent growth. Digital Satellite TV quality, for example, was reported to be achievable at 1.5 Mbps. Usually, the audio/video streaming application imposes firm requirements on communication QoS metrics, such as loss rate, delay and jitter. The great challenge is, consequently, to guarantee these requirements in wireless environments, due to the unpredictable wireless link conditions (noise, fading, and so on). To tackle the QoS problem, the IEEE formed the 802.11e Task group to design and develop a generic framework for supporting QoS provisioning and enforcement. Based on the standardized 802.11 MAC (Medium Access Control), the different IEEE 802.11e [3] proposals focus, mainly, on managing the network access contention between different traffic classes. Among these proposals, EDCF (Enhanced Distributed Coordination Function) introduce priority-based CSMA/CA (Collision Sense Medium Access/Collision Avoidance). EDCF attributes static priorities for each flow at the initiation period. At the same time, a new coordination function, namely Hybrid Coordinator (HC), was recently introduced. Deployed at the Access Point (AP), HC includes a contention-free polling period to provide a guaranteed medium access to exigent flows. HC still have some scalability problems when the number of flows grows. Particularly, there is signaling phase for slot time reservation that (1) is not concordant with real-time streams transmission and (2) introduces an additional data control overhead. Our main concern, in this paper, is to provide generic QoS capable and 802.11-conformant MAC protocol. We define at wireless terminal level the relative priority of each different traffic classes. This is based on traffic requirements, providing transparent continuity for the upper layer QoS mechanisms. For instance, AMPA can easily interact with the well accepted Diffserv (Differentiated Services)[4], Intserv (Integrated services)[5] techniques. We enforce the QoS at MAC level through, firstly, defining flexible/dynamic traffic classes that appropriately share the wireless channel access. This is achieved by assigning appropriate AIFS interval and PFactor for each traffic class; it allows a smooth adaptation and better link exploitation. Secondly, a per-classs adjustable throughput that reacts to wireless network changing conditions. The instantaneous network state is deduced from the packet dropped in the Queuelevel (without using any receiver-based feedback) and from the channel collision rate. Simulation results show that our proposal 1
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outperforms both EDCF and DCF, providing bounded delays, reduced loss rate, and guaranteed throughput. AMPA efficiency is particularly noticeable in overloaded IEEE 802.11 wireless LAN. The remainder of this paper is organized as follow, the section II gives an overview over IEEE 802.11 networks and related researches covering 802.11 MAC enhancements for real-time traffic. In section III, we describe our proposed protocol (AMPA) and its components. The Section IV represents the performance evaluations. Finally; we conclude, in Section V.
2. RELATED WORK 2.1 Legacy IEEE 802.11 MAC Protocols The IEEE 802.11 MAC defines two transmission modes for data packets: the Distributed Coordination Function (DCF) based on CSMA/CA and, the contention-free Point Coordination Function (PCF), where the Access Point controls all transmissions based on a polling mechanism. The DCF and PCF modes are time multiplexed in a “superframe”, which is formed by a PCF contention-free period (CFP) followed by a DCF contention period (CP), positioned at regular intervals. The DCF mode is based on a CSMA/CA mechanism. The access control scheme is shown in Figure 1. A terminal that intends to transmit and senses the channel busy waits for the end of the ongoing transmission, then waits for a time period of DIFS (Distributed coordination Function InterFrame Spaces) length, and then randomly selects a time slot within the backoff window. The backoff length is calculated as follows: Backoff = Random (0, CW) * aSlotTime
(1)
The number of backoff slots is derived from a uniform distribution over the interval [0, CW], where the contention window (CW) parameter ranges from a minimum value of aCWmin up to a maximum value aCWmax. Initially, the CW parameter is set to aCWmin and can be increased up to 255. If no other terminal starts transmitting before the intended slot is reached, the transmission is started. Collisions can only occur in the case where two terminals have selected the same slot.
Figure 1. Backoff mechanism in DCF For each unsuccessful transmission the contention window is exponentially increased as follows:
(
i
)
CW new = CW min × 2 − 1
(2)
If another terminal has selected an earlier slot, the transmission is deferred and its backoff counter is frozen. The terminal waits for the channel to become idle and then waits for the backoff slots remaining from the previous contention.
In order, to guarantee undisturbed transmission even if hidden terminals are present, an RTS/CTS (Request to Send/Clear to Send) mechanism is used. When this mechanism is applied, the contention winner does not transmit the data immediately. Instead it sends an RTS frame to which the receiver answers with a CTS frame. This guarantees that all terminals in the range of either the sender or the receiver know that a packet will be transmitted. In this case, terminals remain silent during the entire transmission. Only the sender is allowed to transmit frames. While the two extra messages present additional overhead, the mechanism is particularly useful in the case of large data frames. The PCF mode is based on a polling mechanism controlled by the AP. During the CFP, the AP polls the terminals registered in its polling list and allows them undisturbed contention-free access to the medium.
2.2 IEEE 802.11 QoS Issues (Quality of service) Best effort service provided by WLAN suits data traffic very well. This has been proved by the success of the mobile Internet access. However, unlike data, multimedia application requires guaranteed high bandwidth and guaranteed maximum end-to-end latency. Multimedia delay and packet loss constraints are not supported by legacy 802.11. Basically, PCF was designed to support real time traffic. However, PCF involves several drawbacks, among which excessive data control overhead and scalability lack. In addition, PCF is explicitly designed for infrastructure wireless communication (WLAN), and therefore can’t be extended for Ad hoc configuration. Many IEEE 802.11 WLAN medium access protocol have been proposed to support Qos requirements of real-time and multimedia applications. Most of the recently works propose to modify the MAC layer defined by the current standard. To introduce priorities and differentiation mechanisms in the IEEE 802.11, the authors in[8]show that three parameters must be considered: (i) Backoff increase function; (ii) the inter frame space; (iii) Maximum frame length. In fact, by assigning different CWmin, DIFS and Maximum frame length, the differentiation between the traffic classes is achieved. However, the authors do not specify any mechanism that tunes the different parameters. Another scheme, named DFS (Distributed Fair Scheduling) [10], utilizes the ideas behind fair queuing in the wireless domain. DFS uses the IEEE 802.11 backoff mechanism to determine which station should send first. As longer the backoff interval as lower the weight of the sending station is. The backof interval range is determined by the frame length. Hence, the QoS provisioning is rather a kind of fairness between competing flows. However, in DFS each wireless terminal has to monitor all transmission packets scrutinizing the “finish tag” of each packet. In addition DFS implies some modifications in the MAC 802.11 header format in order to include the “finish tag”. The TCMA [6][7](Tired Contention Multiple Access) scheme scheme proposes to map eight traffic categories into four Urgency Classes (UC) according to the classes defined in IEEE 802.1d. TCMA introduces priorities between the UC by using different: (i) UC’s backoff time setting; (ii) Urgency Arbitrary Time (UAT). The UAT by definition is used like DIFS in DCF, however, each UCi has its own UATi’s value. Additionally, each station initiates the CWi with a certain value (aCWsize-1) according to UCi
where it belongs. Here the CWsizei’s value is obtained from the beacon frames emitted by the AP. Another important concept introduced by TCMA is the Backoff’s procedure. In fact, unlike DCF, the station decreases the CW for each unsuccessful packet transmission attempt. The decreasing of the CW depends on the CWPFactori (Contention Window Priority Factor) of each station (see equation 3). This parameter is set according to UCi priority. CWnew = [(CW current +1) * (CWPFactor/16)] -1
(3)
Thereby, the CW decreasing is used to reduce the overhead of backoff time. Nevertheless, this mechanism still incurs more packet drops due to the enormous collisions in a heavy network load. The need for better access mechanism supporting service differentiation has led task group E of IEEE 802.11 to propose an extension of the actual IEEE 802.11 standard. The QoS support is realized with the introduction of Traffic Categories (TCs)(Figure 2). Each TC maintains TC specific parameters: Arbitration Interframe Space AIFS[TC], CWmin[TC], PersistenceFactor[TC]. Each station supports multiple backoff instances parameterized with TC specific parameters. The new parameters that have been proposed are: (1) AIFS: At least equal to DIFS and can be enlarged individually for each TC, (2) PF: determines how quickly the contention window is increased when a collision occurs; high priority traffic’s will have a small PF value, while low priority traffic’s have a large PF value (see equation 4), and (3) TXOP: is the maximum duration (i.e. interval of time when the transmission is allowed). New CW[TC]=(old CW[TC] +1) * PF[TC]-1 AC 0
AC 1
AC 2
AIFS[0]
AIFS[1]
AIFS[2]
CW[0]
CW[1]
CW[2]
(4)
AIFS[3] CW[3)
Transmission Attempt
Figure 2. Four access categories (ACs) for EDCF Service differentiation under EDCF is achieved by providing different CWmin for each backoff instance corresponding to certain priority class. Further, different inter-frame space can be used for different priority classes (see Figure 3). As a result, higher priority classes will get more transmission time than lower priority classes. AIFS[i]
AIFS[i]
Busy Medium
Contention Window
SIFS Backoff Window
Next Frame
SlotTime Direct Access
Some works have been done to propose a scheme, which offers an adaptive method to provide a QoS in 802.11. Here, some proposal scheme in this way. ARME (Assured MAC extension) [11] proposes two type of service: the Assured Rate Service and Best Effort. To satisfy the assured Rate Service, ARME suggests to compute dynamically the CW, because the CW determines the probability to win the contention. The smaller the CW is, the higher the probability of getting access to the channel. In this case, an assured Rate Service can therefore be provided by assigning to a station the CW corresponding to the bandwidth requested. For this purpose ARME proposes to adjust the CW until the bandwidth requested by a station is reached. The TCMA scheme seen front, mentions to adjust dynamically the initial value of the CW (CWsize). In fact, the authors propose that the AP updates periodically the CWsize value according to the number of backlogged stations. In AEDCF(Adaptive EDCF) [12], after each successful transmission, the authors propose to reset the CW values more slowly to an adaptive value (different to CWmin) taking into account the current CW size and the average collision rate, while maintaining the priority-based discrimination. Note that, in basic EDCF after each successful transmission, the CW is simply set to the minimum contention window of the corresponding class. Thus the great change proposed in AEDCF is the way to reset the value of the CW after a successful transmission.
AC 3
Virtual Collision Handler
PIFS
Nonetheless, the above described schemes still not propose a dynamic adaptation of their parameter to the network condition changing. They can't provide neither differentiation in heavy load scenario nor permit to serve all traffic classes.
Select Slot and decrement backoff as long as medium stays idle
Figure 3. IEEE 802.11e EDCF channel access
The distributed QoS D-QoS [13] approach proposes the use of different CWs and Contention Offsets (COs) in order to provide relative differentiation between classes. Additionally, the authors propose the possibility of dynamically computing CW/CO values based on the monitored load. However, it does not propose any algorithm for this dynamic computation. Note that all these schemes propose only the dynamic adaptation of the CW parameter, and do not take into account the DIFS (AIFS in IEEE 802.11e) parameter. Although, in [8] it’s clearly seen that backoff priority have a poor performance in noisy environments and the use of DIFS-based differentiation shows best results by providing better wireless channel utilization.
3. THE PROPOSAL SCHEME AMPA Usually, the wireless communication is characterized by low and fluctuating bandwidth link. Moreover, the shared nature of the IEEE 802.11 medium reduces the bandwidth availability in heavy loaded network (i.e. presence of several terminals sharing the wireless channel). From this fact, we design a new protocol (AMPA) that extends the IEEE 802.11 EDCF architecture to provide configurable relative priorities between traffic categories. AMPA provides means for upper-layer mechanisms to specify QoS requirements of each transmitted flow. Our protocol can be considered as an enhancement of the actual well accepted IEEE 802.11e draft. AMPA enforces the QoS differentiation using the combination of two dynamic parameters: AIFS and PFactors. While EDCF assumes a static value of AIFS obtained from QoS
beacon frame (broadcasted at initial stage), AMPA uses a dynamics values. Thus, when network overload occurs, we decrease high priority AIFS. Meanwhile we increase best effort AIFS. However, if the network is in normal condition, we decrease high priority AIFS and increase best effort AIFS. Thus AMPA maintains relative differentiation between the flows some as the network size. In other words, if the network is overloaded, AMPA favours high priority flows, and when the network is in normal condition, AMPA try to serve all traffics. Furthermore, AMPA uses the transported stream relevance and the instantaneous network conditions to compute the AIFS value dynamically. Before detailing AMPA scheme, we assume that all active high priority traffics are beforehand admitted according to available resources. At the same time, best effort TC’s (e.g, web traffics such as HTTP, FTP) may access the medium without any control, which may induce saturating situations.
3.1 AIFS Sliding intervals: High priority stations In order to guarantee QoS, AMPA uses two different procedures to compute AIFS value. The first one is used in case of high priority traffics, and the second one in case of best effort traffics. In case of high priority traffics, we maintain a constant application level perceived QoS for these flows. In this respect we set a predefined QoS metric threshold and TC’s specific AIFS smoothing rules. Each high priority station computes instantaneously the dropped packets rate (α). In fact, the rate of dropped packets gives a pertinent indication about applications perceived QoS. Specifically, it gives the gap between the applications bit rate and the physical layer throughput. The α value is calculated using the number of dropped packets, and the number of packets generated during a constant periods (see equation 5). This period should not be too long in order to get good reactivity and should not be too short in order to reduce the complexity. α = Number dropped packets / Number generated packets (5) Thus, when the loss rates α[i] of a given high priority flow exceeds a certain thresholds PCG[i], the corresponding AIFS is linearly decreased to mitigate the loss rate. On the other hand, when the loss rate does not exceed PCG[i]/2, the AIFS is linearly increased in order to give more medium access opportunities to the best effort flows, and hence achieving better wireless medium utilization.
3.2 AIFS sliding intervals: Best effort In case of best effort, it’s obvious to limit the access of these flows when the network is overloaded. To this aims, the stations belonging to this TC hear the channel and compute the collision rate happening in a certain period (see equation (6)). This experienced collision rate is strongly correlated with the number of active flows. A too high coll[t] means that there are an excessive number of TC flows contending for the medium. Thus, according to this value, the best effort station updates the AIFS value. Coll[t] = [collision duration (number of slots) / control period (number of slots)] * 100 (6)
Usually, it is much suitable to keep certain influence of past history allowing smooth reaction to ephemeral channel fluctuation. This particularly is very prevalent in WLAN environment. For that, each best effort station maintains a set of Coll[t]’s value computed during the five precedent periods. Thus, if the Coll[t] is smaller than the average of (Coll[t-1], Coll[t-2], Coll[t-3], Coll[t-4], Coll[t-5]), therefore the station decreases the AIFS. In other hand, if the Coll[t] is greater than the average of the five precedent collision rate, the stations increase the AIFS.
3.3 Priority Factor distribution As for AIFS, AMPA uses a dynamic PFactor in the Backoff function. The PFactor’s value is updated at the same time as AIFS’s value. On one hand, high priority stations update their PFactor according to the same parameter α[i]. On other hand, best effort stations use the same metric as to know collision rate (Coll[t]) to update the PFactor The adaptation granularity (i.e. frequency of parameters update) is depending on α’s computation frequency. Note that, in case of unsuccessful packets transmission of class i, the new value of CW is multiplied by the PFactori (see equation 4). The traffic with high priority has a smaller value of PFactor than low priority traffic. By this way, we reduce the probability of a new collision (i.e. better link utilization), which consequently decrease delay. Thus, the initial value of the PFactori is chosen according to the priority of the flow.
3.4 Algorithm description To ensure that the priority relationship between classes is still fulfilled, each traffic class initializes the AIFS value with a value included in its AIFS interval (each traffic class has its own AIFS interval). AIFS_init[i]∈ (AIFS_min[i], AIFS_max[i])
(7)
AIFS_max[i] pcgi) Then AIFS_curri = Max (AIFS_mini, AIFS_curri – SlotTime) PFactor_curri= PFactor_initi } }
If ( i represent a station of high priority) { If (Coll[t] < Avg(Coll[t-1], Coll[t-2], Coll[t-3], Coll[t-4], Coll[t-5])) Then AIFS_curri = Max (AIFS_mini, AIFS_curri – SlotTime) PFactor_curri = PFactor_initi-1 If (Coll[t] >= Avg(Coll[t-1], Coll[t-2], Coll[t-3], Coll[t-4], Coll[t-5])) Then AIFS_curri = Min (AIFS_maxi, AIFS_ curri +SlotTime) PFactor_curri = PFactor_initi+1 } Basically in normal network condition, stations of high priority increase the AIFS value by a SlotTime each time they found that the rate of dropped packets doesn’t exceeds the half‘s threshold (PCGi/2) defined for traffic class i. Further they maintain the PFactori at the initial value. At the same time, due to the low collision rate, best effort stations decrease the AIFS and the PFactor. These allow, in normal network conditions, to narrow the gap between the priority classes. In other words, AMPA decreases the differentiation between the traffic classes. However, when the networks is overloaded, the packets drop rate at the application layer becomes high, and therefore exceeds the half’s threshold defined for high priority flows. Thus the stations’ AIFS is decreased aiming at mitigate the dropped packets. In the same time, the collision rate in the network increases. This leads the best effort stations to increase theirs AIFS and PFactor. In other words, under high network load, AMPA increases the differentiation between the high priority class and best effort, in order to protect the high priority flow. Note that, the computed value of the AIFSi must be in the interval defined for the traffic class i. If the AIFSi value reaches AIFS_maxi or AIFS_mini, it will not be updated anymore. In addition, AMPA reacts when the loss rate exceeds the value PCGi/2. This permits to prevent exceeding the maximum loss rate tolerated PCGi through reacting before reaching the threshold. This anticipation provides as well a smooth bit rate regulation.
priority traffic, and WT2, WT3 as a station with best effort traffic. WT1, WT2 and WT3 start sending their packets at seconds 20, 50 and 70 respectively, through disabling the RTS/CTS scheme. Tables 1 and 2 summarize the relevant parameters used in our simulation. Table 1. EDCF, DCF And AMPA MAC Parameters EDCF
DCF
AMPA
AIFS C DIFS C Update AIFS_ AIFS_min AIFS_max C PF_init PF_max PCG(%) (µs) w 'µs) w period init(µs) (µs) (µs) w
WT1
50
15
70 31
WT2
70
31
70 31
WT3
70
31
70 31
1024 Slot time
30
30
70
15
2
2
5
70
70
90
31
4
6
-
70
70
90
31
4
6
-
Table 2. Application traffic parameters Packet's Interval(sec) size(Bytes)
Start's time(sec) Stop's time(sec)
WT1 flow
1500
0.02
20
200
WT2 flow
800
0.02
50
150
WT3 flow
800
0.02
70
170
4.1 The impact of PFactor over AMPA performance In order to highlight the impact of PFactor’s value on the flow transmission performance (throughput and packet loss rate, and so on) we launched three series of simulation. In the first simulation, we used within AMPA a PFactor value included between 3 and 5, while in the second simulation we used a Pfactor value included between 4 and 6. The last simulation uses a static PFactor. Throughtput values of WT-HP 350000 AMPA with no Pfactor AMPA with Pfactor[3,5] AMPA with Pfactor[4,6]
300000 250000
Bytes/sec
4. SIMULATION AND RESULTS
200000 150000 100000 50000
OP T P I LE X GX1
0
WT3
20
40
60
80
®
Access Point
100 120 Time(s)
140
160
180
200
Figure 5. WT1’s instantaneous bit rate
Wired station
alpha values of WT-HP 40
WT2
AMPA with no Pfactor AMPA with Pfactor[3,5] AMPA with Pfactor[4,6]
35 WT1
To evaluate and compare AMPA’s performances with both EDCF and DCF, we used NS-2 (Network simulator) [14]. The topology of the simulation is rather simple (see Figure 4): three WTs, denoted by WTi where i=1,2 and 3 respectively, are uniformly distributed around an AP (Access Point). WTs are sending theirs packets to a wired host attached to the AP. WT1, WT2 and WT3 use a constant bit rate (CBR) traffic sources over UDP (User Datagram Protocol). We consider WT1 as a station with high
30
% packets
Figure 4. Wireless network topology
25 20 15 10 5 0 0
20
40
60
80
100 120 Time(s)
140
160
Figure 6. WT1's Packet drop rate
180
200
Figure 7 and Figure 8 represent the variation of WT2 and WT3 PFactor’s value during the simulation; we notice that the stations WT2, WT3 increase rapidly their PFatcor’s value to reach the maximum. This maximum value is maintained by WT2 and WT3 until the end of simulation. In other words, it is clearly seen that in case of unsuccessful transmission, WT2 and WT3 wait more time with PFactor’s value equals to 6. Accordingly this gives WT1 more probability to take possession of the channel and to transmit.
Figure 9 plots instantaneous WT1’s AIFS values we notice that WT1 decreases the AIFS’s value only from the 110th second. At this stage, the packet drop rate exceeds the threshold of 5% (see Fig. 11). This is due to the fact that AMPA anticipates the loss rate threshold (α = PCG), by reacting when α = PCG/2. Note that, from the second 190, WT1 packets are transmitted without contention. Figure 10 shows the packet drop rate of the different schemes during the simulation. We observe that AMPA behaves better than the other schemes; the obtained gain is about 35%. DIFS values of WT-HP 7e-05 AMPA with no Pfactor AMPA with Pfactor[3,5] AMPA with Pfactor[4,6]
6.5e-05 6e-05 5.5e-05
sec
Figure 5 and Figure 6 show WT1(High priority) throughput and drop rate respectively. During the interval [20, 50], all three schemes give the same performance. From the 50th seconds (where the three stations share the medium) we notice that the use of PFactor improves considerably the performances. We observe that the packet drop rate in AMPA without PFactor, reaches a 35%, while when we use the PFactor the packet drop rate does not exceed 5% (the parameter α = 5%). Moreover, we see that WT1’s throughput and loss rate are better when the best effort stations (WT2, WT3) use a PFactor varying between 4 and 6.
5e-05 4.5e-05 4e-05 3.5e-05
Pfactor’s values (WT-BE)
3e-05
6
0
AMPA with Pfactor[3,5] AMPA with Pfactor[4,6]
20
40
60
80
100
120
140
160
180
200
Time(s)
5.5
Figure 9. WT1 AIFS values
integer
5
Alpha values WT-HP 45
4.5
AMPA with no Pfactor AMPA with Pfactor EDCF DCF
40 4
3 50
60
70
80
90
100 110 Time(s)
120
130
140
150
Figure 7. WT2 PFactor's values
25 20 15 10
0
AMPA with Pfactor[3,5] AMPA with Pfactor[4,6]
0
5.5
20
40
60
80
100 120 Time(sec)
140
160
180
200
Figure 10. WT1 Packet’s drop rate
5
integer
30
5
Pfactor’s values (WT-BE) 6
4.5
4
3.5
3 50
% packets dropped
35 3.5
60
70
80
90
100 110 Time(s)
120
130
140
150
Figure 8. WT3 PFactor's values These simulations show that the use of a PFactor allows better differentiation between the flows. Hence, PFactor is a critical parameter to be taken into account for the quality of service mapping in the 802.11 wireless LAN.
4.2 Comparing AMPA with EDCF and DCF To highlight AMPA performance, we compare AMPA with basic EDCF and DCF schemes. Note that, we use AMPA with a Pfactor’s value included between 4 and 6.
Figures 11 (a, b, and c) plots the throughput of WT1 (High priority station) when using four medium access mechanisms (DCF, AMPA_with_PFactor, AMPA_no_Pfactor and EDCF). Between 0 and 50 second (only WT1 transmits) all schemes give the same performance. At the second 50, WT2 begin to transmit and shares the medium with WT1. We see that AMPA_PFactor outperforms the other scheme; the enhancement is around 150 Kbytes/sec. However, as soon as WT3 enters in competition for the channel (70th second), we notice a degradation of AMPA’s performance. In the 130th second, AMPA becomes again most powerful of the mechanisms. We can explain this efficiency by: firstly, the WT1’s value is at the minimum value (see Fig. 10). Secondly, the PFactor values of WT2 and WT3 are at the maximum value (see Fig. 6 and Fig. 7). In other words, the adaptive differentiation achieved by AMPA between high priority station (WT1) and best effort station (WT2, WT3) is at the maximum possible.
Throughput WT-HP
350000
350000 AMPA with no Pfactor AMPA with Pfactor EDCF DCF
346500
AMPA with no Pfactor AMPA with Pfactor EDCF DCF
300000
346000
250000
345000
Bytes/sec
345500
200000 150000
200000 150000
344500
100000
100000
344000
50000
50000
343500
0
0
5
10
15
20 25 30 Time(sec)
35
40
45
50
60
80
100
120
0 150
140
155
160
165
Time(sec)
Figure. 11-a. WT1 Bit rate (0-50)
Figure 11-b. WT1 Bit rate(50-150)
Delays WT-HP
185
190
195
200
Delays WT-HP 1.4
1.8 AMPA with no Pfactor AMPA with Pfactor EDCF DCF
170 175 180 Time(sec)
Figure. 11-c. WT1 Bit rate (150-200)
Delays WT-HP
0.01238 0.01236
AMPA with no Pfactor AMPA with Pfactor EDCF DCF
300000
250000 Bytes/sec
Bytes/sec
Throughput WT-HP
Throughput WT-HP
347000
AMPA with no Pfactor AMPA with Pfactor EDCF DCF
1.6
AMPA with no Pfactor AMPA with Pfactor EDCF DCF
1.2
1.4
0.01234
1
1.2
0.0123
0.8
1
sec
sec
sec
0.01232
0.8
0.6
0.01228 0.6 0.4
0.01226
0.4 0.2
0.01224
0.2
0.01222
0 0
5
10
15
20 25 30 Time(sec)
35
40
45
50
Figure. 12-a. WT1 End-to-End Delays (0-50)
60
80
100 Time(sec)
120
140
5. CONCLUSION AND FUTUR WORKS In this paper, we have proposed a general framework (AMPA) for IEEE 802.11 MAC-level QoS provisioning. The AMPA scheme is able to respect specific QoS metrics, providing bounded delays, guaranteed packet loss ration, throughput and so on. Our proposal can achieve a stable performance regardless of the traffic load, which represents the most visible aspects of the dynamic adaptation of AMPA. In this paper, we show that application-level QoS constraints can be mapped efficiently to IEEE 802.11 MAC protocol. Especially, we identified two relevant MAC parameters (PFactori and AIFSi interval) for QoS enforcing through dynamic traffic classes definition. Future works will focus on an analytical/deterministic model to determine the values of each traffic class, allowing QoS continuity from wired networks to wireless networks (e.g. IP Diffserv Classes mapping to AMPA classes).
6. REFERENCES
[1] IEEE, Wireless LAN Medium Access Control (MAC) and Physical Layer (PHY) Specifications, IEEE Standard 802.11, 1999 [2] IEEE 802.11g(tm)-2003, Part11 Wireless LAN Medium Access Control (MAC) and Physical Layer (PHY) Specifications Further Higher-Speed Physical Layer Extension in the 2.4 GHZ Band, Supplement to IEEE Standard, 2003.
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Figure. 12-b. WT1 End-to-End Delays (50-50)
Figures 12 (a, b, and c) represents instantaneous WT1 end-toend delays during the whole simulation. We observe that AMPA makes it possible to improve the delays even when the canal is shared between the three stations [70,150]. AMPA maintains the delays bellows 0.6 second, while the others schemes have delays around 1.7 second.
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Figure. 12-c. WT1 End-to-End Delays (150-200)
[3] IEEE 802.11e, Wireless LAN Medium Access Control (MAC) Enhancements for Quality of service (QoS), 802.11e Draft 3.1, Mai 2002. [4] S. Blake et al, "An Architecture for Differentiated Services". RFC 2475, December 1998 [5] R. Brden., D. Clarck, S. Shenker. "Integrated services in the Internet Archotecture: an Overview". Internet RFC 1633, June 1994. [6] M. Benveniste, "Proposed Normative Text for TCMA",IEEE 802.11-01/117, Mar 2001. [7] M. Benveniste", "'Tiered Contention Multiple Access' (TCMA), A QoS-Based Distributed MAC Protocol", The 13th IEEE International Personal, indoor and Mobile Radio Communications Symposium, 2002. [8] I.Aad, C.Castelluccia, "Differentiation mechanisms for IEEE802.11", IEEE Infocom, Avr 2001. Anchorage, Alaksa 2001 [9] H.26L working draft. http://standard.pictel.com/ftp/video\site/h26l/jwdxx.doc, where xx is the version number. [10] N.H. Vaiday, P.Bahl and S. Gupa, "Distributed Fair Scheduling in a Wireless LAN", Sixth annual International Conference on Computing and networking, Boston, USA Aout 2000. [11] A. Banchs and X. Perez, "Providing Throughput Guarantees in the IEEE 802.11 Wireless LAN", IEEE Wireless Communications and Networking Conference WCNC, Orlondo, USA Mar 2002. [12] L. Romdhani, Q.Ni and T.Turletti, "Differentiation mechanisms for IEEE802.11", IEEE Wireless Communications and Networking Conference WCNC, New Orlean, USA 2003. [13] G. Chesson, W. Diepstraten, D. Kitchin and H. Teunissen , "Baseline D-QoS Proposal", IEEE 802.11-03/399. [14] Network Simulator 2, http://www.isi.edu/nsnam
