Abstract-In this paper, we address the following two questions concerning the capacity and configuration of fixed wireless networks: (i) given a set of wireless nodes with arbitrary but fixed locations, and a set of data flows, what is the max-min achievable throughput? and (ii) how should the network be configured to achieve the optimum? We consider these questions from a networking standpoint assuming point-to-point links, and employ a rigorous physical layer model to model conflict relationships between them. Since we seek capacity results, we assume that the network is operated using an appropriate schedule of conflict-free link activations. We develop and investigate a novel optimization framework to determine the optimal throughput and configuration, i.e., flow routes, link activation schedules and physical layer parameters. Determining the optimal throughput is a computationally hard problem, in general. However, using a smart enumerative technique we obtain numerical results for several different scenarios of interest. We obtain several important insights into the structure of the optimal routes, schedules and physical layer parameters. Besides determining the achievable throughput, we believe that our optimization-based framework can also be used as a tool, for configuring scheduled wireless networks, such as those based on IEEE 802.16.Index Terms-Capacity, fixed wireless networks, IEEE 802.16, mesh networks, optimal scheduling and routing.

Abstract-In wireless communications, the desired wireless signal is typically decoded by treating the sum of all the other ongoing signal transmissions as noise. In the networking literature, this phenomenon is typically abstracted using a wireless channel interference model. The level of detail in the interference model, evidently determines the accuracy of the results based upon the model. Several works in the networking literature have made use of simplistic interference models, e.g., fixed ranges for communication and interference, the capture threshold model (used in the ns2 network simulator), the protocol model, and so on. At the same time, fairly complex interference models such as those based on the SINR (signal-to-interference-and-noise ratio) have also been proposed and used. We investigate the impact of the choice of the interference model, on the conclusions that can be drawn regarding the performance of wireless networks, by comparing different wireless interference models. We find that both in the case of random access networks, as well as in the case of scheduled networks (where node transmissions are scheduled to be completely conflict-free), different interference models can produce significantly different results. Therefore, a lot of caution should be exercised before accepting or interpreting results based on simplified interference models. Further, we feel that an SINR-based model is the minimum level of detail that should be employed to model wireless channel interference in a networking context.

In a wireline network, nodes form links with only those nodes they are wired to, and the links do not interfere with one another. In contrast, in a wireless network, signal transmissions are intrinsically broadcast, and suffer from mutual interference. In several physical layer technologies, a wireless signal is decoded by treating the sum of all the other on-going signal transmissions as noise. Hence, from a networking standpoint, there is a need to model wireless channel interference. An accurate interference model is especially important in a multi-hop network context, since there could be several simultaneous wireless transmissions. Several works in the literature have made use of simplified interference models. Some works assume a fixed range for communication and interference, while others are based on concepts like capture threshold where the desired signal strength is compared with interference from a single node at a time, rather than cumulatively. In particular, the latter model is used in ns2 which is the most common simulation tool. Under isotropic pathloss, the capture threshold model is also equivalent to the protocol model proposed by Gupta and Kumar, which is now the subject of a lot of analytical activity notably through conflict graph based problem formulations. We investigate the accuracy and appropriateness of the capture threshold based interference model, by comparing it with one based on the SINR (signal-to-interference-and-noise ratio) with additive interference calculation. We find that both in the case of random access networks, as well as in the case of scheduled networks (where node transmissions are scheduled to be completely conflict-free), a simplified interference model such as the capture threshold model, can produce significantly different results compared to an additive interference based model. Therefore, a lot of caution should be exercised before accepting or interpreting results based on simplified interference models.

We propose an address-light, integrated MAC and routing protocol (abbreviated AIMRP) for wireless sensor networks (WSNs). Due to the broad spectrum of WSN applications, there is a need for protocol solutions optimized for specific application classes. AIMRP is proposed for WSNs deployed for detecting rare events which require prompt detection and response. AIMRP organizes the network into concentric tiers around the sink(s), and routes event reports by forwarding them from one tier to another, in the direction of (one of) the sink(s). AIMRP is address-light in that it does not employ unique per-node addressing, and integrated since the MAC control packets are also responsible for finding the next-hop node to relay the data, via an anycast query. For reducing the energy expenditure due to idle-listening, AIMRP provides a power-saving algorithm which requires absolutely no synchronization or information exchange. We evaluate AIMRP through analysis and simulations, and compare it with another MAC protocol proposed for WSNs, S-MAC. AIMRP outperforms S-MAC for event-detection applications, in terms of total average power consumption, while satisfying identical sensor-to-sink latency constraints.

Digital signatures are one of the fundamental security primitives in Vehicular Ad-Hoc Networks (VANETs) because they provide authenticity and non-repudiation in broadcast communication. However, the current broadcast authentication standard in VANETs is vulnerable to signature flooding: excessive signature verification requests that exhaust the computational resources of victims. In this paper, we propose two efficient broadcast authentication schemes, Fast Authentication (FastAuth) and Selective Authentication (SelAuth), as two countermeasures to signature flooding. FastAuth secures periodic single-hop beacon messages. By exploiting the sender's ability to predict its own future beacons, FastAuth enables 50 times faster verification than previous mechanisms using the Elliptic Curve Digital Signature Algorithm. SelAuth secures multi-hop applications in which a bogus signature may spread out quickly and impact a significant number of vehicles. SelAuth provides fast isolation of malicious senders, even under a dynamic topology, while consuming only 15%-30% of the computational resources compared to other schemes. We provide both analytical and experimental evaluations based on real traffic traces and NS-2 simulations. With the near-term deployment plans of VANET on all vehicles, our approaches can make VANETs practical.