Structural monitoring---the collection and analysis of structural response to ambient or forced excitation--is an important application of networked embedded sensing with significant commercial potential. The first generation of sensor networks for structural monitoring are likely to be data acquisition systems that collect data at a single node for centralized processing. In this paper, we discuss the design and evaluation of a wireless sensor network system (called Wisden) for structural data acquisition. Wisden incorporates two novel mechanisms, reliable data transport using a hybrid of end-to-end and hop-by-hop recovery, and low-overhead data time-stamping that does not require global clock synchronization. We also study the applicability of wavelet-based compression techniques to overcome the bandwidth limitations imposed by lowpower wireless radios. We describe our implementation of these mechanisms on the Mica-2 motes and evaluate the performance of our implementation. We also report experiences from deploying Wisden on a large structure.

Complex interference in static multi-hop wireless mesh networks can adversely affect transport protocol performance. Since TCP does not explicitly account for this, starvation and unfairness can result from the use of TCP over such networks. In this paper, we explore mechanisms for achieving fair and efficient congestion control for multi-hop wireless mesh networks. First, we design an AIMD-based rate-control protocol called Wireless Control Protocol (WCP) which recognizes that wireless congestion is a neighborhood phenomenon, not a node-local one, and appropriately reacts to such congestion. Second, we design a distributed rate controller that estimates the available capacity within each neighborhood, and divides this capacity to contending flows, a scheme we call Wireless Control Protocol with Capacity estimation (WCPCap). Using analysis, simulations, and real deployments, we find that our designs yield rates that are both fair and efficient, and achieve near optimal goodputs for all the topologies that we study. WCP achieves this level of performance while being extremely easy to implement. Moreover, WCPCap achieves the max-min rates for our topologies, while still being distributed and amenable to real implementation.

Abstract — Wireless sensor networks offer the potential to span and monitor large geographical areas inexpensively. Sensor network databases like TinyDB [1] are the dominant architectures to extract and manage data in such networks. Since sensors have significant power constraints (battery life), and high communication costs, design of energy efficient communication algorithms is of great importance. The data flow in a sensor database is very different from data flow in an ordinary network and poses novel challenges in designing efficient routing algorithms. In this work we explore the problem of energy efficient routing for various different types of database queries and show that in general, this problem is NP-complete. We give a constant factor approximation algorithm for one class of query, and for other queries give heuristic algorithms. We evaluate the efficiency of the proposed algorithms by simulation and demonstrate their near optimal performance for various network sizes. Index Terms — sensor networks, graph theory, mathematical programming/optimization I.

An embedded sensor network is a network of embedded computers placed in the physical world that interacts with the environment. These embedded computers, or sensor nodes, are often physically small, relatively inexpensive computers, each with some set of sensors or actuators. These sensor nodes

Wireless sensor networks have recently received a lot of attention due to a wide range of applications such as object tracking, environmental monitoring, warehouse inventory, and health care [15, 29]. In these applications, physical data is continuously collected by the sensor nodes in order to facilitate application specific processing and analysis. A database-style query interface is natural for development of applications and systems on sensor networks. There are projects pursuing this research direction [13, 14, 25]. However, these existing works have not yet explored the spatial property and the dynamic characteristics of sensor networks. In this paper, we investigate how to process a window query in highly dynamic GeoSensor networks and propose several innovative ideas on enabling techniques. The networks considered are highly dynamic because the sensor nodes can move around (by self-propelling or attaching themselves to moving objects) as well as turn to sleeping mode. There exist many research issues in executing a window query in such sensor networks. The dynamic characteristics make those issues non-trivial. A critical set of networking protocols and access methods need to be developed. In this paper, we present a location-based stateless protocol for routing a window query to its targeted area, a space-dividing algorithm for query propagation and data aggregation in the queried area, and a solution to address the user mobility issue when the query result is returned. 1.

In this paper, we present a mechanism for securing group communications in Wireless Sensor Networks (WSN). First, we derive an extension of Logical Key Hierarchy (LKH). Then we merge the extension with directed diffusion. The resulting protocol, LKHW, combines the advantages of both LKH and directed diffusion: robustness in routing, and security from the tried and tested concepts of secure multicast. In particular, LKHW enforces both backward and forward secrecy, while incurring an energy cost that scales logarithmically with the group size. This is the first security protocol that leverages directed diffusion, and we show how directed diffusion can be extended to incorporate security in an efficient manner. 1

In this paper, we introduce a Spatial Sensor Web reference model. Firstly, we present the concept of the Sensor Web and the Spatial Sensor Web. Then we use a layered conceptual model to describe the Sensor Web. Thirdly, we present the Spatial Sensor Web reference model. The reference model is composed by seven logical layers. It provides an architectural framework for constructing a Spatial Sensor Web as well as provides a way of thinking about architectural issues in terms of the applications and constraints of the Spatial Sensor Web. Lastly, we applied the seven layers to ISIES (Intelligent Sensorweb for Integrated Earth Sensing). We use the ISIES as a real-world example to illustrate the seven layers of the reference model.