Eugene Shih

Physical layer driven protocol and algorithm design for energy-efficient wireless sensor networks

The potential for collaborative, robust networks of microsensors has attracted a great deal of research attention. For the most part, this is due to the compelling applications that will be enabled once wireless microsensor networks are in place; location-sensing, environmental sensing, medical monitoring and similar applications are all gaining interest. However, wireless microsensor networks pose numerous design challenges. For applications requiring long-term, robust sensing, such as military reconnaissance, one important challenge is to design sensor networks that have long system lifetimes. This challenge is especially difficult due to the energy-constrained nature of the devices. In order to design networks that have extremely long lifetimes, we propose a physical layer driven approach to designing protocols and algorithms. We first present a hardware model for our wireless sensor node and then introduce the design of physical layer aware protocols, algorithms, and applications that minimize energy consumption of the system. Our approach prescribes methods that can be used at all levels of the hierarchy to take advantage of the underlying hardware. We also show how to reduce energy consumption of non-ideal hardware through physical layer aware algorithms and protocols.

Low-power wireless sensor networks

Wireless distributed microsensor systems will enable fault tolerant monitoring and control of a variety of applications. Due to the large number of microsensor nodes that may be deployed and the need for long system lifetimes, replacing the battery is not an option. Sensor systems must utilize the minimal possible energy while operating over a wide range of operating scenarios. This paper presents an overview of the key technologies required for low-energy distributed microsensors. These include power aware computation/communication component technology, low-energy signaling and networking, system partitioning based on computation and communication tradeoffs, and a power aware software infrastructure.

Energy-centric enabling tecumologies for wireless sensor networks

Distributed networks of thousands of collaborating microsensors promise a maintenance-free, fault-tolerant platform for gathering rich multidimensional observations of the environment. Because a microsensor node must operate for years on a tiny battery, researchers must apply innovative system-level techniques to eliminate energy inefficiencies that would have been overlooked in the past. In this article we advocate two particular enablers for energy conservation: the ability to trade off performance for energy savings within the node; and collaborative processing among nodes to reduce the overall energy dissipated in the network. New levels of energy efficiency - attained through global system-level perspectives on node and network energy consumption - will enable a future where networks of hundreds, thousands, and eventually many millions of collaborating nodes are as commonplace as todays cellular phone.

An architecture for a power-aware distributed microsensor node

Networks of distributed microsensors are emerging as a compelling solution for a wide range of data gathering applications. Perhaps the most substantial challenge facing designers of small but long-lived microsensor nodes is the need for significant reductions in energy consumption. We propose a power-aware design methodology that emphasizes the graceful scalability of energy consumption with factors such as available resources, event frequency, and desired output quality, at all levels of the system hierarchy. Our architecture for a power-aware microsensor node highlights the collaboration between software that is capable of energy-quality tradeoffs and hardware with scalable energy consumption.

Design Considerations for Energy-Efficient Radios in Wireless Microsensor Networks

In the past few years, wireless microsensor networks have attracted a great deal of attention in the research community. This is due to the applications that will be enabled once wireless microsensor networks are in place. The design of wireless microsensor networks, however, represents a difficult challenge. Since many applications require fault-tolerant, long-term sensing, one important challenge is to design sensor networks that have long system lifetimes. Achieving long system lifetimes is difficult because sensor nodes are severely energy-constrained. In this paper, we demonstrate system-level techniques that adapt and tradeoff software and hardware parameters in response to changes in the requirements of the user, the characteristics of the underlying hardware, and the properties of the environment. By using these power-aware, system-level techniques, we are able to reduce the energy consumption of both general, adaptable systems and dedicated point systems. Moreover, given a specific set of operating conditions for a particular system, we show how energy savings of 50% can be achieved.

Energy-efficient link layer for wireless microsensor networks

Wireless microsensors are being used to form large, dense networks for the purposes of long-term environmental sensing and data collection. Unfortunately these networks are typically deployed in remote environments where energy sources are limited. Thus, designing fault-tolerant wireless microsensor networks with long system lifetimes can be challenging. By applying energy-efficient techniques at all levels of the system hierarchy, system lifetime can be extended. In this paper, energy-efficient techniques that adapt underlying communication parameters will be presented in the context of wireless microsensor networks. In particular, the effect of adapting link and physical layer parameters, such as output transmit power and error control coding, on system energy consumption will be examined.

Power-Aware Wireless Microsensor Networks

Distributed networks of thousands of collaborating microsensors promise a maintenance-free, fault-tolerant platform for gathering rich, multi-dimensional observations of the environment. As a microsensor node must operate for years on a tiny battery, careful and innovativetechniques are necessary to eliminate energy inefficiencies overlooked in the past. For instance, properties of VLSI (Very Large Scale Integration) hardware, such as leakage and the start-up time of radio electronics, must be considered for their impact on system energy, especially during long idle periods. Nodes must gracefully scale energy consumption in response to ever-varying performance demands. All levels of the communication hierarchy, from the link layer to media access to routing protocols, must be tuned for the hardware and application. Careful attention to the details of energy consumption at every point in the design process will be the key enabler for dense, robust microsensor networks that deliver maximal system lifetime in the most challenging and operationally diverse environments.