Conference Paper

Poster abstract: Enabling reliable and high-fidelity data center sensing.

DOI: 10.1145/1602165.1602213 Conference: Proceedings of the 8th International Conference on Information Processing in Sensor Networks, IPSN 2009, April 13-16, 2009, San Francisco, California, USA
Source: DBLP

ABSTRACT RACNet is a sensor network that monitors a data center's environmental conditions at high temporal and spatial resolutions. The data RACNet collects can improve the energy efficiency of data centers, currently one of the fastest growing energy consumers in the U.S. RACNet overcomes the challenge of reliable and low-latency data gathering from dense networks deployed in harsh RF environments through rDCP, a novel network protocol that decouples data collection from topology control. Furthermore, rDCP automatically partitions the network to multiple routing trees, each operating at a different frequency channel. The combination of these features enables rDCP to scale up while maintaining high data yields. Preliminary results from a production deployment of 694 sensors (including 174 wireless nodes) show that rDCP achieves a data yield of 99%, while delivering 90% of the measurements in less than 30 seconds.

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    ABSTRACT: We present Koala, a reliable data retrieval system designed to operate at permille (.1%) duty cycles, essential for long term environmental monitoring networks. Koala achieves these low duty cycles by letting the network's nodes sleep most of the time and reviving them through an efficient wake-up strategy whenever the gateway performs a bulk data download. Unlike other systems which consume energy to maintain consistent network state (e.g. routes, sleep schedules, etc.) across the network's nodes, Koala maintains no persistent routing state on the motes. Instead, a basestation calculates the network paths using reachability information collected by the motes. The flexible control protocol (FCP), a protocol we developed, is then used to install this routing information on the network's nodes. This paradigm of operation not only eliminates the overhead of maintaining routing state, but also significantly reduces the complexity of the networking code running on the motes. Results from simulation and an actual implementation on TinyOS 2 indicate that Koala can achieve very low duty cycles under a wide range of download and network sizes.
    Information Processing in Sensor Networks, 2008. IPSN '08. International Conference on; 05/2008
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    ABSTRACT: RACNet is a monitoring sensor network to provide high-fidelity visibility, in terms of spatial and temporal resolu-tion, of data center environmental conditions for energy efficiency improvement. RACNet overcomes the high node density and harsh RF environment challenges in data centers to achieve over 99% reliable data yield and short data collection latency. It does so through a novel network architecture that decouples data collection from the construction of the routing tree. This design, cou-pled with the use of different frequencies along neigh-boring data collection trees, enables RACNet to sup-port large-scale, dense networks while maintaining per-fect data reliability. Results from simulations, testbed, and real world deployments indicate that RACNet out-performs previous data collection systems, especially as node density increases.

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