With the proliferation of location dependent applications in sensor networks, location awareness becomes an essential capability of sensor nodes. Because coarse accuracy is sufficient for most sensor network applications, solutions in range-free localization are being pursued as a cost-effective alternative to more expensive range-based approaches. In this paper, we present APIT, a novel localization algorithm that is range-free. We show that our APIT scheme performs best when an irregular radio pattern and random node placement are considered, and low communication overhead is desired. We compare our work, via extensive simulation, with three state-of-the-art range-free localization schemes to identify the preferable system configurations of each. In addition, we provide insight into the impact of localization accuracy on various location dependent applications and suggestions on improving their performance in the presence of such inaccuracy.

Distributed sensor networks are quickly gaining recognition as viable embedded computing platforms. Current techniques for programming sensor networks are cumbersome, inflexible, and low-level. We introduce EnviroTrack, an object-based distributed middleware system that raises the level of programming abstraction by providing a convenient and powerful interface to the application developer geared towards tracking the physical environment. EnviroTrack is novel in its seamless integration of objects that live in physical time and space into the computational environment of the application. Performance results demonstrate the ability of the middleware to track realistic targets.

Sensor networks, a novel paradigm in distributed wireless communication technology, have been proposed for various applications including military surveillance and environmental monitoring. These systems deploy heterogeneous collections of sensors capable of observing and reporting on various dynamic properties of their surroundings in a time sensitive manner. Such systems suffer bandwidth, energy, and throughput constraints that limit the quantity of information transferred from end-to-end. These factors coupled with unpredictable traffic patterns and dynamic network topologies make the task of designing optimal protocols for such networks difficult. Mechanisms to perform data-centric aggregation utilizing application-specific knowledge provide a means to augmenting throughput, but have limitations due to their lack of adaptation and reliance on application-specific decisions. We, therefore, propose a novel aggregation scheme that adaptively performs application-independent data aggregation in a time sensitive manner. Our work isolates aggregation decisions into a module that resides between the network and the data-link layer and does not require any modifications to the currently existing MAC and network layer protocols. We take advantage of queuing delay and the broadcast nature of wireless communication to concatenate network units into an aggregate using a novel adaptive feedback scheme to schedule the delivery of this aggregate to the MAC layer for transmission. In our evaluation we show that end-to-end transmission delay is reduced by as much as 80% under heavy traffic loads. Additionally, we show as much as a 50% reduction in transmission energy consumption with an overall reduction in header overhead. Theoretical analysis, simulation, and a test-bed implementation on Berkeley's MICA motes are provided to validate our claims.

Wireless Sensor Networks have been proposed for a multitude of location-dependent applications. For such systems, the cost and limitations of hardware on sensing nodes prevent the use of range-based localization schemes that depend on absolute point-to-point distance estimates. Because coarse accuracy is sufficient for most sensor network applications, solutions in range-free localization are being pursued as a cost-effective alternative to more expensive range-based approaches. In this paper, we present APIT, a novel localization algorithm that is range-free. We show that our APIT scheme performs best when an irregular radio pattern and random node placement are considered, and low communication overhead is desired. We compare our work via extensive simulation, with three state-of-the-art range-free localization schemes to identify the preferable system configurations of each. In addition, we study the effect of location error on routing and tracking performance. We show that routing performance and tracking accuracy are not significantly affected by localization error when the error is less than 0.4 times the communication radio radius. 1.

In this paper, we present a middleware architecture for coordination services in sensor networks that facilitates interaction between groups of sensors which monitor different environmental events. It sits on top of the native routing infrastructure and exports the abstraction of mobile communication endpoints maintained at the locations of such events. A single logical destination is created and maintained for every environmental event of interest. Such destinations are uniquely labeled and can be used for communication by application-level algorithms for coordination and sensory data management between the different event locales. For example, they may facilitate coordination, in a distributed intrusion scenario, among nodes in the vicinity of the intruders.We evaluate our middleware architecture using GloMoSim, a wireless network simulator. Our results illustrate the success of our architecture in maintaining event-related communication endpoints. We provide an analysis of how architectural and network dependent parameters affect our performance. Additionally we provide a proof of concept implementation on a real sensor network testbed (Berkeley's MICA Motes).