Alec Woo

System architecture directions for networked sensors

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 and spread throughout our environment like smart dust. 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.

Taming the underlying challenges of reliable multihop routing in sensor networks

The dynamic and lossy nature of wireless communication poses major challenges to reliable, self-organizing multihop networks. These non-ideal characteristics are more problematic with the primitive, low-power radio transceivers found in sensor networks, and raise new issues that routing protocols must address. Link connectivity statistics should be captured dynamically through an efficient yet adaptive link estimator and routing decisions should exploit such connectivity statistics to achieve reliability. Link status and routing information must be maintained in a neighborhood table with constant space regardless of cell density. We study and evaluate link estimator, neighborhood table management, and reliable routing protocol techniques. We focus on a many-to-one, periodic data collection workload. We narrow the design space through evaluations on large-scale, high-level simulations to 50-node, in-depth empirical experiments. The most effective solution uses a simple time averaged EWMA estimator, frequency based table management, and cost-based routing.

TinyOS: An Operating System for Sensor Networks

We present TinyOS, a flexible, application-specific operating system for sensor networks, which form a core component of ambient intelligence systems. Sensor networks consist of (potentially) thousands of tiny, low-power nodes, each of which execute concurrent, reactive programs that must operate with severe memory and power constraints. The sensor network challenges of limited resources, event-centric concurrent applications, and low-power operation drive the design of TinyOS. Our solution combines flexible, fine-grain components with an execution model that supports complex yet safe concurrent operations. TinyOS meets these challenges well and has become the platform of choice for sensor network research; it is in use by over a hundred groups worldwide, and supports a broad range of applications and research topics. We provide a qualitative and quantitative evaluation of the system, showing that it supports complex, concurrent programs with very low memory requirements (many applications fit within 16KB of memory, and the core OS is 400 bytes) and efficient, low-power operation.We present our experiences with TinyOS as a platform for sensor network innovation and applications.

A transmission control scheme for media access in sensor networks

We study the problem of media access control in the novel regime of sensor networks, where unique application behavior and tight constraints in computation power, storage, energy resources, and radio technology have shaped this design space to be very different from that found in traditional mobile computing regime. Media access control in sensor networks must not only be energy efficient but should also allow fair bandwidth allocation to the infrastructure for all nodes in a multihop network. We propose an adaptive rate control mechanism aiming to support these two goals and find that such a scheme is most effective in achieving our fairness goal while being energy efficient for both low and high duty cycle of network traffic.

Exploiting the capture effect for collision detection and recovery

In this paper we evaluate a technique to detect and recover messages from packet collisions by exploiting the capture effect. It can differentiate between collisions and packet loss and can identify the nodes involved in the collisions. This information is provided at virtually no extra cost and can produce significant improvements in existing collision mediation schemes. We characterize this technique using controlled collision experiments and evaluate it in real world flooding experiments on a 36-node sensor network.

The effects of ranging noise on multihop localization: an empirical study

This paper presents a study of how empirical ranging characteristics affect multihop localization in wireless sensor networks. We use an objective metric to evaluate a well-established parametric model of ranging called Noisy Disk: if the model accurately predicts the results of a real-world deployment, it sufficiently captures ranging characteristics. When the model does not predict accurately, we systematically replace components of the model with empirical ranging characteristics to identify which components contribute to the discrepancy. We reveal that both the connectivity and noise components of Noisy Disk fail to accurately represent real-world ranging characteristics and show that these shortcomings affect localization in different ways under different circumstances.

A Network-Centric Approach to Embedded Software for Tiny Devices

The ability to incorporate low-power, wireless communication into embedded devices gives rise to a newgenre of embedded software that is distributed, dynamic, and adaptive. This paper describes the network-centric approach to designing software for highly constrained devices embodied in TinyOS. It develops a tiny Active Message communication model and shows how it is used to build non-blocking applications and higher level networking capabilities, such as multihop ad hoc routing. It shows how the TinyOS event-driven approach is used to tackle challenges in implementing the communication model with very limited storage and the radio channel modulated directly in software in an energy efficient manner. The open, component-based design allows many novel relationships between system and application.

Design and implementation of a sensor network system for vehicle tracking and autonomous interception

We describe the design and implementation of PEG, a networked system of distributed sensor nodes that detects an uncooperative agent called the evader and assists an autonomous robot called the pursuer in capturing the evader. PEG requires embedded network services such as leader election, routing, network aggregation, and closed loop control. Instead of using general purpose distributed system solutions for these services, we employ whole-system analysis and rely on spatial and physical properties to create simple and efficient mechanisms. We believe this approach advances sensor network design, yielding pragmatic solutions that leverage physical properties to simplify design of embedded distributed systems. We deployed PEG on a 400 square meter field using 100 sensor nodes, and successfully intercepted the evader in all runs. We confronted practical issues such as node breakage, packaging decisions, in situ debugging, network reprogramming, and system reconfiguration. We discuss the approaches we took to cope with these issues and share our experiences in deploying a realistic outdoor sensor network system.

Networking support for query processing in sensor networks

Networking and query processing must be co-designed to allow data self-organization for flexible but efficient in-network storage, access, and processing.

A spreadsheet approach to programming and managing sensor networks

We present a spreadsheet approach to simplifying the process of managing, programming, and interacting with sensor networks and visualizing, archiving and retrieving sensor data. An excel spreadsheet prototype has been built to demonstrate the idea. This environment provides excel users, who are already familiar with spreadsheet applications, a convenient and powerful tool for programming and data analysis. We discuss the architecture of this prototype and our experience in implementing the tool. We show two different classes of sensor-net applications built using this platform. We also present performance data on the scalability of the tool with respect to data rate and number of data streams