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The use of wireless devices with accelerometers and gyroscopes to measure the movements of humans and objects is a growing area of interest. Applications range from simple activity detection to detailed full-body motion capture using networks of sensors worn on the body. A variety of algorithms have been proposed for these applications, but opportunities for accurate evaluation and comparison have...
An important performance consideration for wireless sensor networks is the amount of information collected by all the nodes in the network over the course of network lifetime. Since the objective of maximizing the sum of rates of all the nodes in the network can lead to a severe bias in rate allocation among the nodes, we advocate the use of lexicographical max-min (LMM) rate allocation. To calculate...
Base station location has significant impact on network lifetime performance for a sensor network. For a multi- hop sensor network, this problem is particular challenging as we need to jointly consider base station placement and data routing strategy to maximize network lifetime performance. This paper presents an approximation algorithm that can guarantee (1 - epsiv) optimal network lifetime performance...
Most currently deployed sensor networks use the same channel to communicate information among nodes. This is a source of great inefficiency as it poorly utilizes the available wireless spectrum. This paper takes advantage of radio capabilities of MicaZ motes that can communicate on multiple frequencies as specified in the 802.15.4 standard. We consider the case of a data collection sensor network...
The key application scenario of wireless sensor networks is data gathering: sensor nodes transmit data, possibly in a multi-hop fashion, to an information sink. The performance of sensor networks is thus characterized by the rate at which information can be aggregated to the sink. In this paper, we derive the first scaling laws describing the achievable rate in worst-case, i.e. arbitrarily deployed,...
Recent work has shown that, despite the minimal information provided by a binary proximity sensor, a network of such sensors can provide remarkably good target tracking performance. In this paper, we examine the performance of such a sensor network for tracking multiple targets. We begin with geometric arguments that address the problem of counting the number of distinct targets, given a snapshot...
This paper considers the problem of blindly calibrating sensor response using routine sensor network measurements. We show that as long as the sensors slightly oversample the signals of interest, then unknown sensor gains can be perfectly recovered. Remarkably, neither a controlled stimulus nor a dense deployment is required. We also characterize necessary and sufficient conditions for the identification...
For several tasks in sensor networks, such as localization, information fusion, or sensor scheduling, Bayesian estimation is of paramount importance. Due to the limited computational and memory resources of the nodes in a sensor network, evaluation of the prediction step of the Bayesian estimator has to be performed very efficiently. An exact and closed-form representation of the predicted probability...
Geographic routing is a useful and scalable point-to-point communication primitive for wireless sensor networks. However, previous work on geographic routing makes the unrealistic assumption that all the nodes in the network are awake during routing. This overlooks the common deployment scenario where sensor nodes are duty-cycled to save energy. In this paper we investigate several important aspects...
We consider wireless sensor networks whose nodes are randomly deployed and, thus, provide an irregular sampling of the sensed field. The field is assumed to be bandlimited; a sink node collects the data gathered by the sensors and reconstructs the field by using a technique based on linear filtering. By taking the mean square error (MSE) as performance metric, we evaluate the effect of quasi-equally...
This paper considers an estimation network of many distributed sensors with a certain correlation structure. Due to limited communication resources, the network selects only a subset of sensor measurements for estimation as long as the resulting fidelity is tolerable. We present a distributed sampling and estimation framework based on innovations diffusion, within which the sensor selection and estimation...
In this paper we propose a lightweight algorithm for constructing multi-resolution data representations for sensor networks. We compute, at each sensor node u, O(log n) aggregates about exponentially enlarging neighborhoods centered at u. The ith aggregate is the aggregated data among nodes approximately within 21 hops of u. We present a scheme, named the hierarchical spatial gossip algorithm, to...
In this paper, we present a wireless sensor platform designed for processing multipoint human motion with low latency and high resolution. One application considered here is interactive dance, in which a choreographer wishes to translate the movements of multiple dancers into real-time audio or video content to accompany the performance. This can only be accomplished using a distributed measurement...
We study the problem of aggregating data from a sparse set of nodes in a wireless sensor network. This is a common situation when a sensor network is deployed to detect relatively rare events. In such situations, each node that should participate in the aggregation knows this fact based on its own sensor readings, but there is no global knowledge in the network of where all these interesting nodes...
Energy harvesting offers a promising alternative to solve the sustainability limitations arising from battery size constraints in sensor networks. Several considerations in using an environmental energy source are fundamentally different from using batteries. Rather than a limit on the total energy, harvesting transducers impose a limit on the instantaneous power available. Further, environmental...
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