Rex Min

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.

A framework for energy-scalable communication in high-density wireless networks

Power-aware communication is essential for maximizing the life¿time of energy-constrained wireless devices. Applications running on such devices can cooperatively reduce communication energy by trading communication latency, reliability, or range for energy savings. We introduce a framework that exposes these high level trade-offs to a power-aware communication subsystem featuring variable-strength convolutional coding, an adjustable power ampli¿fier, and a voltage-scaled processor. An application programming interface (API) exposes an applications minimum quality con¿straints on the communication. These constraints are translated into energy-efficient parameter settings for the communication hardware. We apply our framework to improved communication energy models and measurements from a wireless microsensor node to effect over an order of magnitude of energy scalability.

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.

Dynamic voltage scaling techniques for distributed microsensor networks

Distributed microsensor networks promise a versatile and robust platform for remote environment monitoring. Crucial to long system lifetimes for these microsensors are algorithms and protocols that provide the option of trading quality for energy savings. Dynamic voltage scaling on the sensor nodes processor enables energy savings from these scalable algorithms. We demonstrate dynamic voltage scaling on the beginnings of a sensor node prototype, which currently consists of a commercial processor, a digitally adjustable DC-DC regulator, and a power-aware operating system.

Energy-efficient communication for ad-hoc wireless sensor networks

The energy dissipated by communication is a key concern in the development of networks of hundreds to thousands of distributed wireless microsensors. To evaluate the dissipation of communication energy in this unique application domain, energy models based on actual microsensor hardware are incorporated into a simulation tool designed expressly for high-density, energy-conscious wireless networks. Assessing and leveraging the energy implications of microsensor hardware and applications is crucial to achieving energy-efficient microsensor network communication.

MobiCom poster: top five myths about the energy consumption of wireless communication

A transmission lever operated switch is incorporated in the electric control circuit for an electric clutch employed in the drive of a tractor mounted mower whereby the electric circuit is deenergized whenever the transmission control lever is placed in its reverse position. The control circuit for the electric clutch includes a seat operated switch whereby the electric circuit will be deenergized whenever the seat is unoccupied. The electric circuit further includes an on-off switch which is interconnected with an ignition circuit switch for an internal combustion engine whereby when the ignition switch is closed, the on-off switch for the electric clutch circuit will be open. Thus, during starting of the engine, the mower blade drive will be inoperative due to the deenergization of the electric clutch control circuit. The electrical interlock control prevents operation of the mower blade during starting of the engine, when the operators seat is unoccupied and/or when the transmission control is in reverse.

Power-aware systems

The key to maximizing energy efficiency of systems is understanding and systematically harnessing the tremendous operational diversity they exhibit. We define the power awareness of a system as its ability to minimize energy consumption by adapting to changes in its operating point. These changes occur as a result of variations in input statistics, desired output quality, tolerable latency and throughput. The key objective of this paper is to unambiguously define the notion of power-awareness, distinguish it from the better understood concept of low-power; to propose a systematic methodology that enhances power-awareness and finally to illustrate the impact of such re-engineering. By applying power-awareness formalisms to systems ranging from multipliers to variable voltage processors, we demonstrate increases in energy efficiency of 60%-200%.

Design considerations for next generation wireless power-aware microsensor nodes

In order to break the 100 /spl mu/W average power barrier of a wireless microsensor node, aggressive design methodologies need to be developed. Dynamic voltage scaling should be more aggressive, reaching subthreshold operation, and knobs should be available for adapting hardware bit-precision and latency. Since the nodes operate in a sleep state most of the time, standby leakage currents must be reduced and the power supply voltage regulated to a near-optimum value. This paper presents insight and simulation/experimental results addressing some of the challenges of designing next generation wireless microsensor nodes.