Brian Zill

Routing in multi-radio, multi-hop wireless mesh networks

We present a new metric for routing in multi-radio, multi-hop wireless networks. We focus on wireless networks with stationary nodes, such as community wireless networks.The goal of the metric is to choose a high-throughput path between a source and a destination. Our metric assigns weights to individual links based on the Expected Transmission Time (ETT) of a packet over the link. The ETT is a function of the loss rate and the bandwidth of the link. The individual link weights are combined into a path metric called Weighted Cumulative ETT (WCETT) that explicitly accounts for the interference among links that use the same channel. The WCETT metric is incorporated into a routing protocol that we call Multi-Radio Link-Quality Source Routing.We studied the performance of our metric by implementing it in a wireless testbed consisting of 23 nodes, each equipped with two 802.11 wireless cards. We find that in a multi-radio environment, our metric significantly outperforms previously-proposed routing metrics by making judicious use of the second radio.

Comparison of routing metrics for static multi-hop wireless networks

Routing protocols for wireless ad hoc networks have traditionally focused on finding paths with minimum hop count. However, such paths can include slow or lossy links, leading to poor throughput. A routing algorithm can select better paths by explicitly taking the quality of the wireless links into account. In this paper, we conduct a detailed, empirical evaluation of the performance of three link-quality metrics---ETX, per-hop RTT, and per-hop packet pair---and compare them against minimum hop count. We study these metrics using a DSR-based routing protocol running in a wireless testbed. We find that the ETX metric has the best performance when all nodes are stationary. We also find that the per-hop RTT and per-hop packet-pair metrics perform poorly due to self-interference. Interestingly, the hop-count metric outperforms all of the link-quality metrics in a scenario where the sender is mobile.

Estimation of link interference in static multi-hop wireless networks

We present a measurement-based study of interference among links in a static, IEEE 802.11, multi-hop wireless network. Interference is a key cause of performance degradation in such networks. To improve, or to even estimate the performance of these networks, one must have some knowledge of which links in the network interfere with one another, and to what extent. However, the problem of estimating the interference among links of a multi-hop wireless network is a challenging one. Accurate modeling of radio signal propagation is difficult since many environment and hardware-specific factors must be considered. Empirically testing every group of links is not practical: a network with n nodes can have O(n2) links, and even if we consider only pairwise interference, we may have to potentially test O(n4) pairs. Given these difficulties, much of the previous work on wireless networks has assumed that information about interference in the network is either known, or that it can be approximated using simple heuristics. We test these heuristics in our testbed and find them to be inaccurate. We then propose a simple, empirical estimation methodology that can predict pairwise interference using only O(n2) measurements. Our methodology is applicable to any wireless network that uses omni-directional antennas. The predictions made by our methodology match well with the observed pairwise interference among links in our 22 node, 802.11-based testbed.

Enhancing the security of corporate Wi-Fi networks using DAIR

We present a framework for monitoring enterprise wireless networks using desktop infrastructure. The framework is called DAIR, which is short for Dense Array of Inexpensive Radios. We demonstrate that the DAIR framework is useful for detecting rogue wireless devices (e.g., access points) attached to corporate networks, as well as for detecting Denial of Service attacks on Wi-Fi networks.Prior proposals in this area include monitoring the network via a combination of access points (APs), mobile clients, and dedicated sensor nodes. We show that a dense deployment of sensors is necessary to effectively monitor Wi-Fi networks for certain types of threats, and one can not accomplish this using access points alone. An ordinary, single-radio AP can not monitor multiple channels effectively, without adversely impacting the associated clients. Moreover, we show that a typical deployment of access points is not sufficiently dense to detect the presence of rogue wireless devices. Due to power constraints, mobile devices can provide only limited assistance in monitoring wireless networks. Deploying a dense array of dedicated sensor nodes is an expensive proposition.Our solution is based on two simple observations. First, in most enterprise environments, one finds plenty of desktop machines with good wired connectivity, and spare CPU and disk resources. Second, inexpensive USB-based wireless adapters are commonly available. By attaching these adapters to desktop machines, and dedicating the adapters to the task of monitoring the wireless network, we create a low cost management infrastructure.