We present a measurement study of a large-scale urban WiFi mesh network consisting of more than 250 Mesh Access Points (MAPs), with paying customers that use it for Internet access. Our study, involved collecting multi-modal data, e.g., through continuous gathering of SNMP logs, syslogs, passive traffic capture, and limited active measurements in different parts of the city. Our study is split into four components — planning and deployment of the mesh, success of mesh routing techniques, likely experience of users, and characterization of how the mesh is utilized. During our data collection process that spanned 8 months, the network changed many times due to hardware and software upgrades. Hence to present a consistent view of the network, the core dataset used in this paper comes from a two week excerpt of our dataset. This part of the dataset had more than 1.7 million SNMP log entries (from 224 MAPs) and more than 100 hours of active measurements. The scale of the study allowed us to make many important observations that are critical in planning and using WiFi meshes as an Internet access technology. For example, our study indicates that the last hop 2.4GHz wireless link between the mesh and the client is the major bottleneck in client performance. Further we observe that deploying the mesh access points on utility poles results in performance degradation for indoor clients that receive poor signal from the access points.

We design, implement, and evaluate a technique to identify the source network interface card (NIC) of an IEEE 802.11 frame through passive radio-frequency analysis. This technique, called PARADIS, leverages minute imperfections of transmitter hardware that are acquired at manufacture and are present even in otherwise identical NICs. These imperfections are transmitter-specific and manifest themselves as artifacts of the emitted signals. In PARADIS, we measure differentiating artifacts of individual wireless frames in the modulation domain, apply suitable machine-learning classification tools to achieve significantly higher degrees of NIC identification accuracy than prior best known schemes.

Abstract — We propose an efficient client-based approach for channel management (channel assignment and load balancing) in 802.11-based WLANs that lead to better usage of the wireless spectrum. This approach is based on a “conflict set coloring ” formulation that jointly performs load balancing along with channel assignment. Such a formulation has a number of advantages. First, it explicitly captures interference effects at clients. Next, it intrinsically exposes opportunities for better channel re-use. Finally, algorithms based on this formulation do not depend on specific physical RF models and hence can be applied efficiently to a wide-range of in-building as well as outdoor scenarios. We have performed extensive packet-level simulations and measurements on a deployed wireless testbed of 70 APs to validate the performance of our proposed algorithms. We show that in addition to single network scenarios, the conflict set coloring formulation is well suited for channel assignment where multiple wireless networks share and contend for spectrum in the same physical space. Our results over a wide range of both simulated topologies and in-building testbed experiments indicate that our approach improves application level performance at the clients by upto three times (and atleast 50%) in comparison to current best-known techniques. I.

Dynamic Host Configuration Protocol (DHCP) was defined to facilitate automatic configuration of IP addresses and other network parameters to hosts in a network. Efficiency of DHCP's address management is especially important today in part due to proliferation of mobile devices with transient network access patterns and the consequent increased demand on transient IP addresses in open-access networks. Unfortunately, DHCP's flexible design makes it susceptible to a variety of misconfigurations. The focus of this work is, therefore, to evaluate the performance and vulnerabilities of DHCP in operational networks today. To this end, we developed a tool called DHCP-Watch that facilitates DHCP-related network debugging and enables better capacity planning. We used this tool to perform a first-of-its-kind detailed measurement study of DHCP performance in operational university campus networks. Our measurements revealed various trends of IP address usage. Additionally, we discovered frequent anomalous operations due to network misconfigurations and presence of misbehaving hosts.