This full text paper was peer reviewed at the direction of IEEE Communications Society subject matter experts for publication in the IEEE INFOCOM 2009 proceedings.
Minimizing End-to-End Delay: A Novel Routing Metric for Multi-Radio Wireless Mesh Networks Hongkun Li, Yu Cheng, Chi Zhou
Weihua Zhuang
Department of Electrical and Computer Engineering Illinois Institute of Technology {hli55, cheng, zhou}@iit.edu
Department of Electrical and Computer Engineering University of Waterloo
[email protected]
Abstract—This paper studies how to select a path with the minimum cost in terms of expected end-to-end delay (EED) in a multi-radio wireless mesh network. Different from the previous efforts, the new EED metric takes the queuing delay into account, since the end-to-end delay consists of not only the transmission delay over the wireless links but also the queuing delay in the buffer. In addition to minimizing the end-to-end delay, the EED metric implies the concept of load balancing. We develop EEDbased routing protocols for both single-channel and multi-channel wireless mesh networks. In particular for the multi-radio multichannel case, we develop a generic iterative approach to calculate a multi-radio achievable bandwidth (MRAB) for a path, taking the impacts of inter/intra-flow interference and space/channel diversity into account. The MRAB is then integrated with EED to form the metric of weighted end-to-end delay (WEED). As a byproduct of MRAB, a channel diversity coefficient can be defined to quantitatively represent the channel diversity along a given path. Both numerical analysis and simulation studies are presented to validate the performance of the routing protocol based on the EED/WEED metric, with comparison to some wellknown routing metrics.
I. I NTRODUCTION Routing in wireless mesh networks has been a hot research area in recent years, with the objective to achieve as high throughput as possible over the network. The main methodology adopted by most of the existing work is selecting path based on interference-aware or load-balancing routing metrics to reduce network-wide channel contentions. It has been revealed that the capacity of a single-radio multi-hop wireless network can not scale up with the network size, due to the co-channel interference [1]–[3]. The multi-radio multi-channel connection has been widely considered as an efficient approach to increase the wireless network capacity [8]. Design of efficient routing schemes for multi-radio multichannel wireless mesh network is much more challenging compared to the single-channel case. Many popular multimedia applications, e.g., voice over IP, IPTV, and on-line gaming, have strict delay requirement. In this paper, we aim at designing a routing metric to minimize the end-to-end delay, considering not only the transmission delay at the medium access control (MAC) layer, but also the queuing delay at the network layer. Most of the previous studies focus only on the transmission delay of the packet This work was supported in part by NSF grant CNS-0832093.
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The impact of queuing delay on path selection.
being served at the MAC layer [13], [15], while in many cases the queuing delay takes a significant portion of the total delay over a hop. The delay through a node, which has many packets in queue but short transmission time, could be larger than through the one, which has less packets in the queue but longer transmission delay. We here use an example, as illustrated in Fig. 1 to emphasize the impact of network-layer queuing delay on routing. The number annotating each link is the success probability for a transmission over the link, denoted as psuc , which means on average it takes 1/psuc transmission trails to successfully deliver a packet. The number M denotes the number of packets in the network-layer queue, waiting to be served by the MAC layer. Suppose that the bandwidth of each link is 11Mbit/s and the packet length is 1100bytes; it gives a transmission time of 0.8ms. If the queue delay is not included, routing based on the expected transmission time (ETT) would prefer the path S-XY-D (9.6ms) over the path S-A-B-C-D (11.2ms). Nevertheless, the path S-A-B-C-D would be the better one with the queuing delay taken into account. In this case, the end-to-end delay over S-X-Y-D is 97.6ms, but only 24 ms over S-A-B-C-D. In this example, the delay values ignore the backoff overhead, which will be considered in our routing metric design. The newly proposed routing metric of end-to-end delay (EED) in fact exploits the cross-layer design: each node needs to not only monitor the transmission failure probability at the MAC layer to estimate the MAC transmission delay, but also count the number of packets waiting in the networklayer buffer to estimate the queuing delay. The EED metric also implies the concept of load-balancing. The path with
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This full text paper was peer reviewed at the direction of IEEE Communications Society subject matter experts for publication in the IEEE INFOCOM 2009 proceedings.
minimum EED normally passes through the links with less packets in the queue, and thus balances the traffic off those congested links. Moreover, counting the number of packets in the buffer is a convenient implementation; most of the existing load-balancing routing schemes require the traffic information available, which is usually not easy to obtain in practice [16]. In addition to the transmission delay and queuing delay at each hop, the end-to-end delay over a multi-hop wireless network is particularly impacted by the interferences among different hops, which can be classified into inter-flow and intraflow interference [23]. In this paper, we further propose a path metric called multi-radio achievable bandwidth (MRAB) to accurately capture the impacts of inter/intra-flow interferences and space/channel diversity along a path. We consider a practical scenario that an end-to-end path may consist of both multi-radio hops and single-radio hops, where different channels do not interfere with each other but interferences exist within the same channel. We particularly develop a sub-path based iterative approach to model the complex interactions among inter-flow interference, intra-flow interference, and simultaneous transmission due to space and channel diversity. The MRAB is then integrated with EED to form the metric of weighted end-to-end delay (WEED). As a byproduct of MRAB, a channel diversity coefficient can be defined to quantitatively represent the channel diversity along a given path. We evaluate the performance of the WEED based routing protocol via numerical analysis and ns2 simulations, with comparison to some popular metrics, under both single and multiple channel cases. It is confirmed that the EED/WEED metric consistently yields better performance. The reminder of this paper is organized as follows: Section II reviews more related work. Section III derives the routing metric of EED. Section IV presents the algorithm to compute the MRAB, which captures the interaction between the inter- and intra-flow interferences. The MRAB metric is integrated with the EED metric to form the WEED metric for routing over the multi-radio mesh networks. The routing protocol is described in Section V. Section VI presents some numerical analysis and simulation studies to validate the routing performance based on the EED/WEED metric, with comparison to some well-known routing metrics. Section VII gives the concluding remarks. II. R ELATED WORK The routing metric plays a critical role in a routing protocol. The studies in [8], [16], [17] design routing metrics for loadbalancing in a multi-hop wireless network. The routing metrics however require the real-time traffic information. To exploit the space diversity, the link conflict graph is normally applied to model the interference among different hops [18], and the interference clique transmission time is proposed as a routing metric in [20]. However, the conflict graph based approaches normally induce large computation overhead in searching for the maximal independent sets or cliques, and are not suitable for dynamic distributed routing protocols. De Couto et al. propose the metric of expected transmission
count (ETX) [21] to describe the channel contention level experienced by a wireless link, which works well in a homogeneous single-radio environment. However, ETX is not capable of describing the complex scenarios in a multi-radio wireless mesh network, normally involving inter-/intra-flow interferences and different rate/intererence/topology profiles over different channels. mETX and ENT [6] are proposed to enhance ETX by considering the variable link reliability. The ETOP metric enhances ETX by incorporating the impact of link positions [5]. A bandwidth-aware routing with QoS requirement is proposed in [26]. The link metric of expected transmission time (ETT) and the associated path metric of weighted cumulative ETT (WCETT) are proposed in [13] for multi-channel mesh networks, which try to enhance the ETX by counting the heterogeneous channel rate and intra-flow interference, but the inter-flow interference is still not considered. Furthermore, when calculating the intra-flow interference, WCETT always takes all links into account and overlooks the situation that two links far away enough can transmit packets simultaneously. The metric of interference and channel switching (MIC) [15] incorporates both inter-flow and intra-flow interference, whereas it only contains the number of interfering nodes rather than the total amount of interference on these nodes for the inter-flow interference. In [25], we propose a metric of multi-hop effective bandwidth (MHEB) to compute the usable bandwidth when both inter- and intra-flow interferences are present. However, the MHEB metric just uses a simple weighted average to combine the inter- and intra- flow interferences. In this paper, the MRAB is based on MHEB, but use a more accurate approach to capture the complex interplay between the two types of interferences. III. E ND - TO -E ND D ELAY M ETRIC The end-to-end delay over a path is the summation of delays experienced by all the hops along the path. For convenience, we also use EED to denote the delay metric at each link. The meaning of EED will be clear in the context. In order to compute the EED metric over a wireless channel, each node needs to monitor the number of packets buffered at the network layer waiting for MAC layer service, as well as measuring the transmission failure probability at the MAC layer. The transmission failure probability is the probability that a MAC-layer transmission fails due to either collisions or bad channel quality. While counting the number of packets in the queue is straightforward, we will discuss how to measure the transmission failure probability over a link in Section V. The EED over a link i, say between node ni and ni+1 , consists of the queuing delay and transmission delay as EEDi = E [queuing delay + transmission delay] .
(1)
The transmission delay can also be interpreted as the packet service time, which is defined as the period from the instant that a packet begins to be serviced by the MAC layer to the instant that it is either successfully transmitted or dropped after a predefined number of retransmissions.
This full text paper was peer reviewed at the direction of IEEE Communications Society subject matter experts for publication in the IEEE INFOCOM 2009 proceedings.
Suppose that the 802.11 distributed coordination function (DCF) MAC protocol is used, each transmission or retransmission includes protocol overhead due to the binary backoff mechanism [28]. Let pi denote the transmission failure probability over link i, and assume it is stable through all the retransmissions of the packet. Also, let Ti denote the packet service time over link i, and K the maximum number of retransmissions. The average transmission delay K+1 k L k−1 I{k
