A novel self-tuning feedback controller for active queue management supporting TCP flows
Introduction
Internet congestion occurs when the aggregated demand for a resource (e.g., channel bandwidth) exceeds the available capacity of the resource. Congestion, due to the speed mismatch between a wired network and wireless LAN (WLAN) at the access point (AP), is regarded as a critical problem that affects the overall performance of WLAN. Congestion typically results in long delays in data delivery, wasted resources due to dropped packets, and the possibility of a congestion collapse [1], [2], [46]. Congestion control is an essential technology on the Internet, which can usually be performed by two methods: (1) by an end-to-end protocol, such as TCP and (2) by an active queue management (AQM) scheme, which is implemented in routers [3], [47], [48] and employed to control traffic [4], [5]. The basic philosophy of AQM is to trigger packet dropping (or marking, when explicit congestion notification [6], [7] is enabled) before the buffer overflows, and the drop probability is proportional to the degree of congestion. AQM can achieve smaller queuing delays and higher throughput by purposely dropping packets. AQM [8], [9] can be classified into two types: (1) rate-based, which controls the flow rate at the congested channel (e.g., [1]), and (2) queue-based, which controls the queue at the congested channel (e.g., [10], [11]). There are several AQM schemes that have been reported in the recent literature for congestion control.
Random early detection (RED) [11], [12], [13], [14] recommended for deployment by the Internet Engineering Task Force (IETF), is the most prominent and well-studied AQM scheme [15], [16]. It is based on queue management, and has been widely implemented in routers for congestion control on the Internet. The main objective of RED is to keep the average queue length (average buffer occupancy) low. To accomplish this target, RED randomly drops incoming packets with a probability proportional to the average queue length, which makes the RED scheme suitable for irregular bursts of traffic. One important factor in measuring the performance of a traffic controller is stability: the stability of packet drop rate and the stability of queue length. A drawback of the RED method is that it is difficult to set the parameters of the RED traffic controller to stabilize the system under the diversity of Internet traffic [17], [18]. The problem becomes especially severe when the average queue length reaches a certain threshold, which may result in a sharp decrease of throughput and an increase of the drop rate [3].
There are several variants of RED that have been proposed to address the above problem, such as Adaptive-RED [10], [19], [20], Proportional Derivative RED controller (PD-RED) [3], Proportional Integral controller (PI-RED) [21], [22], and so on. With RED [11], [12], [13], [14], the resulting average queue length is very sensitive to the level of congestion and initial parameter settings, which makes its behavior unpredictable [21]. Adaptive-RED attempts to stabilize router queue length at a level independent of the active connections, by using an exponentially weighted moving average as an integral controller [10], [19], [20]. Sun et al. proposed a new RED scheme [3] based on the proportional derivative control theory, called PD-RED, to improve the performance of the AQM. Unfortunately, neither Adaptive-RED nor PD-RED provides any systematic method to configure the RED parameters. Moreover, the control gain selection in both methods is based only on empirical observation and simulation analysis, which can only work well in certain given situation. A theoretical model and analysis for control gain selection and parameter setting are required. Holot et al. [21] proposed a Proportional Integral controller, PI-RED, as a means to improve the responsiveness of the TCP/AQM dynamic, and stabilize the router queue length around the target value. Similarly, Deng et al. [23] proposed a Proportional Integral Derivative model, to improve system stability under dynamic traffic conditions. Both methods used feedback control theory to describe and analyze the TCP/RED dynamic. However, the use of a highly simplified linear quadratic Gaussian controller [24] limited their discussion to the classical control elements. Consequently, their methods can only directly channel traffic control parameters to one of the AQM objectives, which leads to poor global performance. Xiong et al. proposed a Self-tuning Proportional and Integral RED (SPI-RED) [25] on average queue length, to regulate queue length. The average queue scheme keeps the average queue length low, but still allows occasional bursts of packets in the queue. In contrast, this paper proposes a novel proportional and differential control based on instantaneous queue length, called NPD-RED, which effectively avoids the problem of occasional bursts of packets.
Wireless access points act as bridges between wireless and wired networks. Since the actually available bandwidth in wireless networks is much smaller than that in wired networks, there is a bandwidth disparity in channel capacity which makes the access point a significant network congestion point. Only a handful of research papers have explored the AQM issues in WLAN. In [26], Xu et al. presented an AQM scheme for WLAN, but the performance analysis of the proposed AQM scheme was limited, because the authors only considered the delay from wired network to WLAN. On the other hand, throughput and average queue length are generally accepted as more important metrics in evaluating an AQM performance. In [27], Pang et al. mainly focused on the comparative analysis of different versions of TCPs, particularly TCP Veno [28] and TCP Reno under RED and Tail-Drop (TD) Queue. This study concluded that RED does not help in throughput in WLAN. However, it lacks the detailed analysis about the reason why RED can result in the performance degradation [29].
The main contributions of this paper are as follows. First, we propose a novel feedback control scheme, called NPD-RED, for the TCP/RED dynamic time-delayed model in wired network and wired–wireless network routers (refer to [13], [30]). The core idea is new probability function for packet dropping. At the packet level, NPD-RED uses the changes in the instantaneous queue and the differential in queue length to update packet drop probability upon the arrival of new packets. On larger time-scales, NPD-RED dynamically adjusts the packet drop probability using the measured packet loss ratio. Second, we provide a theoretical analysis of the stability of the proposed probability function, and give theoretical guidance in determining the parameters for the proposed NPD-RED method. Our theoretical analysis is based on a TCP dynamic model, and uses optimal control methodologies. Furthermore, in the proposed NPD-RED method, these key parameters are decoupled from other tuning parameters, as well as from the parameters related to network conditions. The controlled parameters are adapted within dynamically changing ranges, which are determined by the stability condition. This makes the system analysis more realistic, and we propose this new configuration of NPD-RED to enhance the network performance. Finally, we conduct extensive simulations to compare the performance of our proposed method with other existing schemes. The simulation results demonstrated that the NPD-RED algorithm outperforms the existing schemes (RED, PI-RED, Adaptive-RED, and PD-RED).
The remainder of the paper is organized as follows. In Section 2, we present the system model and definitions. Section 3 discusses the NPD-RED algorithm, and develops guidelines based on theoretical analysis for choosing the parameters to achieve system stability. In Section 4, we carry out simulations under a variety of network scenarios, and analyze the performance of the proposed method. Section 5 explains more work related with AQM. Finally, we make conclusions and discuss future work in Section 6.
Section snippets
The system model and definitions
In this study, our objective is to develop an active queue management system to improve the stability of bottleneck queue in a TCP network.
In [4], a dynamic model of TCP behavior was developed, adopting fluid-flow and stochastic differential equation analysis. Simulation results demonstrated that this model accurately captured the dynamic of TCP. Following this work, a packet dropping scheme was proposed for active queue management for Internet routers in [4]. We follow the model introduced in
The NPD-RED algorithm
In this section, we present a novel packet dropping algorithm called NPD-RED, and also give a theoretical analysis and algorithm for choosing the proportional and differential parameters to achieve system stability.
Performance evaluation
In this section, we evaluate the performance of the proposed NPD-RED packet dropping algorithm through a number of simulations performed using NS2 [38].
The network topology used in the simulation is shown in Fig. 1. It is a simple dumbbell topology based on a single common bottleneck channel of 3 Mb/s capacity with identical, long-lived and saturated TCP/Reno flows. In other words, the TCP connections are modeled as greedy FTP connections, which always have data to send as long as their
Related work
In addition to the work cited in Section 1, there have been some other alternate mechanisms for AQM. For example, the Stabilized Random Early Drop (S-RED) protocol [35], [39] uses adaptive methods to adjust the max drop probability , depending on three events: buffer overflow, empty buffer and queue length increase. However, this approach introduces additional parameters that need to be configured [40].
BLUE [41] is another type of adaptive scheme. It adaptively computes packet drop
Conclusion and future work
Wireless access points act as bridges between wireless and wired networks. Since the actually available bandwidth in wireless networks is much smaller than that in wired networks, there is a bandwidth disparity between the wired and the wireless interface of an access point, which makes the access point a significant network congestion point. The recently proposed AQM is an effective method used in wired network and wired–wireless network routers for congestion control.
In this paper, we
Acknowledgments
This research has been supported by the US National Science Foundation CAREER Award under Grant No. CCF-0545667. C.-X. Wang acknowledges the support from the Scottish Funding Council for the Joint Research Institute in Signal and Image Processing with the University of Edinburgh, as part of the Edinburgh Research Partnership in Engineering and Mathematics.
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