Resource-aware and Collaborative Communication
Introduction
There is a class of data-intensive wireless sensor network applications such as high-fidelity volcano monitoring facing the key challenge on collecting those high-resolution signals from various sensors given the fundamentally resource limited nature of sensor networks (bandwidth, power, etc.). This research is to understand low power wireless link behavior, and design resource-aware and collaborative communication protocols to fulfil critical missions with guaranteed quality of service (QoS).
The goals of this research include:
- to study low power wireless link behavior
- to study techniques for resource awareness
- to model the network as collaborative unit for realistic analysis
- to regulate communication behaviors based on resource availability and mission QoS requirement
Background
Recent advances in MEMS sensor technology as well as low-power micro-controller and radio design have enabled the development of cheap, small, low-power sensor nodes, integrating sensing, processing and wireless communication capabilities. Embedding thousands of sensors into an environment creates a digital skin or wireless network of sensors. These massively distributed sensor networks, communicate with one another and summarize the immense amounts of low-level information to produce data representative of the overall environment. Different greatly from conventional networks like data or telecommunication networks, WSNs are built of autonomous network nodes that each have limited physical bit rate, memory and energy available. The networks have to operate collaboratively in a ad-hoc fashion to reduce congestion, interference, and power consumption while prvoding high data goodput and service quality.
Publications
Wen-Zhan Song, Renjie Huang, Behrooz Shirazi, Rick LaHusen
TreeMAC: Localized TDMA MAC Protocol for High-throughput and Fairness in Sensor Networks
Seventh Annual IEEE International Conference on Pervasive Computing and Communications (IEEE PerCom 2009 accept ratio 17%)
Renjie Huang, Wen-Zhan Song, and Behrooz Shirazi
Q-MAC: Localized QoS-Aware TDMA MAC Protocol for Real-time Sensor Networks
Washington State University, Sensorweb Research Lab, Technique report WSUSRL-200901.