QoS Performance Improvement for WLAN Using ... - Semantic Scholar

QoS Performance Improvement for WLAN using Priority Random Early Detection Cheng-Chih Yang1,3, Jheng Sian Li2, Ruei-Yi Li1, Shang-Yo Lin1, and Jyh-Horng Wen1 1

Institute of Electrical Engineering National Chung Cheng University, Taiwan Department of Communication Engineering Chung Cheng University, Taiwan 3 Department of Electronic Engineering Nan Kai Institute of Technology, Taiwan 2

In this article, we pay attention to the qualities of service (QoS) on wireless LAN. We proposed a Priority Random Early Detection (PRED) algorithm, which integrated Random Early Detection (RED) with IEEE 802.11e EDCF so that QoS performance can be improved for WLAN. Under heavy traffic load condition, the performance of channel accessing will be inefficient due to collisions. PRED provides good differentiation among different access categories (AC). Compared with the usage of the traditional first-in-first-out (FIFO) queuing strategy with different priorities in a node, PRED supports higher throughput for high priority packets.

Keywords: RED, PRED, QoS, WLAN, FIFO.

congestion problem in packet-switched networks. RED can prevent congestion by controlling the average queue size. The strategy it adopted is dropping packets timely and ensuring that there will be always a buffer available for an incoming packet. The algorithm for RED is given in Figure 1 [7]. RED computes the average queue size avg by using exponential weighted moving average (EWMA) at each packet arrival at the queue. If the estimated avg exceeds its minimum threshold minth then the random drop of packets starts with a probability Pa that increases with avg until Pb reaches the maximum dropping threshold maxp when avg reaches its maximum threshold maxth. If avg exceeds maxth then the final drop probability Pa is set to one. The probability Pa and Pb are computed as follows:

Pb

Pa =

I. INTRODUCTION

Pb = In WLAN, the medium access control (MAC) protocol is the key element that provides the efficiency in accessing the channel, while satisfying the QoS requirements of multiple flows. IEEE 802.11 distributed WLAN have become widely deployed since the contention-based MAC protocol is simple, robust, and allowed fast installation with minimal management and maintenance costs. Although the contention-based MAC protocol fits for best effort traffic, it is unsuitable for multimedia services with QoS requirements. However, QoS is necessary for real-time applications such as web, voice or live video transmissions. Even though IEEE 802.11 has mentioned a contention-free MAC protocol, which is well suited for real-time applications, it is hardly implemented due to several reasons, such as higher complexity and inefficiency for normal best effort traffic, lack of robustness, and the strong assumption of global synchronizations [1]. Therefore, a lot of QoS researches have been proposed to improve the performance of WLAN currently, which can be categorized into three classes: 1) Traffic classification 2) Channel access and packet scheduling 3) Admission control [2]. In addition, the IEEE 802.11e standard has been completed to support QoS requirements in WLAN. The IEEE 802.11e standard aims at improving the capabilities and efficiency of the IEEE 802.11 MAC protocol by defining a mechanism to support the multiple services. The IEEE 802.11e mechanism is necessary for common users who want to use the inexpensive WLAN applications which require QoS guarantees. How to choose the optimal values of IEEE 802.11e mechanism to provide QoS requirements remains an unsolved issue [3]. The goals of MAC protocol include maintaining multiple services locally, supporting priority guarantees, gaining high throughput, and reducing delay. Current trend of this MAC protocol is comparatively suitable for IEEE 802.11e. The contention-based access mechanism is called enhanced DCF (802.11e EDCF). Random Early Detection (RED) is an algorithm that solves

(1)

(1 − count * Pb ) max p ( avg − minth )

(2)

maxth − minth

where count is the number of un-dropped packets since last dropped packet. From (2) we know that Pb varies linearly in the range [0,maxp], and Pa varies in the range [0,1]. Pa

1

maxp

0

minth

maxth

avg

Figure 1. The relationship between avg and Pa

II. THE PROPOSED ALGORITHˠЁPRED 2.1 The Structure of PRED In the proposed PRED algorithm, we make use of the concept of RED to queue packets of different priority in a node [7]. The packet which enters local queue will use IEEE 802.11e EDCF to access the channel. The structure of PRED is shown in Figure 2. The queuing method which we use is as follows. We offer corresponding minth[AC] and maxth[AC] according to each AC. The packets with higher priority have bigger minth[AC] and maxth[AC]. On the contrary, the packets with lower priority have smaller minth[AC] and maxth[AC]. Compared with the original RED, the PRED algorithm can

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support priority in a node. And then, the packet out of the local queue performs IEEE 802.11e EDCF to access the channel. By the usage of the corresponding minth[AC], maxth[AC], AIFS[AC], CWmin[AC] and CWmax[AC], PRED can support prioritized medium access for QoS requirements of WLAN. Mobile Stations AC_BK AC_BE AC_VI AC_VO

RED

802.11e EDCF

.. .

Figure 2. The structure of PRED 2.2 Adaptive Tuning of PRED The adaptive tuning method which we use is shown in Figure 3. In order to guarantee the QoS under changing traffic load, we introduce a parameter q[AC]. q[AC] is a threshold that judges whether the arriving packet can perform RED or not. If the current queue size of a node is greater than q[AC], the arriving packet will be dropped. Otherwise, the arriving packet can perform RED. The initial value of q[AC] is equal to the queue size of a node. After each collision, q[AC] is decreased as follows: q[AC] = q[AC] í tune[AC] (3)

2.3 Collision Resolution In fact, due to the nature of IEEE 802.11 EDCF and in particular due to the dynamic adjustment of q[AC], a resolution for decreasing the probability of collision is necessary. The drawback of IEEE 802.11 EDCF is that the contention window will be reset to the initial value (CWmin[AC]) after each success transmission, regardless the traffic load. This method is effective under low traffic load. But under the heavy traffic load, it is ineffective since the probability of collisions will increase and cause grave performance reduction. However, there is a mechanism, called GDCF, has solved this problem in IEEE 802.11 DCF [8]. Even so, we still need to do some adjustment in IEEE 802.11 EDCF. As we can see in the section 2.2, the packets with higher priority can still maintain the QoS requirement even under heavy traffic load condition. But the following problem is that the probability of collisions will increase since CWmax[AC] of higher priority packets is relatively small. Therefore, we need to do some revision to this problem, which is shown in Figure 4. Even CW[AC] reaches CWmax[AC], it still can be doubled after several consecutive collisions (cont_c). This method can solve the problem of colliding under heavy traffic load condition. Figure 5 shows the flowchart of PRED. The procedures for “Perform RED” and “Perform EDCF” are mentioned above.

when CW[AC] = CWmax[AC] if the number of consecutive collisions = cont_c double CW[AC] (where AC can be 2 or 3) Figure 4. The revision to EDCF

where tune[AC] is a constant value and tune[0] > tune[1] > tune[2] > tune[3]. On the contrary, if after several consecutive successful transmissions (uncollide_time), q[AC] is increased with tune[AC]: q[AC] = q[AC] + tune[AC]. Under low traffic load condition, the change of q[AC] is slight. However, under heavy traffic load condition, the gap between q[AC] will increase. Therefore the packets with lower priority will be dropped at first and the packets with higher priority can still maintain the QoS requirement even under seriously collision condition.

for each AC Initialization: q[AC] = queue_size for each packet arrival if current queue size > q[AC] drop the arriving packet else perform RED end for if collision reset uncollide_time q[AC] = q[AC] í tune[AC] else uncollide_time = uncollide_time í 1 if uncollide_time = 0 reset uncollide_time q[AC] = q[AC] + tune[AC] end if end for Figure 3. The method for adaptive tuning of PRED

Figure 5. Flowchart of PRED

III. THE OPTIMAL VALUES OF PRED We have introduced a parameter cont_c in section 2.3, but how to set this parameter is a critical issue. If cont_c is too small, the packets of higher priority will be allowed to increase their CW[AC] easily, and as a consequence they will not be able to achieve the desired QoS requirement. On the other hand, if cont_c is too large, the probability of collisions will be very high and the overall performance will be damaged. Therefore, we will simulate to search for the optimal value of cont_c.

IV.

PERFORMANCE EVALUATION

4.1 Simulation Environment

Our simulation model is built in Dedicated Short Range

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Communications (DSRC). DSRC is a block of spectrum in the 5.850 to 5.925 GHz band. It is a short to medium range communications service that supports both public safety and private operations in roadside-to-vehicle and vehicle-to-vehicle communication environments. DSRC complements cellular communications by providing very high data transfer rates while minimizing latency in the link of short range [9]. DSRC is also a part of Intelligent Transportation Systems (ITS). Compared with the existing wireless communication techniques of ITS, such as wireless AM and FM broadcaster, Global System for Mobile Communications (GSM), Global Positioning System (GPS), satellite telephone service in the 2.3GHz band, and collision avoidance radar system in the 77GHz band, DSRC can support low latency(