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Client Protection in Wireless Home Networks Kandaraj Piamrat and Patrick Fontaine Technicolor 1, avenue de Belle Fontaine 35576 Cesson-Sévigné, France {kandaraj.piamrat, patrick.fontaine}@technicolor.com Abstract—In-home wireless networks are currently available in every home today. However, the open nature of wireless medium and the increase of wireless traffic make it difficult for network operator to guarantee user experience of provided services. In this paper, we focus on multimedia services especially wireless IPTV that needs to be guaranteed by network operator. In order to avoid global degradation and to ensure per-client quality, we propose to use a fair-scheduler implementable with Quiet Element available in the IEEE 802.11 standard. Unlike most of existing schemes, our proposition is applicable to both downlink and uplink streams and can be implemented easily in real access point products. Performance evaluation is conducted using NS-3 and real house propagation maps. Keywords-wireless home networks; client protection; traffic isolation; IPTV service I. INTRODUCTION As a problematic fact, wireless network is a share and open environment, thus it is prone to interference and disturbance from the surroundings. Moreover, as with the shared medium, node suffering from bad quality will impact other nodes in the same environment. This anomaly problem has been raised and investigated in [1]. To adapt to changing condition, IEEE 802.11 standard [2] has provided a set of transmission rates. For instance, eight modulations exist in IEEE 802.11a [3] (6, 9, 12, 18, 24, 36, 48, 54 Mbps). Generally, high rates can be used when channel condition is good enough like short distance whereas lower rates are used to reach farther recipients and are more robust to interference or mobility. However, the problem of lower rates is the longer occupied airtime due to slower transmission of the same amount of data. Consequently, using these rates result in less airtime remaining for other users (i.e. if one station is suffering, all the others will be affected as well). Our objective is to prevent this problem by protecting/ isolating clients having good conditions from those having bad conditions. Therefore, when one client is degrading, the remaining clients will not be affected. Another objective is the ease of deployment. The solution should require no change in legacy clients otherwise it will never be deployed in real networks. In this paper, we will focus on wireless home networks, which are emerging rapidly today. The focus will be on IPTV service that needs to be guaranteed by network operator. In fact, providing IPTV services on wireless networks is a big challenge since the required packet loss rate at application layer is as low as 10 -8 and with such a varying network environment as Wi-Fi, it is a difficult task. The remainder of this paper is organized as follow. Section II provides related works then Section III describes the proposed scheme in details. Section IV presents performance evaluation in different angles. Finally, section V provides conclusions and future works. II. RELATED WORKS Several works have been proposed to handle resource allocation problem in wireless networks using especially scheduling mechanisms. Major issues concerning wireless scheduling are link variability, fairness, QoS, throughput, channel utilization, power consumption, and simplicity. Metrics for scheduler are various, for example, link utilization, delay bound, fairness, throughput, service degradation, isolation, energy consumption, implementation complexity, scalability, it is hence difficult to guarantee all of them. Many schemes deploy scheduler at the access point (AP); numerous propositions derived from standard schedulers (DCF or EDCA) such as MPDCF [4], or traditional schedulers (Deficit Round Robin (DRR), Fair Queuing (FQ)) such as DWFSS [5]. However, most of the time, the objective is fair share regarding throughput or throughput maximization. Most often, only on downlink direction that can be managed easily by the AP. For dealing with both directions (including uplink transmission from users), there are also standard schedulers (PCF or HCF), its variants (FHCF [6]), or others schedulers such as JUDS [7] or SHAPE [8]. Even though, they have powerful performance, they are usually not compatible with legacy equipments. On the other hand, related works also concern traffic isolation issue such as SleepWell [9], which schedule shifted transmission among APs with the goal of minimizing energy consumption. Contrary to existing solutions that optimize overall throughput and performance of every clients; our goal is an easily deployable solution that can guarantee excellent quality for clients having good network condition. For that, we deploy TDMA for resource allocation and round robin for its simplicity of implementation. Our solution will provide fairness (regarding allocating airtime) and protection for good- conditioned clients. Moreover, it is applicable to both downlink and uplink directions and is compatible with the standard. III. PROPOSED MECHANISM In this section, we describe the concepts of our proposed mechanism and the implementation of our solution. A. Concepts The IEEE802.11 standard lacks of per-stream Quality of Service (QoS) guarantee. In fact, today’s wireless clients are WMM certified which can provide prioritized access for voice and video streams over data flows. Access categories are defined to differentiate between four classes of service (namely voice, video, data and background); however there is no differentiation between two streams of the same category, like two video streams for example. According to the standard, CSMA/CA mechanism does not define the limitation of airtime occupied by client suffering from bad link quality. In such case, flows in the same category may be affected by a bad- quality node (due to sharing of the same transmission queue for 2011 IEEE International Conference on Consumer Electronics - Berlin (ICCE-Berlin) 978-1-4577-0234-1/11/$26.00 ©2011 IEEE 34

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Page 1: [IEEE 2011 IEEE First International Conference on Consumer Electronics - Berlin (ICCE-Berlin) - Berlin, Germany (2011.09.6-2011.09.8)] 2011 IEEE International Conference on Consumer

Client Protection in Wireless Home Networks

Kandaraj Piamrat and Patrick Fontaine Technicolor

1, avenue de Belle Fontaine 35576 Cesson-Sévigné, France

{kandaraj.piamrat, patrick.fontaine}@technicolor.com

Abstract—In-home wireless networks are currently available in every home today. However, the open nature of wireless medium and the increase of wireless traffic make it difficult for network operator to guarantee user experience of provided services. In this paper, we focus on multimedia services especially wireless IPTV that needs to be guaranteed by network operator. In order to avoid global degradation and to ensure per-client quality, we propose to use a fair-scheduler implementable with Quiet Element available in the IEEE 802.11 standard. Unlike most of existing schemes, our proposition is applicable to both downlink and uplink streams and can be implemented easily in real access point products. Performance evaluation is conducted using NS-3 and real house propagation maps.

Keywords-wireless home networks; client protection; traffic isolation; IPTV service

I. INTRODUCTION As a problematic fact, wireless network is a share and open

environment, thus it is prone to interference and disturbance from the surroundings. Moreover, as with the shared medium, node suffering from bad quality will impact other nodes in the same environment. This anomaly problem has been raised and investigated in [1]. To adapt to changing condition, IEEE 802.11 standard [2] has provided a set of transmission rates. For instance, eight modulations exist in IEEE 802.11a [3] (6, 9, 12, 18, 24, 36, 48, 54 Mbps). Generally, high rates can be used when channel condition is good enough like short distance whereas lower rates are used to reach farther recipients and are more robust to interference or mobility. However, the problem of lower rates is the longer occupied airtime due to slower transmission of the same amount of data. Consequently, using these rates result in less airtime remaining for other users (i.e. if one station is suffering, all the others will be affected as well).

Our objective is to prevent this problem by protecting/ isolating clients having good conditions from those having bad conditions. Therefore, when one client is degrading, the remaining clients will not be affected. Another objective is the ease of deployment. The solution should require no change in legacy clients otherwise it will never be deployed in real networks. In this paper, we will focus on wireless home networks, which are emerging rapidly today. The focus will be on IPTV service that needs to be guaranteed by network operator. In fact, providing IPTV services on wireless networks is a big challenge since the required packet loss rate at application layer is as low as 10-8 and with such a varying network environment as Wi-Fi, it is a difficult task.

The remainder of this paper is organized as follow. Section II provides related works then Section III describes the proposed scheme in details. Section IV presents performance evaluation in different angles. Finally, section V provides conclusions and future works.

II. RELATED WORKS Several works have been proposed to handle resource

allocation problem in wireless networks using especially scheduling mechanisms. Major issues concerning wireless scheduling are link variability, fairness, QoS, throughput, channel utilization, power consumption, and simplicity. Metrics for scheduler are various, for example, link utilization, delay bound, fairness, throughput, service degradation, isolation, energy consumption, implementation complexity, scalability, it is hence difficult to guarantee all of them. Many schemes deploy scheduler at the access point (AP); numerous propositions derived from standard schedulers (DCF or EDCA) such as MPDCF [4], or traditional schedulers (Deficit Round Robin (DRR), Fair Queuing (FQ)) such as DWFSS [5]. However, most of the time, the objective is fair share regarding throughput or throughput maximization. Most often, only on downlink direction that can be managed easily by the AP. For dealing with both directions (including uplink transmission from users), there are also standard schedulers (PCF or HCF), its variants (FHCF [6]), or others schedulers such as JUDS [7] or SHAPE [8]. Even though, they have powerful performance, they are usually not compatible with legacy equipments. On the other hand, related works also concern traffic isolation issue such as SleepWell [9], which schedule shifted transmission among APs with the goal of minimizing energy consumption.

Contrary to existing solutions that optimize overall throughput and performance of every clients; our goal is an easily deployable solution that can guarantee excellent quality for clients having good network condition. For that, we deploy TDMA for resource allocation and round robin for its simplicity of implementation. Our solution will provide fairness (regarding allocating airtime) and protection for good-conditioned clients. Moreover, it is applicable to both downlink and uplink directions and is compatible with the standard.

III. PROPOSED MECHANISM In this section, we describe the concepts of our proposed

mechanism and the implementation of our solution.

A. Concepts The IEEE802.11 standard lacks of per-stream Quality of

Service (QoS) guarantee. In fact, today’s wireless clients are WMM certified which can provide prioritized access for voice and video streams over data flows. Access categories are defined to differentiate between four classes of service (namely voice, video, data and background); however there is no differentiation between two streams of the same category, like two video streams for example. According to the standard, CSMA/CA mechanism does not define the limitation of airtime occupied by client suffering from bad link quality. In such case, flows in the same category may be affected by a bad-quality node (due to sharing of the same transmission queue for

2011 IEEE International Conference on Consumer Electronics - Berlin (ICCE-Berlin)

978-1-4577-0234-1/11/$26.00 ©2011 IEEE 34

Page 2: [IEEE 2011 IEEE First International Conference on Consumer Electronics - Berlin (ICCE-Berlin) - Berlin, Germany (2011.09.6-2011.09.8)] 2011 IEEE International Conference on Consumer

downlink flows or same access priority for uplink flows). Our objective is to avoid this situation by enabling intra-class differentiation between clients. To do so, our mechanism deploys two concepts: 1) traffic isolation between multiple clients and 2) fair allocation through TDM.

� Traffic isolation In our mechanism, clients are isolated in different basic

service sets (BSS). For that, multiple virtual APs (VAP) are created within the same physical AP. Each VAP defines a virtual WLAN by broadcasting its beacon with a unique BSS identifier (BSSID). Each client of the wireless network is then associated to a different VAP. For downlink streams, the AP has separate transmission queue for each BSS; therefore traffic between multiple clients can be isolated and scheduled in a proper way. For uplink streams, the AP needs a mechanism to control access to the medium and to allocate airtime for each client. Since each client is associated to a different BSS, the airtime allocation will be controlled on a per BSS basis, as will be explained in more details in the next subsection.

� Fair allocation To allocate bandwidth between clients, airtime in a network

is divided into N partitions corresponding to the number of clients in the network. In order to guarantee fairness (regarding the required throughput) among different clients, each client has a dedicated airtime corresponding to the one necessary for sending its traffic using a specified modulation (for example highest modulation). Therefore, we obtain a fair allocation since each node will receive the allocated duration that is proportional to its throughput requirement. We assume non saturated network where overall traffic (if transmitted at the specified rate) does not exceed network capacity. A scheduler implementing TDM will be presented in the next subsection.

B. Implementation This section describes implementation of frame definitions

and communication architecture. Modifications are applied only to AP; our solution is hence compatible with legacy clients (without any change).

� Frame definitions The implementation of allocation and protection can be

done via Quiet Element (QE), available already in the IEEE 802.11h standard [10] and products operating in 5GHz band, where dynamic frequency selection (DFS) is mandatory. This element, which is part of Beacon frame, enables a (virtual) AP to prevent any transmission of its station during a specified time. Only station associated to this BSS will not be allowed to transmit. Therefore TDMA between multiple stations that are isolated in different BSS can be implemented by scheduling QE in beacon frames of the VAPs.

Figure 1 shows the format of a QE. The interesting values are Quiet Duration (duration of the interval) and Quiet Offset (offset of the start of the interval, related to the target beacon transmission time (TBTT)). Both are expressed in unit of 1ms.

Element ID Length Quiet

CountQuiet Period

Quiet Offset

Quiet Duration

Figure 1. Quiet Element

According to flows requirements, a scheduler constructs a TDM frame which is translated into QEs. To achieve low latency, the Beacon frames of each BSS can include several QEs, in order to define more than one sub-frame per beacon interval. Figure 3 illustrates an example, two QEs are used in order to create two super frames in one Beacon interval (duration between the transmission of two beacons). We can notice that Beacon transmissions are shifted (between the two BSSs) but quiet periods are still synchronized. Beacon transmission could also be delayed by a busy medium, but quiet periods would again remain synchronized since quiet intervals are relative to TBTT. As the multiple VAPs are created in the same physical AP, the AP can compute timing information needed to elaborate the QE, for example the TBTT offset between two VAPs.

� Communication architecture

VAP1

Scheduler

TSFTimer

QuietGenerate

BeaconGenerate

AP

STA1

QuietAnalysis

BeaconReception

VAPN

TSFTimer

QuietGenerate

BeaconGenerate

STAN

QuietAnalysis

BeaconReception

...

... Figure 2. Functional blocks

Figure 2 depicts the functional blocks involved in the implementation of the protection between multiple clients. One physical access point supports multiple virtual BSSs. VAP1 to VAPN are created in order to isolate the N clients in different BSS. Usually, in current products, number of VAPs can be between 5 and 8 but it can goes up to 19 for some of them. A scheduler, in the AP, implements TDMA by allocating airtime to the virtual BSSs. It creates sub-frames for each BSS by generating alternative quiet periods. For synchronization of the sub-frames, it retrieves TSF timers of each VAP and computes the TBTT offset between all BSSs. The sub-frames are converted in Quiet Element and added to a beacon of the proper BSS. STA1 to STAN are legacy clients without any modification. Wireless clients can receive beacons from all BSSs but only the QEs from its own BSS are taken into account, as indicated in the standard.

B B

BSS1 Beacon interval

B B

BSS2 Beacon interval

BSS2 Quiet

BSS1 sub-frame

BSS1 CSMA/CAData exchange

BSS2 CSMA/CAData exchange

Super Frame

TBTT offsetTBTT1 TBTT2

BSS1 Quiet

Super FrameSuper Frame

BSS2 sub-frame BSS1 sub-frame BSS2 sub-frame BSS1 sub-frame BSS2 sub-frame

BSS2 CSMA/CAData exchange

BSS2 CSMA/CAData exchange

BSS2 Quiet BSS2 Quiet

BSS1 CSMA/CAData exchange

BSS1 CSMA/CAData exchange

BSS1 Quiet BSS1 QuietTime

Time

Figure 3. Virtual BSS coordination with quiet periods

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IV. PERFORMANCE EVALUATION A. Scenario

We describe network topology of the test here. Figure 4 indicates signal attenuation when the transmitter is the AP. For realistic propagation loss, we use propagation maps of the floor plan of a real apartment obtained via Volcano [11], more details can be found in [12]. In the evaluation, there are two clients (one stream of 10Mbps per client). Two scenarios are considered: 1) scenario with only downlink traffic (DL-DL); and 2) scenario with both uplink and downlink traffic (UL-DL). The first stream (video0) represents IPTV transmission: a DL flow in (1) from the AP to a television and an UL flow in (2) from a Personal Video Recorder (PVR) to the AP; both nodes are stationary. A second stream (video1) represents a flow transmitted to a mobile tablet; its mobility within high-attenuated area is on purpose because we want to illustrate the effect of degradation. It can be noticed that we only focus on one section of the apartment that better illustrates the scenario.

Figure 4. Signal attenuation

Nodes’ mobility during connection is presented in Figure 5. The client0 is almost stationary (rectangle), client1 moves randomly (dots) within the delimited area, this movement covers approximately the whole specified space. One physical AP is placed in the scenario. In legacy approach, the AP serves both clients. In our approach, one physical AP has two virtual APs installed at the same position (vap0 and vap1); one VAP serves only one client.

Figure 5. Nodes’ mobility for scenario: DL-DL (left) & UL-DL (right)

B. Test Set up NS-3 [13] configuration is presented in Table I. Standard

IEEE 802.11a is deployed with 5GHz band and 20MHz bandwidth. The noise figure has been modified for realistic indoor environment. As for the power, output power is set to 15 dBm, transmission and reception gains of antennas are 2dBi. For rate adaptation, ideal algorithm has been used. With this algorithm, rate is selected according to signal to noise ratio

(SNR) of client. Moreover, realistic propagation mappings have been integrated into NS-3; these mappings, which depend on floor plan of the house, represent signal attenuation illustrated in Figure 4.

TABLE I. NS-3 CONFIGURATION Parameter Value

Standard IEEE 802.11a Frequency channel 5GHz, 20MHz BW Noise figure 7+19 dB [14] ED/CCA threshold -82/-62 dBm [2] Output power 15dBm Tx and Rx antenna gains 2dBi Rate adaptation algorithm Ideal (based on SNR)

C. Results The results are presented in two parts, scenario with: 1)

downlink direction only (DL-DL); and 2) both uplink downlink direction (UL-DL).

1) Scenario with only downlink traffic (DL-DL): We recall that in this scenario the video0 is transmitted to a TV set (stationary node) and the video1 is transmitted to a mobile tablet (mobile node). We discuss here different metrics such as signal strength along with selected transmission rates then we continue with goodput and the summary of performance concerning statistics on packet loss, retransmission, etc. For visibility reason, results are shown for only 60s of simulation. � Signal strengths during the connection are presented in

Figure 6. It can be noticed that client0 always has very good received signal strengths (RSS) since this node is stationary and remains in the living room where signal attenuation from the physical AP is low. On the other hand, the mobility of client1 affects directly its RSS as we can observe the fluctuating values. In ideal algorithm, values of RSS should be higher than -52.4 dBm for transmission at 54 Mbps, for example.

Figure 6. Signal strength of clients

Figure 7. Selected modulation of the two clients

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Page 4: [IEEE 2011 IEEE First International Conference on Consumer Electronics - Berlin (ICCE-Berlin) - Berlin, Germany (2011.09.6-2011.09.8)] 2011 IEEE International Conference on Consumer

� Selected transmission rates during the connection are presented in Figure 7. It can be noticed that the fluctuating RSSs of client1 result directly in different rate selected along the connection. Transmission rate frequently goes down to 48, 36, 24, 18, 12 Mbps, these slower rates selected for transmission are harmful in open environment such as wireless networks because sending at lower rate requires more time to transmit the same amount of traffic. In our case, two flows of 10 Mbps makes the total of 20 Mbps net on bandwidth requirement. If sending at lower rates (lower than 20 Mbps), saturation is unavoidable and packet loss can occur resulting in overflow at AP’s queue.

� Goodput of the two schemes are presented in Figure 8. We can observe that, with our proposition, while video1 is suffering from bad performance, video0 can still enjoy perfect quality and the required throughput is guaranteed. On the contrary, the previously described impact of shared environment can be clearly observed here: while video1 of legacy scheme suffers from mobility and bad RSS, video0 is also affected and finally both service qualities are degraded as bad as each other. We can observe the obtained goodput of the two stations are very similar, the curve of video0 follows tightly the one of video1. This typical problem cannot be solved neither with WMM (Wi-Fi Multimedia) since in such mechanism only one queue exist per type of traffic.

Figure 8. Goodput: with protection (left) and legacy (right)

� Performance summary of DL-DL scenario is presented in Table II, in terms of packet dropped at AP’s queue (%drop), retransmission at AP (%retx), and packet loss rate at application level of client (PLR). First, we can observe that the percentages of drops at AP’s queue of the two clients in legacy approach are as high as each other. On the contrary, both clients in our scheme perform much better (video0 can enjoy error-free transmission). We recall that the packet dropped at the AP’s queue cannot be recovered since UDP is used as transport protocol for IPTV. One can argue that our configuration is not fair because in legacy approach, the two clients need to share the same queue at AP while in virtual AP approach they are not. In order to avoid the biased results regarding this issue, we have also provided results while setting the queue size of AP in legacy scenario to be doubled the one of virtual AP (labeled legacy doubled queue size). The percentage of drops at AP queue is a slightly better but no improvement obtained elsewhere. Second, as video1 in legacy approach suffers from bad channel condition (due to mobility), the retransmission number climbs up to 15% while in our approach there is only 3.5% of retransmission. This higher number of retransmissions results in the higher number of drops at

AP’s queue. It should be remarked here that the gain obtained from the retransmission will be very useful when the number of users increases. As we know that the higher the number of retransmission, the smaller the airtime left for other users. As a consequence, with legacy approach, none of the client can have guarantee on their video quality (required PLR <10-8); our proposed mechanism can guarantee at least one client in this scenario, which is the IPTV transmission to the television. For the mobile node, it is difficult to recover since it moves around and encounters areas where RSS are poor, even higher transmission rate will not help since it is less robust to channel error. In the future, we can deploy more APs with coordination to remedy this problem.

TABLE II. PERFORMANCE SUMMARY

%drop %retx PLR

DL-

DL

legacy scheme video 0 14.1 0.0 10-1 video 1 15.1 15.0 10-1

legacy doubled queue size

video 0 12.1 0.0 10-1 video 1 12.9 15.1 10-1

proposed scheme

video 0 0.0 0.0 <10-8 video 1 2.8 3.5 10-2

2) Scenario with both uplink & downlink traffic (UL-DL): In this section, we provide the results of the second case study. As a recall, there are traffic in both uplink and downlink direction in this case. The downlink traffic corresponds to IPTV flow running on the mobile tablet (mobile node), the uplink traffic corresponds to the PVR traffic (stationary node) uploading to the internet. � Goodput of the two schemes are presented in Figure 9. It

can be noticed that with this configuration, both schemes have slightly differences on performance. The curve of video0 in legacy approach has small peaks along the session and the curve of video1 in legacy approach has much more fluctuations than in our approach. It can be noticed that the obtained performances in both cases are quite similar; this can be explained by the fact that there are two senders in this scenario. In the previous scenario DL-DL, both nodes in legacy scheme have to share the same channel and the same AP’s resources. Therefore, when one station suffers, the other will suffer as well. On the other hand, in scenario UL-DL, the two streams are transmitted by two different senders thus they are more independent (one transmitter is PVR node and the other one is AP).

Figure 9. Goodput: with protection (left) and legacy (right)

� Packet drops at client are presented in Figure 10 in order to better illustrate the results. These drops are caused by error at reception. In order to illustrate the problem, we focus on drops of video1 which suffers from mobility. The plotted graph illustrates number of drop per 100 ms in both schemes. The average number of dropped packets in

37

Page 5: [IEEE 2011 IEEE First International Conference on Consumer Electronics - Berlin (ICCE-Berlin) - Berlin, Germany (2011.09.6-2011.09.8)] 2011 IEEE International Conference on Consumer

legacy approach is 12.4 versus only 7.47 in the proposed scheme. This confirms that with our method of traffic isolation using Quiet element, error can be decrease as much as 40%.

Figure 10. Drops at mobile node due to error at reception.

� Channel occupancy time of AP for video1 is presented in Figure 11. It can be remarked that high numbers of errors in Figure 10 results in high retransmission as we can see from Table III that numbers of retransmission in legacy scheme are higher than in our scheme. These retransmissions result directly in channel occupancy time that is higher (maximum 40 % in legacy scheme and only 30% maximum in our scheme) for sending the same amount of traffic. It can also be noticed from Table III that percentages of airtime occupied (%busy) by both transmitters are almost equal in our scheme, which is not the case of legacy scheme.

Figure 11. Channel occypancy time of access points.

� Performance summary of UL-DL scenario is presented in Table III. We can observe that stationary node (PVR uplink) with legacy scheme can also achieve the required PLR but with higher retransmissions than in our scheme. These retransmissions result from collision between AP and uplink transmitter. On the other hand, in our scheme, the retransmission is zero because we have a fair and protected airtime sharing between all transmitters. The mobile nodes in both schemes obtained similar results. The problem of packets dropped at AP’s queue is due to the airtime sharing among virtual APs, which is not optimized in this proposition (based on the proportion of traffic affected to each AP). In the future, we can improve this mechanism to provide an optimized sharing taking into account more factors such as delay, jitter, packet size, packetization interval, peak rate, etc.

V. CONCLUSION AND FUTURE WORKS We have proposed a mechanism that can protect client from

degradation impact of others in a shared environment. For ease

of implementation, we deploy Quiet Element available in the standard to coordinate transmission among different nodes (both downlink and uplink directions). According to the regulatory organizations [15][16], all clients willing to operate on 5GHz band have to support Dynamic Frequency Selection, which includes Quiet Element. Therefore, our scheme is compatible with the standard especially with legacy clients.

In the future, we plan to refine the airtime allocation among virtual APs by traffic categories taking into account characteristics and requirements of different traffic classes. We will also extend the scenario to use the concept to multiple-APs approach [17] within the home network or for large-scaled usages.

TABLE III. PERFORMANCE SUMMARY

%drop %retx PLR %busy

UL-

DL legacy scheme video 0 0.0 2.2 10-8 21.7

video 1 5.9 10.9 10-2 22.9

proposed scheme video 0 0.0 0.0 10-8 21.2 video 1 9.3 7.0 10-1 21.0

REFERENCES [1] M. Heusse, F. Rousseau, G. Berger-Sabbatel, and A. Duda, 2003.

“Performance anomaly of 802.11b”. In Proceeding of INFOCOM’03, 2, pp. 836-843.

[2] IEEE 802.11-2007, Part 11: Wireless LAN Medium Access Control (MAC) and Physical Layer (PHY) Specifications.

[3] IEEE standard 802.11a-1999, Part 11: Wireless LAN Medium Access Control (MAC) and Physical Layer (PHY) Specifications: High-speed Physical Layer in the 5 GHZ band. IEEE Computer Society. 1999.

[4] H. Yoon; H. Gi Ahn; T.-J. Lee; K. Jang; J.-B. Chang 2006 "Traffic Scheduling for MPDCF MAC to Support QoS-Sensitive Data in IEEE 802.11 Wireless LANs," First International Conference on Communication System Software and Middleware, vol., no., pp.1-5.

[5] A. Riza, L.T. Chaw, P. K. Keong, H.K. Pee 2010 “Improving QoS in WLAN using dynamic weighted fair scheduling,” Malaysian Journal of Computer Science, vol.23(2), pp. 85-101.

[6] P. Ansel, Q. Ni, T. Turletti, 2006 “FHCF: A Simple and Efficient Scheduling Scheme for IEEE 802.11e Wireless LAN” in Mobile Networks and Applications, vol.11, no.3, pp. 391-403.

[7] J. Yoo, H. Luo, and C.-K. Kim 2009 “Opportunistic Joint Uplink/Downlink Scheduling for WLANs”, Technical Report UIUCDCS-R-2006-2757. url: http://hdl.handle.net/2142/11239.

[8] M. Carrera, P. Srikhantha, M. May, C. Rosenberg 2011 “SHAPE: Scheduling in Wireless Home Networks”, Technicolor Technical Report http://www.thlab.net/~carrera/ attachments/CR-PRL-2011-01-0001.pdf

[9] J. Manweiler and R. R Choudhury 2011 “Avoiding the Rush Hours: WiFi Energy Management via Traffic Isolation” in press Mobisys 2011.

[10] IEEE standard 802.11h-2003, Amendment 5: Spectrum and Transmit Power Management Extensions in the 5 GHz band in Europe.

[11] SIRADEL, VOLCANO Suite 3.0 2010, url: http://www.siradel.com/1/volcano-software-suite.aspx

[12] F. Baron, 2011 “Propagation simulation for NS3” Technicolor Technical Report,CR-RRL-2011-03-0001. url: http://www.thlab.net/~fontainep/ref/

[13] The ns-3 network simulator. url: http://www.nsnam.org [14] E. Perahia and R. Stacey, 2008 Next Generation Wireless LANs:

Throughput, Robustness, and Reliability in 802.11n. Cambridge University Press.

[15] FCC. 2006. Part 15 Subpart E Compliance Measurement Procedures for Unlicensed-National Information Infrastructure Devices Operating in the 5.25-5.35 GHz and 5.47-5.725 GHz Bands Incorporating Dynamic Frequency Selection.

[16] ETSI. 2008. Broadband Radio Access Networks (BRAN), 5GHz High Performance RLAN, EN 301 893 v1.5.1.

[17] K. Piamrat and P. Fontaine 2011 “Coordinated Architecture for Wireless Home Networks”, accepted for publication in SIGCOMM Workshop on Home Networks (HomeNets).

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