A wide variety of sensors have been incorporated into a spectrum of wireless sensor network (WSN) platforms, providing flexible sensing capability over a large number of low-power and inexpensive nodes. Traditional signal processing algorithms, however, often prove too complex for energy-and-cost-effective WSN nodes. This study explores how to design efficient sensing and classification algorithms that achieve reliable sensing performance on energy-andcost-effective hardware without special powerful nodes in a continuously changing physical environment. We present the detection and classification system in a cutting-edge surveillance sensor network, which classifies vehicles, persons, and persons carrying ferrous objects, and tracks these targets with a maximum error in velocity of 15%. Considering the demanding requirements and strict resource constraints, we design a hierarchical classification architecture that naturally distributes sensing and computation tasks at

networked system of distributed sensor nodes that detects an uncooperative agent called the evader and assists an autonomous robot called the pursuer in capturing the evader. PEG requires services such as leader election, routing, network aggregation, and closed loop control. Instead of using general purpose distributed system solutions for these services, we employ whole-system analysis and rely on spatial and physical properties to create simple and efficient mechanisms. We believe this approach advances sensor network design, yielding pragmatic solutions that leverage physical properties to simplify design of embedded distributed systems. We deployed PEG on a 400 square meter field using 100 sensor nodes, and successfully intercepted the evader in all runs. While implementing PEG, we confronted practical issues such as node breakage, packaging decisions, in situ debugging, network reprogramming, and system reconfiguration. We discuss the approaches we took to cope with these issues and share our experiences in deploying a large sensor network system. I.

In this paper, we address the problem of tracking cooperative mobile nodes in wireless sensor networks. Aiming at a resource efficient solution, we advocate the use of sensors that maintain their location information and rely on the tracking service only when their locations change. In the proposed approach, the tracked node transmits a signal and infrastructure nodes measure the Doppler shifts of the transmitted signal. We show that Mica2 motes can measure RF Doppler shifts with 0.2 Hz accuracy corresponding to a 0.14 m/s error in relative speed estimates using radio interferometric technique. The tracking problem is modeled as a non-linear optimization problem and an extended Kalman filter is used to solve it accurately assuming Gaussian measurement errors. However, this approach may fail if the tracked node changes its speed or direction. We propose to update the Kalman filter state by performing constrained least-squares optimization when a maneuver is detected. The combined approach achieves almost a 50 % accuracy improvement over the Kalman filter alone when the mobile node changes its direction and speed frequently. We describe our proof-ofconcept implementation of the tracking service and evaluate its performance experimentally and in simulation.

We argue that communication abstractions for wireless sensor networks should expose the tradeoff between accuracy and resource usage, allowing applications to adapt to changing network conditions and tune energy and bandwidth requirements. We describe abstract regions, a family of spatial operators that capture local communication within regions of the network, which may be defined in terms of radio connectivity, geographic location, or other properties of nodes. Abstract regions provide feedback on the quality of collective operations, and expose an interface for tuning resource consumption. We present the implementation of abstract regions in the TinyOS programming environment, as well as preliminary results demonstrating their use for building adaptive sensor network applications.

Location-awareness is an important requirement for many mobile wireless applications today. When GPS is not applicable because of the required precision and/or the resource constraints on the hardware platform, radio interferometric ranging may offer an alternative. In this paper, we present a technique that enables the precise tracking of multiple wireless nodes simultaneously. It relies on multiple infrastructure nodes deployed at known locations measuring the position of tracked mobile nodes using radio interferometry. In addition to location information, the approach also provides node velocity estimates by measuring the Doppler shift of the interference signal. The performance of the technique is evaluated using a prototype implementation on mote-class wireless sensor nodes. Finally, a possible application scenario of dirty bomb detection in a football stadium is briefly described.

In wireless sensor networks, sensor nodes are capable of not only measuring real world phenomena, but also storing, processing and transferring these measurements. Many techniques have been proposed for disseminating sensing data. However, most of them are not efficient in the scenarios where a huge amount of sensing data are generated, but only a small portion of them is queried. In this paper, we first propose an index-based data dissemination scheme to address the problem. With this scheme, sensing data are collected, processed and stored at the nodes close to the detecting nodes, and the location information of these storing nodes is pushed to some index nodes, which act as the rendezvous points for sinks and sources. To address the issues of fault tolerance and load balance, we extend the scheme with an adaptive ring-based index (ARI) technique, in which the index nodes for one event type form a ring surrounding the location which is determined by the event type, and the ring can be dynamically reconfigured. Considering that frequently updating or querying index nodes may cause high overhead, we also propose a lazy index updating (LIU) mechanism and a lazy index querying (LIQ) mechanism to reduce the overhead. Analysis and simulations are conducted to evaluate the performance of the proposed scheme. The results show that the proposed scheme outperforms the external storage-based scheme, the DCS scheme, and the local storage-based schemes with flood-response style. The results also show that using ARI can tolerate clustering failures and achieve load balance, and using LIU (LIQ) can further improve the system performance. 1

A wireless sensor network is constrained by computation capability, memory space, communication bandwidth, and above all, energy supply. When a critical event triggers a surge of data generated by the sensors, congestion may occur as data packets converge toward a sink. Congestion causes energy waste, throughput reduction, and information loss. However, the important problem of congestion avoidance in sensor networks is largely open. This paper proposes a congestion-avoidance scheme based on light-weight buffer management. We describe simple yet effective approaches that prevent data packets from overflowing the buffer space of the intermediate sensors. These approaches automatically adapt the sensors ’ forwarding rates to nearly optimal without causing congestion. We discuss how to implement buffer-based congestion avoidance with different MAC protocols. In particular, for CSMA with implicit ACK, our 1/k-buffer solution prevents hidden terminals from causing congestion. We demonstrate how to maintain near-optimal throughput with a small buffer at each sensor and how to achieve congestion-free load balancing when there are multiple routing paths towards multiple sinks.

We present an actor platform for wireless sensor networks (WSNs). A typical WSN may consist of hundreds to tens of thousands of tiny nodes embdedded in an environment. Hence, manual reprogramming of nodes for development, fixing bugs and updating features is an arduous process; moreover, in some cases physical access to nodes is simply out of the question. In an attempt to address this problem, network reprogramming tools such as Deluge and MNP [10, 14] have been developed. Unfortunately, these bulk reprogramming services incur significant costs in terms of energy usage, latency, and loss of sensing coverage when nodes are rebooted into a new program image. ActorNet, in contrast, provides an environment for lightweight concurrent object-oriented mobile code on WSNs. As such, actorNet enables a wide range of new dynamic applications on WSNs, including support for fully customizable queries and aggregation functions, in-network interactive debugging facilities, and high-level concurrent programming on the inherently parallel sensor network platform. Moreover, actorNet cleanly integrates all of these features into a fine-tuned, multi-threaded embedded Scheme interpreter which supports compact, maintainable programs – a significant advantage over primitive stack-based virtual machines [15, 8]. 1

Abstract — In this paper, we combine inertial sensing and sensor network technology to create a pedestrian dead reckoning system. The core of the system is a lightweight sensor-andwireless-embedded device called NavMote that is carried by a pedestrian. The NavMote gathers information about pedestrian motion from an integrated magnetic compass and accelerometers. When the NavMote comes within range of a sensor network (composed of NetMotes), it downloads the compressed data to the network. The network relays the data via a RelayMote to an information center where the data are processed into an estimate of the pedestrian trajectory based on a dead reckoning algorithm. System details including the NavMote hardware/software, sensor network middleware services, and the dead reckoning algorithm are provided. In particular, simple but effective step detection and step length estimation methods are implemented in order to reduce computation, memory, and communication requirements on the Motes. Static and dynamic calibrations of the compass data are crucial to compensate the heading errors. The dead reckoning performance is further enhanced by wireless telemetry and map matching. Extensive testing results show that satisfactory tracking performance with relatively long operational time is achieved. The paper also serves as a brief survey on pedestrian navigation systems, sensors, and techniques. Index Terms — Pedestrian navigation system, dead reckoning, wireless sensor network. I.

Abstract — Wireless sensor networks have attracted great attention in research and industrial development due to its fast-growing application potentials. New techniques must be developed for sensor networks due to their lack of infrastructure support and the constraints on computation capability, memory space, communication bandwidth, and above all, energy supply. To prolong the life time of a battery-powered sensor network, an energy efficient routing algorithm for data collection is essential. We propose a new geographic routing algorithm that forwards packets from sensors to base stations along efficient routes. The algorithm eliminates the voids that cause nonoptimal routing paths in geographic routing. It replaces the right-hand rule by distance upgrading. It is fully distributed and responds to topology changes instantly with localized operations. We formally prove the correctness of the algorithm and evaluate its performance by simulations. I.