One of the purposes of network tomography is to infer the status of parameters (e.g., delay) for the links inside a network through end-to-end probing between (external) boundary nodes along predetermined routes. In this work, we apply concepts from compressed sensing and expander graphs to the delay estimation problem. We first show that a relative majority of network topologies are not expanders for existing expansion criteria. Motivated by this challenge, we then relax such criteria, enabling us to acquire simulation evidence that link delays can be estimated for 30% more networks. That is, our relaxation expands the list of identifiable networks with bounded estimation error by 30%. We conduct a simulation performance analysis of delay estimation and congestion detection on the basis of l1minimization, demonstrating that accurate estimation is feasible for an increasing proportion of networks.

Network coding (NC), in principle, is a Layer-3 innovation that improves network throughput in wired networks for multicast/broadcast scenarios. Due to the fundamental differences between wired and wireless networks, extending NC to wireless networks generates several new and significant practical challenges. Two-way information exchange (both symmetric and asymmetric) between a pair of 802.11 sources/sinks using an intermediate relay node is a canonical scenario for evaluating the effectiveness of Wireless Network Coding (WNC) in a practical setting. Our primary objective in this work is to suggest pragmatic and novel modifications at the MAC and PHY layers of the 802.11 protocol stack on a Software Radio (SORA) platform to support WNC and obtain achievable throughput estimates via lab-scale experiments. Our results show that network coding (at the MAC or PHY layer) increases system throughput-typically by 20-30%.

Data downloading on the fly is the base of commercial data services in vehicular networks, such as office-on-wheels and entertainment-on-wheels. Due to the sparse special distribution of roadside Base Stations (BS) along the road, downloading through Roadside-to-Vehicle (R2V) connections is intermittent. When multiple vehicles with geographical proximity have a common interest in certain objects to download, they can collaborate to significantly reduce their overall download time. In this paper, we investigate the application of Network Coding (NC) in collaborative downloading (CD). We focus on the R2V part of CD, and analytically derive probability distribution and the expected value of the amount of time necessary to deliver all of the information to the vehicles with and without NC. Our results show that using NC slightly improves the downloading time in addition to removing the need for having any sort of uplink communications from vehicles to the infrastructure.

New techniques in cross-layer wireless networks are building demand for ubiquitous channel sounding, that is, the capability to measure channel impulse response (CIR) with any standard wireless network and node. Towards that goal, we present a software-defined IEEE 802.11b receiver and CIR measurement system with little additional computational complexity compared to 802.11b reception alone. The system implementation, using the universal software radio peripheral (USRP) and GNU Radio, is described and compared to previous work. We validate the CIR measurement system and present the results of a measurement campaign which measures millions of CIRs between WiFi access points and a mobile receiver in urban and suburban areas.

In network tomography, we seek to infer link parameters inside a network (such as link delays) by sending end-to-end probes between (external) boundary nodes. The main challenge here is to estimate link-level attributes from end-to-end measurements. In this paper, based on the idea of combinatorial compressed sensing, we specify conditions on network routing matrix under which it is possible to estimate link delays from measurements of end-to-end delay. Moreover, we provide an upper-bound on the estimation error.

In network tomography, we seek to infer link status parameters (delay, congestion, loss rates etc.) inside a network through end-to-end measurements at (external) boundary nodes. As can be expected, such approaches generically suffer from identifiability problems; i.e., status of links in a large number of network topologies is not identifiable. We introduce an innovative approach based on linear network coding that overcomes this problem. We provide sufficient conditions on network coding coefficients and training sequence under which any logical network is guaranteed to be identifiable. In addition, we show that it is possible to locate any congested link inside a network during an arbitrary amount of time by increasing size of transmitted packets, leading to raise in complexity of the method. Further, a probability of success is provided for a random network. OPNET is used to implement the concept and confirm the validity of the claims — simulation results confirm that LNC correctly detects the congested link in situations where standard probing based algorithm fails.

Location distinction is the ability to determine when a device has changed its position. We explore the opportunity to use sophisticated PHY-layer measurements in wireless networking systems for location distinction. We first compare two existing location distinction methods - one based on channel gains of multi-tonal probes, and another on channel impulse response. Next, we combine the benefits of these two methods to develop a new link measurement that we call the complex temporal signature. We use a 2.4 GHz link measurement data set, obtained from CRAWDAD [10], to evaluate the three location distinction methods. We find that the complex temporal signature method performs significantly better compared to the existing methods. We also perform new measurements to understand and model the temporal behavior of link signatures over time. We integrate our model in our location distinction mechanism and significantly reduce the probability of false alarms due to temporal variations of link signatures.