Technological progress in integrated, low-power, CMOS communication devices and sensors makes a rich design space of networked sensors viable. They can be deeply embedded in the physical world or spread throughout our environment. The missing elements are an overall system architecture and a methodology for systematic advance. To this end, we identify key requirements, develop a small device that is representative of the class, design a tiny event-driven operating system, and show that it provides support for efficient modularity and concurrency-intensive operation. Our operating system fits in 178 bytes of memory, propagates events in the time it takes to copy 1.25 bytes of memory, context switches in the time it takes to copy 6 bytes of memory and supports two level scheduling. The analysis lays a groundwork for future architectural advances.

This paper demonstrates that it is possible to generate a reasonably accurate coordinate system on randomly distributed processors, using only local information and local communication. By coordinate system we imply that each element assigns itself a logical coordinate that maps to its global physical location, starting with no apriori knowledge of position or orientation. The algorithm presented is inspired by biological systems that use chemical gradients to determine the position of cells [12]. Extensive analysis and simulation results are presented. Two key results are: there is a critical minimum average neighborhood size of 15 for good accuracy and there is a fundamental limit on the resolution of any coordinate system determined strictly from local communication. We also demonstrate that using this algorithm, random distributions of processors produce significantly better accuracy than regular processor grids - such as those used by cellular automata. This has implications for discrete models of biology as well as for building smart sensor arrays.

We describe techniques for coordinating the actions of large numbers of small-scale robots to achieve useful large-scale results in surveillance, reconnaissance, hazard detection, and path finding. We exploit the biologically inspired notion of a "virtual pheromone," implemented using simple transceivers mounted atop each robot. Unlike the chemical markers used by insect colonies for communication and coordination, our virtual pheromones are symbolic messages tied to the robots themselves rather than to fixed locations in the environment. This enables our robot collective to become a distributed computing mesh embedded within the environment, while simultaneously acting as a physical embodiment of the user interface. This leads to notions of world-embedded computation and world-embedded displays that provide different ways to think about robot colonies and the types of distributed computations that such colonies might perform.

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Contents Preface iv 1.0 Introduction 1 1.1 Smart Dust Scenarios 2 1.1.1 Forest Fire Warning 2 1.1.2 Enemy Troop Monitoring 3 1.2 Smart Dust Capabilities 3 1.2.1 Distributed Sensor Networks and Ad-hoc Networking 4 1.2.2 High Level Interpretation of Spatial Sensor Data 4 1.2.3 Distributed Processing 5 1.2.4 COTS Dust 6 2.0 COTS Dust Architecture 7 2.1 Power 8 2.2 Computation 9 2.2.1 Static vs. Dynamic Current 11 2.2.2 Strong Thumb 11 2.3 Sensors 12 2.3.1 Magnetometer (2/3 Axis) 13 2.3.2 Accelerometers (2/3 Axis) 14 2.3.3 Light Sensor 16 2.3.4 Temperature Sensor 17 2.3.5 Pressure Sensor 17 2.3.6 Humidity Sensor 19 2.4 Communication 19 2.4.1 Acoustic Communication 20 2.4.2 RF Communication 23 2.4.3 Optical Communication 27 2.4.4 Optical Communication vs. RF Communication 32 3.0 COTS Dust Systems 35 3.1 Mouse Collars 35 3.2 Radio Frequency Mote (RF Mote) 39 3.2.1 RF Communica

Abstract. We demonstrate that it is possible to achieve robust and reasonably accurate localization in a randomly placed wireless sensor network composed of inexpensive components of limited accuracy. We present an algorithm for creating an accurate local coordinate system, aligned with the global coordinates, without the use of global control, globally accessible beacon signals, or accurate estimates of inter-sensor distances. The coordinate system is robust and automatically adapts to the failure or addition of sensors. We present a theoretical analysis of the accuracy, simulation results, and recent experimental results. Two key theoretical results are: there is a critical minimum average neighborhood size of 15 for good accuracy and there is a fundamental limit on the resolution of any coordinate system determined strictly from local communication. Simulation results show that we can achieve position accuracy to within 20 % of the local radio range even when there is variation of up to 10 % in the radio ranges. The algorithm improves with finer quantizations of inter-sensor distance estimates: with 6 levels of quantization position errors better than 10 % are achieved. Experimental results with acoustic ranging distance estimates suggest that this algorithm works acceptably on real hardware.

The fundamental constraint on a networked sensor is its energy consumption, since it may be either impossible or not feasible to replace its energy source. We analyze the power dissipation implications of implementing the network sensor with either a central processor switching between I/O devices or a family of processors, each dedicated to a single device. We present the energy measurements of the current generations of networked sensors, and develop an abstract description of tradeoffs between both designs.

In this paper, we present a programming language approach for the assembly of arbitrary twodimensional shapes by decentralized, identicallyprogrammed agents. Our system compiles a predetermined global shape into a program that instructs these agents to grow the shape via replication and location-based control mechanisms. In the globalto-local compilation phase, an input shape is decomposed into a network of covering-discs. The disc network parameterizes the agent program, a biologically-inspired framework allowing agents to amorphously produce the shape using replication and local interaction. Our system is robust to random agent failure, and regenerates in the event of region death.

An amorphous computing substrate is comprised of hundreds or thousands of individual computing nodes, each with limited resources. Amorphous computers have primarily been used for sensor fusion purposes, with nodes coordinating to aggregate, log, and act on data gathered. Although several programming models exist for these tasks, they are frequently mismatched with the problem domain, and do not scale. There are no existing languages that provide a way to reliably execute programs that far exceed the capabilities of any single computing node. We introduce a language RGLL that is both well suited to amorphous computing and scales well. We describe a hypothetical language, RSEAM, that can compile large programs not designed with amorphous computers in mind so that they can resiliently execute on amorphous computers. We describe the mechanisms of its operation, and show how they can be implemented in RGLL.