Showing papers in "Center for Embedded Network Sensing in 2001"

Geography-informed Energy Conservation for Ad Hoc Routing

Abstract: We introduce a geographical adaptive fidelity (GAF) algorithm that reduces energy consumption in ad hoc wireless networks. GAF conserves energy by identifying nodes that are equivalent from a routing perspective and turning off unnecessary nodes, keeping a constant level of routing fidelity. GAF moderates this policy using application- and system-level information; nodes that source or sink data remain on and intermediate nodes monitor and balance energy use. GAF is independent of the underlying ad hoc routing protocol; we simulate GAF over unmodified AODV and DSR. Analysis and simulation studies of GAF show that it can consume 40% to 60% less energy than an unmodified ad hoc routing protocol. Moreover, simulations of GAF suggest that network lifetime increases proportionally to node density; in one example, a four-fold increase in node density leads to network lifetime increase for 3 to 6 times (depending on the mobility pattern). More generally, GAF is an example of adaptive fidelity, a technique proposed for extending the lifetime of self-configuring systems by exploiting redundancy to conserve energy while maintaining application fidelity.

Robust range estimation using acoustic and multimodal sensing

Abstract: Many applications of robotics and embedded sensor technology can benefit from fine-grained localization. Fine-grained localization can simplify multi-robot collaboration, enable energy efficient multi-hop routing for low-power radio networks, and enable automatic calibration of distributed sensing systems. We focus on range estimation, a critical prerequisite for fine-grained localization. While many mechanisms for range estimation exist, any individual mode of sensing can be blocked or confused by the environment. We present and analyze an acoustic ranging system that performs well in the presence of many types of interference, but can return incorrect measurements in non-line-of-sight conditions. We then suggest how evidence from an orthogonal sensory channel might be used to detect and eliminate these measurements. The work illustrates the more general research theme of combining multiple modalities to obtain robust results.

Habitat monitoring: Application driver for wireless communications technology

Abstract: As new fabrication and integration technologies reduce the cost and size of micro-sensors and wireless interfaces, it becomes feasible to deploy densely distributed wireless networks of sensors and actuators. These systems promise to revolutionize biological, earth, and environmental monitoring applications, providing data at granularities unrealizable by other means. In addition to the challenges of miniaturization, new system architectures and new network algorithms must be developed to transform the vast quantity of raw sensor data into a manageable stream of high-level data. To address this, we propose a tiered system architecture in which data collected at numerous, inexpensive sensor nodes is filtered by local processing on its way through to larger, more capable and more expensive nodes.We briefly describe Habitat monitoring as our motivating application and introduce initial system building blocks designed to support this application. The remainder of the paper presents details of our experimental platform.

Scalable Coordination for Wireless Sensor Networks: Self-Configuring Localization Systems

Abstract: Pervasive networks of micro-sensors and actuators offer to revolutionize the ways in which we understand and construct complex physical systems. Sensor networks must be scalable, long-lived and robust systems, overcoming energy limitations and a lack of pre-installed infrastructure. We explore three themes in the design of self-configuring sensor networks: tuning density to trade operational quality against lifetime; using multiple sensor modalities to obtain robust measurements; and exploiting fixed environmental characteristics. We illustrate these themes through the problem of localization, which is a key building block for sensor systems that itself requires coordination.

Dynamic Fine-Grained Localization in Ad-Hoc Wireless Sensor Networks

Abstract: The recent advances in radio and embedded system technologies have enabled the proliferation of wireless micro-sensor networks. Such wirelessly connected sensors are released in many diverse environments to perform various monitoring tasks. In many such tasks, location awareness is inherently one of the most essential system parameters. It is not only needed to report the origins of events, but also to assist group querying of sensors, routing, and to answer questions on the network coverage. In this paper we present a novel approach to the localization of sensors in an ad-hoc network. We describe a system called AHLoS (Ad-Hoc Localization System) that enables sensor nodes to discover their locations using a set distributed iterative algorithms. The operation of AHLoS is demonstrated with an accuracy of a few centimeters using our prototype testbed while scalability and performance are studied through simulation.

Evaluating Control Strategies for Wireless-Networked Robots Using an Integrated Robot and Network Simulation

Abstract: Wireless communication is an enabling factor in multiple mobile robot systems. There is significant interaction between robot controllers and communications subsystems. We present a method for evaluating combined robot control/communication strategies for a team of wireless-networked robots performing a resource transportation task. Two alternative controller designs are compared under established communication and radio propagation models. For each we measure the overall performance of the robot team including the cost of communication. The study illustrates how our evaluation tools can be used for designing controllers for robots operating in wireless communication environments.

Using Geospatial Information in Sensor Networks

Abstract: This paper describes several ways sensor networks can benefit from geospatial information and identifies two research directions. First, better models of localization error, logical location, and communications costs are required to understand the interactions between spatial information and control and communications algorithms in sensor networks. Second, wider use of spatial information in densely deployed sensor networks will move sensor networking applications from simple tracking to object counting and area monitoring, and can enable data mining techniques sensor networks to accomplish “spatial sensor mining”.

Sensor Network Tomography: Monitoring Wireless Sensor Networks

Abstract: UNIVERSITY OF SOUTHERN CALIFORNIA INFORMATION SCIENCES INSTITUTE Sensor Network Tomography: Monitoring Wireless Sensor Networks Yonggang “Jerry” Zhao (USC/ISI), Ramesh Govindan (USC/ISI) And Deborah Estrin (UCLA) Goal SNT scans provide continuous updates of overall sensor network state after deployed in unpredictable environment for … Early Warning of System Failure Discover those regions that may fail because of resource depletion. Challenges Compared to instrumentation of other distributed systems such as the Internet, continuously monitoring a wireless sensor network poses different challenges … Low User-to-Device Ratio The sheer number of sensors makes it infeasible to centrally collect detailed state from individual sensor nodes. Incremental Deployment Analogous to weather maps or radar images, a scan depicts resource availability or sensing activity within a sensor field. Provide guidance to selectively place additional sensors to “weakest regions” or “hot spots” to improve performance. Highly Distributed Data Processing Knowledge of overall state over a region is more useful than of the individual node states. Functionality Validation Evaluate overall response of the sensors to known stimulus or fine-tune detection algorithms. Limited Energy Resource High cost of communication requires carefully design to collect monitoring data. Our Approach Abstracted Representation Instead of extracting individual node state, SNT scans represent abstracted view of particular network characteristics. Example: A Residual Energy Scan consists of value range and a polygon with geographic locations of outline nodes. Value = 35~37% Coverage = In-network Aggregation Scans are constructed by aggregating small ones when being delivered within the network. Details are discarded to compensate local processing cost by saving communication cost. Example: Conditions for aggregating two residual energy scans: Values are similar and Coverages are adjacent. Errors are introduced by aggregation. Scan A V=35.5~37%) Scan B V=35~ 36% Scan A+B V=35~37% Incremental Update When scan changes, only the changed part need to be reported as an update, and it may be dropped if the change is within the error introduced by aggregation. Complementary Tools Detailed network states of a particular region can also be extracted once the user identify suspicious problems. Preliminary Results and Future Work Link Scan Display connectivity between sensor network testbed nodes Very helpful to set up preferred network topology to debug/demonstrate different wireless routing protocols. Implementation on Testbed PC/104 based wireless nodes with Radiometrix transceiver (On-going) Linux 2.2 + DirectedDiffusion-3 Residual Energy Scan Depict overall distribution of the remaining energy levels of sensor nodes. UCB mote hardware with RFM radio transceiver (Future) Tiny-OS + Tiny-diffusion Compared to extracting energy levels from individual nodes, Future Work Messaging Cost Ratio R Constructing residual energy scans by aggregation and incremental update shows better scalability and energy-efficiency characteristics. Relative Error D Network Size (N) T= 1% T= 2% T= 5% T=10% T=25% Continue to explore design space Alternative Representation and Aggregation Schemes Study the robustness of our design to network dynamics Another type of scan: Outlier Scans To Depict Abnormal Behaviors within the Network Challenge: Compute the cut-off values to identify outliers The error introduced by aggregation is acceptable. T=30% Implementation Network Size (N) Provide tools for other researchers

Fluidics-The Link between Micro and Nano Sciences and Technologies

Abstract: Microfluidics is a collection of processes for moving bulk fluid mass or controlling the paths of selected embedded particles, cells or molecules, in flows. Length scale matching between the flow and the device is the key for efficient momentum and energy transfers of the desired fluid motions. MEMS enable us to handle minute amounts of fluid in the nano or pico liter range. With properly designed microfluidic devices, molecules can be directly manipulated by the flow patterns inside the device, which provides a pathway to exploit the nano world. Obviously, understanding of the molecular effects on flows becomes a crucial issue. In traditional fluid dynamics, the flow length scale is much larger than the molecular length scale. Continuum is the most common hypothesis for flow researches. In the case of micro/nano engineering system, we are in the transition regime between continuum and molecule dominated conditions. This feature brings us the challenges when exploring the science and developing the technology in micro/nano fluidics.

A Zepto Mole DNA Micro Sensor

Abstract: Using molecular beacons (MB) as highly sensitive and selective nucleic acid probes, we eliminate two of the major but cumbersome steps, probe immobilization and washing, of gene-based biosensors. By integrating sidewall mirrors with microchannels, we can increase the signal-to-noise ratio of the optical detection. The detection specificity is achieved using a MB based DNA hybridization technique. Molecular beacons become fluorescent only upon hybridization with target DNA/RNA molecules as the quencher is separated from the fluorophore. We can hence eliminate washing and immobilization steps and establish the inchannel detection technique. This technique reduces the detection volume to 36 pL. Microchannels coated with metal films with high reflectance are used to increase the signal level in the Laser Induced Fluorescence (LIF) system. By using the side-mirror channel with inchannel sensing technique, the detection limit is 0.07 zmol which is at least 3 orders of magnitude lower than many other DNA detection schemes.