2013 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery
Context-aware Optimization on Medium Access Delay for High-density 802.11n Wi-Fi Network Guolin Sun, Guisong Liu, Yao Li, Chuan Xiao School of Computer Science and Engineering University of Electronic Science and Technology of China Chengdu, China E-mail:
[email protected]
which is known as the effective number of clients for a single AP in this paper. Quality of user Experience (QoE) becomes an important performance metric in wireless networks. In order to provide better QoE in high-load scenarios, information of application characteristics can be used to improve the performance of 802.11n, which is called application-aware[3, 4]. The intuition tells us network congestion state can instruct us to choose a smart way for MAC transmission in 802.11n network. With experiments on our prototype, we take the channel utilization rate as channel busy time. In this paper, we are motivated to design algorithms with bursting transmission to improve QoE with the consideration of high-load context. The section 2 describes the practical phenomenons in the scenario of HT 802.11n network and defines the technical problem in this paper. In section 3, we provide a simple context-aware adaptive link transmission algorithm for the problem. The experimental test on the WiFi prototype is evaluated in section 4. In the end, we make conclusion in Section 5.
Abstract—With demands from increasing population of Wi-Fi devices, diversification of application services, and high-density deployment of APs, we need more care about the Quality of user Experience in 802.11 Wi-Fi networks. In this paper, we propose a context-aware optimization method with bursting transmission to reduce medium access delay of clients in highload scenario and improve effective number of clients in highdensity scenario of 802.11n network. To determine the time to switch MAC frame transmission modes, we choose the channel utilization rate to indicate the “channel busy time”. We switch transmission modes once the channel utilization rate is higher than a fixed threshold. We implement this method on Atheros 9340 chips and evaluate it on the performance of End-to-End transmission delay with TCP scripts instead of Ping commands with Chariot tools in our prototype of 802.11n Wi-Fi APs. The experimental results show the proposed method can improve the effective client number of APs and reduce access delay in the situation of high-density clients. Keywords- context-aware optimization, 802.11n, medium access delay
I.
II.
INTRODUCTION
With the development of mobile wireless network in the past 20 years, a variety of terminal forms appear in 802.11n Wi-Fi network. A sample High-Throughput (HT) scenario with different forms includes smart phone, iPad, Laptop, which is illustrated in the Fig.1. The 802.11n Wi-Fi network can be compatible with the legacy devices, 802.11a/b as well as 802.11g.The HT mode means that all clients are working in the 802.11n mode[1].
The IEEE 802.11n standard is playing an important role in the rapid development of wireless network. IEEE 802.11n mainly combines optimization of Medium Access Control (MAC) and Physical Layer (PHY) to improve throughput performance sufficiently and increase the bit rate to be up to 600Mbps[1]. IEEE 802.11n MAC improves the throughput by aggregating multiple frames into one AMPDU or AMSDU before transmission[2]. Frame aggregation scheme can reduce the transmission time for preamble and frame headers as well as the waiting time in the CSMA/CA(Carrier Sense Multiple Access – Collision Avoidance) random back-off period for successive frame transmission. At PHY layer, 802.11n uses MIMO(Multiple-Input Multiple-Output) to increase the bit rate. Due to traffic explosion and spectrum scarcity, 802.11 APs are often deployed in a high-density Wi-Fi nework. A variety of terminal types appear in our daily lives, such as smart phone, iPad, Lap-top and so on. All mobile terminals will be equipped with Wi-Fi interfaces in the future. These mobile devices can offer supports for a rich set of application, such as live video conferencing, online games and music sharing, and others. However, the performance of AP today can’t support a large number of clients to connect at the same time, 978-0-7695-5106-7/13 $26.00 © 2013 IEEE DOI 10.1109/CyberC.2013.85
SCENARIO DESCRIPTION AND PROBLEMS
Figure 1 The mixed-form client scenario 461
Under the condition of saturated load for 802.11n Wi-Fi network, the maximum number of 802.11n clients connected with a single AP is definitely limited. For the original SDK, a standalone AP can connect with fifteen clients at most at a common time under the saturated load condition in 802.11n HT mode. Once the number of client is greater than 15, two phenomenons can be observed as below: 1) some clients will be dropped; 2) the average MAC access delay of clients will be larger than 100ms. The value 100ms is the threshold for video frames transmission without interrupts. Obviously, the QoE will decrease heavily when the AP deployed in a place with a large population of clients. Therefore, our goal in this paper is to improve the effective number of clients which AP can connect at the same time. Through context sensing with channel utilization rate, we try to find a way to increase the effective number of clients which a Wi-Fi AP can connect with at the same time. III.
higher throughput by allowing the transmitter to send a series of frames in succession without relinquishing control of the transmission medium, as shown in Fig.2 (b). In the standard transmission procedure, all of Wi-Fi devices must contend for Transmission Opportunities (TXOPs) to access medium then transmit data. The program would do split according to the time period. Once it finishes a successful transmission, the device will try to get an extra TXOP again. However, in frame bursting transmission, each device requests a burstduration for a long time based on the length of service queue, before they attempt to transmit a series of frames. As a result, it shortens the dead-time between each frame, and the entire transmission time could be shortened. That means the frame bursting transmission with un-interrupted transmission does not only increase the number of packets sent, but also check if any node needs radio resource. In this way, it reduces the resource waste and increases the throughput. Considering the burst traffic, we allocate a fixed burst duration to the clients to empty the incoming packets. In this way, we expect the channel busy rate will be reduced so that we can provide more TXOPs for new access clients. In this paper, we propose to switch the transmission mode dynamically with context-aware design. Through detecting channel busy or not, we can get the measurements of channel utilization. Based on the channel utilization rate, we can determine when to switch frame transmission mode. In this way, we expect to achieve the goal of improving the number of clients AP can connect with. The algorithm procedure is illustrated in Fig.3.
THE PROPOSED SOLUTION
The frame aggregation mechanism was defined in IEEE 802.11n Std. documents[1]. The A-MPDU frame aggregation procedure at MAC layer is shown in Fig.2 (a). At first, each MSDU appends with its own MAC header and FCS to form a sub-MPDU. Before each sub-MPDU, an MPDU delimiter is then inserted. In order to make each sub-MPDU is 4 bytes in length, padding bits are inserted and padding bits can also facilitate sub-frame delineation at the receiver. Then, all the sub-MPDUs are concatenated to form a large PSDU.
Figure 2 (a) Frame format for A-MPDU
Figure 3 The switch algorithm procedure IV.
EXPERIMENT AND EVALUATION
An experiment and prototype, outlined as below, is done to check the gains on system throughput and access delay of 802.11n Wi-Fi clients. A cross-over Ethernet cable should be used to connect the server AP and client APs for throughput
Figure 2 (b) Frame Bursting mechanism Different from the AMPDU frame aggregation, Frame bursting is a technique that's sometimes used in several link level communication protocols for shared medium to achieve
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test. An 100Mbps Ethernet connection is used to register TCP throughput of 85-90Mbps. Three host/PCs reside in an independent subnet or network from the corporate network. One is called as IxChariot client collection A, which is used to generate downlink traffic. The other is called as IxChariot client collection B, which generates uplink traffic in Wi-Fi network. The IxChariot control terminal will control the test, collect and display the results[5]. The virtual network card collection on side of AP and clients are managed separately with client-collection A and client-collection B. The third server PC is an IxChariot control terminal to measure system throughput. With HTTP test script, IxChariot client generates best effort traffic. Each thread interval is configured as 1s. Throughput and End-to-End delay are taken as measurement metrics to evaluate the performance on QoE. In the practical experiment, metric of End-to-End delay on TCP was found stable than the delay with Ping Command.
traffic between clients and AP and record channel utilization as well as average throughput. To get a general experimental result in our prototype, we defined two scenarios for test to get the results on channel utilization and average system throughput. The first scenario includes fourteen 802.11n clients with Modulation Coding Scheme(MCS) 15 and the second scenario includes mixed rate clients: six 802.11n clients with MCS 15, three 802.11n clients with MCS 7, three 802.11g clients and two 802.11b clients. The result of the HT scenario is illustrated in Fig.5 and the result of the mixed scenario is illustrated in Fig.6.
Figure 5 Test result in the HT scenario
Figure 4 Experimental network and test configuration The topology of test environment is given in Fig. 4. We set five threads, or streams, for each endpoint group, which includes a pair of downlink and uplink traffic. In other word, we have ten threads in total. For example, we set five threads from 192.168.3.100 to 192.168.3.1 and five threads inverse. The Aps/routers are configured in work mode as “server AP” and “client APs”. The 802.11n Wi-Fi prototype with Atheros 9340 chipsets can implement the measurement of channel busy fraction[6,7]. The register AR_RCCNT(0x80f4) and AR_CCCNT(0x80f8) can jointly provide us the information about “channel busy time”. AR_RCCNT provides us the number of timeslots that were sensed busy due to the clear-channel-assessment (CCA) and AR_CCCNT provides us the total number of timeslots that have passed. We extend the driver to obtain the content of the register, calculate the channel busy fraction as AR_CCCNT divided by AR_RCCNT and export the fraction to the /tmp/msg.txt. We set the application to read the value of the registers every 500ms and calculate the average fraction every 50 times.
Figure 6 Test result in the mixed scenario The Fig. 5 and Fig. 6 can show channel utilization rate and average throughput gradually increase linearly when the number of clients is less than 10. The channel utilization and average throughput reach the maximum when client number is 10 and the maximum of channel utilization is about 90%. After the number of clients reaches ten, channel utilization tends to be stabilized but the average throughput begins to decline. Therefore, it is appropriate to choose the channel utilization rate 80% as a switch threshold to frame bursting transmission , whatever in HT mode or mixed-rate mode. B. Test on access delay w/o Frame Bursting In order to know QoE performance of bursting on MAC access delay of new coming clients, the TCP End-to-End test is used instead of Ping command. This application has a server and a client. The client sends data to server through the AP, 500 data packets for each transmission. From client side, we can compute average access delay. In the practical test without bursting, we firstly record channel utilization
A. Test on throughput and channel busy time In order to monitor the change of channel busy time and throughput, we use the Chariot console to generate network
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reaches eight, channel utilization tends to be saturated with burst duration is 0 and 5100, as shown in Fig. 7. In Fig. 9, throughput goes down with the frame bursting transmission, after eight clients. The average access delay of new client would grow slowly if we set the burst duration to 5100. So we conclude that this channel utilization 80% can be used as the switch threshold for bursting transmission, when the AP throughput tends be saturated.
rate, average throughput and access delay. Then, the channel utilization rate, average throughput and access delay are recorded with bursting. The result of the channel utilization is illustrated in Fig. 7, the result comparison on the terminal access delay is shown in Fig. 8 and the result comparison on the average throughput is illustrated in Fig. 9.
V.
CONCLUSIONS
In this paper, we propose an adaptive MAC transmission method with the channel utilization rate for 802.11n Wi-Fi network. This method can improve the MAC access delay of clients in a high-density network. This means it can improve the effective number of clients, served by one AP and quality of user experience. This method actually provides a contextaware optimization with bursting transmission for the highload scenarios of Wi-Fi networks. We implement the channel utilization rate measurement on Atheros 9340 chips with two registers. The End-to-End transmission delay performance is evaluated with a TCP test script on a 802.11n compatible Laptop. We implement the proposed method on experiment platform. The results show the proposed method can improve the effective number of clients about 50% in a scenario of saturated load. The QoE on terminal access delay can also be improved in the congestion network.
Figure 7 Test result on channel utilization
ACKNOWLEDGMENT Thanks for cooperation and support provided by VoLans Technologies, Chengdu, China. REFERENCES [1]
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Figure 8 Test result on End-to-End access delay
Figure 9 Test result on average throughput In Fig. 8, the average access delay would increase suddenly without frame bursting, when the client number reaches eight. However, with frame bursting and the value of burst duration 5100, the access delay will keep a slow rate of growth after the number of clients reaches eight. Therefore, access delay of new terminals can be shortened effectively with the frame bursting in a high-load scenario. After the number of clients
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