Wireless ad-hoc sensor networks will provide one of the missing connections between the Internet and the physical world. One of the fundamental problems in sensor networks is the calculation of coverage. Exposure is directly related to coverage in that it is a measure of how well an object, moving on an arbitrary path, can be observed by the sensor network over a period of time. In addition to the informal definition, we formally define exposure and study its properties. We have developed an efficient and effective algorithm for exposure calculation in sensor networks, specifically for finding minimal exposure paths. The minimal exposure path provides valuable information about the worst case exposure-based coverage in sensor networks. The algorithm works for any given distribution of sensors, sensor and intensity models, and characteristics of the network. It provides an unbounded level of accuracy as a function of run time and storage. We provide an extensive collection of experimental results and study the scaling behavior of exposure and the proposed algorithm for its calculation. I.

A16mm 3 autonomous solar-powered sensor node with bidirectional optical communication for distributed sensor networks has been demonstrated. The device digitizes integrated sensor signals and transmits/receives data over a free-space optical link. The system consists of three die–a 0.25µm CMOS ASIC, a 2.6 mm 2 SOI solar cell array, and a micromachined four-quadrant corner-cube retroreflector (CCR), allowing it to be used in a one-to-many network configuration. The CMOS ASIC includes a photosensor, integrated 3 MHz oscillator, 69 pJ/bit optical receiver, and 31 pJ/sample ADC.

subsystems, storage and processing resources, and in some cases actuators. The sensors in a node observe phenomena such as thermal, optic, acoustic, seismic, and acceleration events, while the processing and other components analyze the raw data and formulate answers to specific user requests. Recent advances in technology have paved the way for the design and implementation of new generations of sensor network nodes, packaged in very small and inexpensive form factors with sophisticated computation and wireless communication abilities. Although still at infancy, these new classes of sensor networks, generally referred to as wireless sensor networks (WSN), show great promise and potential with applications ranging in areas that have already been addressed, to domains never before imagined. In this article we provide an overview of this new and exciting field and a brief discussion on the factors pushing the recent flurry of sensor network related research and commercial undertakings. We also provide overview discussions on architectural design characteristics of such networks including physical components, software layers, and higher level services. At each step, we highlight special characteristics of WSNs and discuss why existing approaches and results from wireless communication networks are not necessarily suitable in WSN domains. We conclude by briefly summarizing the state of the art and the future research directions.

This paper presents our work toward the integration of a multisensor microsystem with wireless communication, using system-on-chip (SoC) methodology. Four different forms of microelectronic sensors have been fabricated on two separate 5 5mm 2 silicon chips measuring pH, conductivity, dissolved oxygen concentration, and temperature. The sensors are integrated with a sensor fusion chip comprising analog circuitry for sensor operation and signal amplification prior to digital decoding and transmission. The microsystem prototype will be packaged in a miniature capsule, which measures 16 mm 55 mm including batteries and dissipates 6.3 mW for a minimal life cycle of 12 h. Index Terms---Laboratory-on-a-chip (LoC), microsystem, multisensor array, system-on-chip (SoC), wireless communication.

Recent advances in silicon processing and microelectromechanical systems (MEMS) have made possible the production of very large numbers of very small components at very low cost in massively parallel batches. Assembly, in contrast, remains a mostly serial (i.e., nonbatch) technique. In this paper, we argue that massively parallel selfassembly of microparts will be a crucial enabling technology for future complex microsystems. As a specific approach, we present a technique for assembly of multiple batches of microparts based on capillary forces and controlled modulation of surface hydrophobicity. We derive a simplified model that gives rise to geometric algorithms for predicting assembly forces and for guiding the design optimization of selfassembling microparts. Promising initial results from theory and experiments and challenging open problems are presented to lay a foundation for general models and algorithms for selfassembly.

The performance features of MEMS transducers allow the development of a new class of small, low-power sensor microsystems which utilize a suite of sensors to support a wide range of applications. This paper presents a system-level framework for constructing such microsystems where system modularity for application adaptability is a primary design consideration. System architecture, communication protocols, modular packaging, and interface electronics are discussed in general terms, and an implementation of these concepts is presented. Key requirements for microsystem modularity, such as a communication bus and a universal microsensor interface circuit which support plug-n-play operation for online reconfiguration, are developed and presented in this paper. 1.

oscillators are demonstrated using a custom-designed single-stage zero-phase-shift sustaining amplifier together with planar-processed micromechanical resonator variants with quality factors in the thousands that differ mainly in their power-handling capacities. The resonator variants include two 40- m-long 10-MHz clamped-clamped-beam (CC-beam) resonators, one of them much wider than the other so as to allow larger power-handling capacity, and a 64- m-diameter 60-MHz disk resonator that maximizes both and power handling among the resonators tested. Tradeoffs between and power handling are seen to be most important in setting the close-to-carrier and far-from-carrier phase noise behavior of each oscillator, although such parameters as resonant frequency and motional resistance are also important. With a 10 higher power handling capability than the wide-width CC-beam resonator, a comparable series motional resistance, and a 45 higher of 48 000, the 60-MHz wine glass resonator reference oscillator exhibits a measured phase noise of 110 dBc/Hz at 1-kHz offset, and 132 dBc/Hz at far-from-carrier offsets. Dividing down to 10 MHz for fair comparison with a common conventional standard, this oscillator achieves a phase noise of 125 dBc/Hz at 1-kHz offset, and 147 dBc/Hz at far-from-carrier offsets. Index Terms—Gain control, microelectromechanical devices, microresonators, nonlinear distortion, oscillator noise, oscillators,

We combine here two well known and established concepts: Microelectromechanical systems (MEMS) and neurocomputing. First, we consider MEMS oscillators having low amplitude activity and we derive a simple mathematical model that describes nonlinear phase-locking dynamics in them. Then, we investigate a theoretical possibility of using MEMS oscillators to build an oscillatory neurocomputer having autocorrelative associative memory. The neurocomputer stores and retrieves complex oscillatory patterns in the form of synchronized states with appropriate phase relations between the oscillators. Thus, we show that MEMS alone can be used to build a sophisticated information processing system (U.S. patent is applied for). Keywords---resonators, Andronov-Hopf bifurcation, oscillatory associative memory, neural networks, smart matter I. Introduction. M ICROELECTROMECHANICAL systems (MEMS) are used to create miniature, highly accurate sensors and actuators which can gather non-electronic inform...

A Sensor Web is a system of intra-communicating spatially distributed sensor pods that can be deployed to monitor and explore new environments. By its very nature, the Sensor Web provides spatio-temporal data in a form consistent with that needed for environment modeling and represents a new paradigm for in situ monitoring and exploration. For example, a wireless web of scattered sensor pods on the Martian surface is an ideal way to pursue gaseous biosignature searches. Sensor Web climate and agricultural monitoring on Earth (particularly when coupled with remote measurements) characterize significant commercial opportunities for this technology. Recent laboratory demonstrations at the Jet Propulsion Laboratory (JPL) have shown the potential of current Sensor Web technology. These demonstrations are leading to a JPL effort to field a Sensor Web in Baja California to examine gaseous biosignatures from the microbial mats there.