The focus of surveillance missions is to acquire and verify information about enemy capabilities and positions of hostile targets. Such missions often involve a high element of risk for human personnel and require a high degree of stealthiness. Hence, the ability to deploy unmanned surveillance missions, by using wireless sensor networks, is of great practical importance for the military. Because of the energy constraints of sensor devices, such systems necessitate an energy-aware design to ensure the longevity of surveillance missions. Solutions proposed recently for this type of system show promising results through simulations. However, the simplified assumptions they make about the system in the simulator often do not hold well in practice and energy consumption is narrowly accounted for within a single protocol. In this paper, we describe the design and implementation of

Abstract — The wireless sensor networks community, has now an increased understanding of the need for realistic link layer models. Recent experimental studies have shown that real deployments have a “transitional region ” with highly unreliable links, and that therefore the idealized perfect-reception-within-range models used in common network simulation tools can be very misleading. In this paper, we use mathematical techniques from communication theory to model and analyze low power wireless links. The primary contribution of this work is the identification of the causes of the transitional region, and a quantification of their influence. Specifically, we derive expressions for the packet reception rate as a function of distance, and for the width of the transitional region. These expressions incorporate important channel and radio parameters such as the path loss exponent and shadowing variance of the channel; and the modulation and encoding of the radio. A key finding is that for radios using narrow-band modulation, the transitional region is not an artifact of the radio non-ideality, as it would exist even with perfectthreshold receivers because of multi-path fading. However, we hypothesize that radios with mechanisms to combat multi-path effects, such as spread-spectrum and diversity techniques, can reduce the transitional region. I.

All analytical and simulation research on ad hoc wireless networks must necessarily model radio propagation using simplifying assumptions. A growing body of research, however, indicates that the behavior of the protocol stack may depend significantly on these underlying assumptions. The standard response to this problem is a call for more realism in designing radio models. But how much realism is enough? This study is the first to approach this question by validating simulator performance (both at the physical and application layers) with the results of real-world data. Referencing an extensive set of measurements from a large outdoor routing experiment, we start by evaluating the relative realism of common assumptions made in radio model design, identifying those which provide a reasonable approximation of reality. Although several such investigations have been made for static sensor networks, radio behavior in mobile network deployments is a much less-studied topic. We then reproduce our experimental setup in our simulator, and generate the same applicationlayer metrics under progressively smaller sets of these assumptions. By comparing the simulated outcome to the outcome of our experiment, we are able to discern at what point our balance of simplification and realism captures the real behavior of our target environment.

Z-MAC is a hybrid MAC protocol for wireless sensor networks. It combines the strengths of TDMA and CSMA while offsetting their weaknesses. Nodes are assigned time slots using a distributed implementation of RAND. Unlike TDMA where a node is allowed to transmit only during its own assigned slots, a node can transmit in both its own time slots and slots assigned to other nodes. Owners of the current time slot always have priority in accessing the channel over non-owners. Therefore, under low contention where not all owners have data to send, non-owners can “steal ” time slots from owners. This has the effect of switching between CSMA and TDMA depending on contention. Z-MAC is robust to topology changes and clock synchronization errors; in the worst case its performance falls back to that of CSMA. We implemented Z-MAC in TinyOS and evaluated its channel utilization, energy, latency and fairness over single-hop, twohop and multi-hop sensor network topologies constructed using Mica2. The result shows that Z-MAC has remarkably better data throughput than existing sensor MAC protocols while consuming comparable energy (over three times better throughput under high contention).

We present the design of the eXtreme Scale Mote, a new sensor network platform for reliably detecting and classifying, and quickly reporting, rare, random, and ephemeral events in a largescale, long-lived, and retaskable manner. This new mote was designed for the ExScal project which seeks to demonstrate a 10,000 node network capable of discriminating civilians, soldiers and vehicles, spread out over a 10km 2 area, with node lifetimes approaching 1,000 hours of continuous operation on two AA alkaline batteries. This application posed unique functional, usability, scalability, and robustness requirements which could not be met with existing hardware, and therefore motivated the design of a new platform. The detection and classification requirements are met using infrared, magnetic, and acoustic sensors. The infrared and acoustic sensors are designed for low-power continuous operation and include asynchronous processor wakeup circuitry. The usability and scalability requirements are met by minimizing the frequency and cost of human-in-the-loop operations during node deployment, activation, and verification through improvements in the user interface, packaging, and configurability of the platform. Recoverable retasking is addressed by using a grenade timer that periodically forces a system reset. The key contributions of this work are a specific design point and general design methods for building sensor network platforms to detect exceptional events. 1.

This article describes one of the major efforts in the sensor network community to build an integrated sensor network system for surveillance missions. The focus of this effort is to acquire and verify information about enemy capabilities and positions of hostile targets. Such missions often involve a high element of risk for human personnel and require a high degree of stealthiness. Hence, the ability to deploy unmanned surveillance missions, by using wireless sensor networks, is of great practical importance for the military. Because of the energy constraints of sensor devices, such systems necessitate an energy-aware design to ensure the longevity of surveillance missions. Solutions proposed recently for this type of system show promising results through simulations. However, the simplified assumptions they make about the system in the simulator often do not hold well in practice, and energy consumption is narrowly accounted for within a single protocol. In this article, we describe the design and implementation of a complete running system, called VigilNet, for energyefficient surveillance. The VigilNet allows a group of cooperating sensor devices to detect and track the positions of moving vehicles in an energy-efficient and stealthy manner. We evaluate VigilNet middleware components and integrated system extensively on a network of 70 MICA2 motes. Our results show that our surveillance strategy is adaptable and achieves a significant extension of

Extensive empirical studies presented in this paper confirm that the quality of radio communication between low power sensor devices varies significantly with time and environment. This phenomenon indicates that the previous topology control solutions, which use static transmission power, transmission range, and link quality, might not be effective in the physical world. To address this issue, online transmission power control that adapts to external changes is necessary. This paper presents ATPC, a lightweight algorithm of Adaptive Transmission Power Control for wireless sensor networks. In ATPC, each node builds a model for each of its neighbors, describing the correlation between transmission power and link quality. With this model, we employ a feedback-based transmission power control algorithm to dynamically maintain individual link quality over time. The intellectual contribution of this work lies in a novel pairwise transmission power control, which is significantly different from existing node-level or network-level power control methods. Also different from most existing simulation work, the ATPC design is guided by extensive field experiments of link quality dynamics at various locations and over a long period of time. The results from the real-world experiments demonstrate that 1) with pairwise adjustment, ATPC achieves more energy savings with a finer tuning capability and 2) with online control, ATPC is robust even with environmental changes over time.

Abstract — This paper presents a study of how empirical ranging characteristics affect multihop localization in wireless sensor networks. We use an objective metric to evaluate a well-established parametric model of ranging called Noisy Disk: if the model accurately predicts the results of a real-world deployment, it sufficiently captures ranging characteristics. When the model does not predict accurately, we systematically replace components of the model with empirical ranging characteristics to identify which components contribute to the discrepancy. We reveal that both the connectivity and noise components of Noisy Disk fail to accurately represent real-world ranging characteristics and show that these shortcomings affect localization in different ways under different circumstances. I.

Vehicular ad hoc networks (VANETs) using WLAN technology have recently received considerable attention. The evaluation of VANET routing protocols often involves simulators since management and operation of a large number of real vehicular nodes is expensive. We study the behavior of routing protocols in VANETs by using mobility information obtained from a microscopic vehicular traffic simulator that is based on the on the real road maps of Switzerland. The performance of AODV and GPSR is significantly influenced by the choice of mobility model, and we observe a significantly reduced packet delivery ratio when employing the realistic traffic simulator to control mobility of nodes. To address the performance limitations of communication protocols in VANETs, we investigate two improvements that increase the packet delivery ratio and reduce the delay until the first packet arrives. The traces used in this study are available for public download.

Recently, several studies have analyzed the statistical properties of low power wireless links in real environments, clearly demonstrating the differences between experimentally observed communication properties and widely used simulation models. However, most of these studies have not performed in depth analysis of the temporal properties of wireless links. These properties have high impact on the performance of routing algorithms. Our first goal is to study the statistical temporal properties of links in low power wireless communications. We study short term temporal issues, like lagged autocorrelation of individual links, lagged correlation of reverse links, and consecutive same path links. We also study long term temporal aspects, gaining insight on the length of time the channel needs to be measured and how often we should update our models. Our second objective is to explore how statistical temporal properties impact routing protocols. We studied one-to-one routing schemes and developed new routing algorithms that consider autocorrelation, and reverse link and consecutive same path link lagged correlations. We have developed two new routing algorithms for the cost link model: (i) a generalized Dijkstra algorithm with centralized execution, and (ii)a localized distributed probabilistic algorithm. 1