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Configuring and managing a large-scale monitoring network solving real world challenges for ultra low powered and long-range wireless mesh networks

Published: 12 October 2005 Publication History

Abstract

In creating wireless networking solutions suitable for deployment in harsh, unpredictable, and widespread environments, we were confronted with a series of problems as-yet unsolved by commercially available technologies. The purpose of this article is to describe how we addressed mission-critical customer requirements by developing a wireless technology explicitly for devices in Ultra Low Power (ULP) and Long-Range wireless mesh networks. The key end-points in our target implementation are battery-operated devices located in hard-to-reach places, but which are nonetheless expected to offer a lifespan of several years without human intervention.We provide an overview of the technical requirements for building ULP networks, with a focus on configuration and management (including patent pending self-configuration and dynamic-routing features).This is followed by a case study of an existing 25,000 node wireless network deployed for an automatic meter reading (AMR) solution, and examples of provisioning individual nodes in complex real-world networks. We also describe how transmitting information about existing network hierarchy to new nodes not only preserves overall battery life in other network nodes, but also simplifies installation efforts significantly. The technology described here is particularly applicable to metering, telemetry, remote monitoring, and large-scale data collection solutions, while straightforwardly suited for personal and property security, medical surveillance, access control, lighting systems, as well as numerous industrial sectors.With a strong background in utility metering systems, Coronis Systems provides ready-to-use wireless solutions for manufacturers, VARs, and integrators in the automatic remote metering and wireless sensor network industries.

References

[1]
Seema Bandyopadhyay and Edward J. Coyle, An Energy Efficient Hierarchical Clustering Algorithm for Wireless Sensor Networks. Purdue University, IN, USA - 2003 IEEE.
[2]
Bhaskar Krishnamachari, Yasser Mourtada, and Stephen Wicker, The Energy-Robustness Tradeoff for Routing in Wireless Sensor Networks. University of Southern California, Los Angeles, CA, USA - 2003 IEEE.
[3]
Jim Chou, Dragan Petrovic and Kannan Ramchandran, Tracking and Exploiting Correlations in Dense Sensor Networks. University of California, Berkeley, CA, USA - 2002 IEEE.
[4]
Babak Hassibi and Amir F. Dana, On the power efficiency of sensory and ad-hoc wireless networks. California Institute of Technology, Pasadena, CA, USA - 2002 IEEE.
[5]
Maggie Xiaoyan Cheng, Jianhua Sun, Manki Min and Ding-Zhu Du, Energy-efficient Broadcast and Multicast Routing in Ad Hoc Wireless Networks. University of Minnesota, USA - 2003 IEEE.
[6]
H. Nakakita, K. Yamaguchi, M. Hashimoto, T. Saito and M. Sakurai, A Study on Secure Wireless Networks Consisting of Home Aplliances. 2003 IEEE.
[7]
Chih-fan Hsin and Mingyan Liu, A Distributed Monitoring Mechanism for Wireless Sensor Networks. University of Michigan, USA, 2002.

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  • (2011)Secure Lossless Aggregation Over Fading and Shadowing Channels for Smart Grid M2M NetworksIEEE Transactions on Smart Grid10.1109/TSG.2011.21624312:4(844-864)Online publication date: Dec-2011
  1. Configuring and managing a large-scale monitoring network solving real world challenges for ultra low powered and long-range wireless mesh networks

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      cover image ACM Other conferences
      sOc-EUSAI '05: Proceedings of the 2005 joint conference on Smart objects and ambient intelligence: innovative context-aware services: usages and technologies
      October 2005
      316 pages
      ISBN:1595933042
      DOI:10.1145/1107548
      Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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      New York, NY, United States

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      Published: 12 October 2005

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      sOc-EUSAI05: Smart Objects & Ambient Intelligence
      October 12 - 14, 2005
      Grenoble, France

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      • (2011)Secure Lossless Aggregation Over Fading and Shadowing Channels for Smart Grid M2M NetworksIEEE Transactions on Smart Grid10.1109/TSG.2011.21624312:4(844-864)Online publication date: Dec-2011

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