home - projects - publications SenseWeb/SensorMap (Link) SenseWeb is a peer produced sensor network that consists of sensors deployed by contributors across the globe. It allows developing sensing applications that use the shared sensing resources and our sensor querying and tasking mechanisms. SensorMap is one such application that mashes up sensor data from SenseWeb on a map interface, and provides interactive tools to selectively query sensors and visualize data, along with authenticated access to manage sensors. EnviroMic EnviroMic is a distributed acoustic monitoring, storage and trace retrieval sensor network system geared for a prolonged interval of disconnected operation. Audio represents one of the least exploited modalities in sensor networks to date. The relatively high frequency and large size of audio traces motivate distributed algorithms for coordinating recording tasks, reducing redundancy of data stored by nearby sensors, filtering out silence, and balancing storage utilization in the network. Applications of acoustic monitoring with EnviroMic range from the study of mating rituals and social behavior of animals in the wild to audio surveillance of military targets. EnviroMic is designed for disconnected operation, where the luxury of having a basestation cannot be assumed. We implement the system on a TinyOS-based platform and systematically evaluate its performance through both indoor testbed experiments and a preliminary outdoor deployment in a nearby forest. Results demonstrate up to a 4-fold improvement in effective storage capacity of the network compared to uncoordinated recording. EnviroStore EnviroStore is a cooperative storage system for sensor networks geared for disconnected operation (where sensor nodes do not have a connected path to a basestation). The goal of the system is to maximize its data storage capacity by appropriately distributing storage utilization and opportunistically offloading data to external devices when possible. The system is motivated by the observation that a large category of sensor network applications, such as environmental data logging, does not require real-time data access. Such networks generally operate in a disconnected mode. Rather than focusing on multihop routing to a basestation, an important concern becomes (i) to maximize the effective storage capacity of the disconnected sensor network such that it accommodates the most data, and (ii) to take the best advantage of data upload opportunities when they become available to relieve network storage. The storage system described in this paper achieves the above goals, leading to significant improvements in the amount of data collected compared to non-cooperative storage. It is implemented in nesC for TinyOS and evaluated in TOSSIM through various application scenarios. The next step is to evaluate EnviroStore via a testbed consisting of 48 MicaZs. EnviroLog (Link) EnviroLog is a distributed service that improves repeatability of experimental testing of sensor networks via asynchronous recording and replay. Sensing events from dynamic environments are normally asynchronous and non-repeatable. This lack of repeatability makes it particularly difficult to statistically evaluate the performance of sensor network applications. Hence, it is essential to have the capability to capture and replay sensing events, providing a basis not only for system evaluation, but also for realistic protocol comparison and parameter tuning. To achieve that, we design and implement EnviroLog, a distributed service that improves repeatability of experimental testing of sensor networks via asynchronous event recording and replay. To use EnviroLog, an application programmer needs only to specify two types of simple annotations to the source code. Automatically, the preprocessor embeds EnviroLog into any desired level of an event-driven architecture. It records all events generated by lower layers and can replay them later to upper layers on demand. We validate the accuracy and performance of recording and replay through a set of microbenchmarks, using the latest XSM platforms. We further demonstrate the strength of EnviroLog in system tuning and performance evaluation for sensor network applications in an outdoor environment with 37 XSMs. EnviroSuite /EnviroTrack (Link) EnviroSuite (previously named as EnviroTrack) is a new distributed computing paradigm suitable for sensor network applications marked by heavy interactions with an external environment. Sensor networks open a new frontier for embedded distributed computing. Paradigms for sensor network programming in the large have been identified as a significant challenge towards developing large-scale applications. Classical programming languages are too low-level. In this project, we implemented, and experimentally evaluated EnviroSuite, a programming framework that introduces a new paradigm, called environmentally immersive programming, to abstract distributed interactions with the environment. Environmentally immersive programming refers to an object-based programming model in which individual objects represent physical elements in the external environment. It allows the programmer to think directly in terms of environmental abstractions. EnviroSuite provides language primitives for environmentally immersive programming that map transparently into a support library of distributed algorithms for tracking and environmental monitoring. We show how nesC code of realistic applications is significantly simplified using EnviroSuite, and demonstrate the resulting system performance on Mica2 and XSM platforms. VigilNet (Link) VigilNet is a large-scale (targeted for 1,000 nodes), self-organized, wireless sensor networks system for long-term (6 months) surveillance, involving detection, tracking, classification, and identification of various targets. VigilNet represents 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. In this project, we designed and implemented a complete running system (called VigilNet) for energy-efficient surveillance. VigilNet allows a group of cooperating sensor devices to detect and track the positions of moving vehicles in an energy-efficient and stealthy manner. The system consists of 40,000 lines of nesC and Java code, supporting XSM, Mica2 and Mica2dot platforms. The work is currently undergoing a technology transition to DIA.