Geology ReportsSearch

Geology topics

N. Peterson

Publications and source records attributed to N. Peterson.

3 recordsLinked to original sources

Design of smart sensing components for volcano monitoring

In a volcano monitoring application, various geophysical and geochemical sensors generate continuous high-fidelity data, and there is a compelling need for real-time raw data for volcano eruption prediction research. It requires the network to support network synchronized sampling, online configurable sensing and situation awareness, which pose significant challenges on sensing component design. Ideally, the resource usages shall be driven by the environment and node situations, and the data quality is optimized under resource constraints. In this paper, we present our smart sensing component design, including hybrid time synchronization, configurable sensing, and situation awareness. Both design details and evaluation results are presented to show their efficiency. Although the presented design is for a volcano monitoring application, its design philosophy and framework can also apply to other similar applications and platforms. ?? 2009 Elsevier B.V.

Pervasive and Mobile Computing

TinyOS-based quality of service management in wireless sensor networks

Previously the cost and extremely limited capabilities of sensors prohibited Quality of Service (QoS) implementations in wireless sensor networks. With advances in technology, sensors are becoming significantly less expensive and the increases in computational and storage capabilities are opening the door for new, sophisticated algorithms to be implemented. Newer sensor network applications require higher data rates with more stringent priority requirements. We introduce a dynamic scheduling algorithm to improve bandwidth for high priority data in sensor networks, called Tiny-DWFQ. Our Tiny-Dynamic Weighted Fair Queuing scheduling algorithm allows for dynamic QoS for prioritized communications by continually adjusting the treatment of communication packages according to their priorities and the current level of network congestion. For performance evaluation, we tested Tiny-DWFQ, Tiny-WFQ (traditional WFQ algorithm implemented in TinyOS), and FIFO queues on an Imote2-based wireless sensor network and report their throughput and packet loss. Our results show that Tiny-DWFQ performs better in all test cases. ?? 2009 IEEE.

Conference Paper