Geographical data collection in sensor networks with self-organizing transaction cluster-heads

Neeraj Rajgure, Eric Platon, Cristian Borcea, Shinichi Honiden

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper proposes 2G, a flexible and energy-efficient data collection protocol for sensor networks for increasing network lifetime. To this end, it integrates self-organizing data aggregation mechanisms based on geographical and cluster-based routing, and transaction cluster-head (TCH). A TCH is a location-based role, dynamically assigned to a node for the duration of handling a request-response transaction that targets its region of the network. TCH nodes collect raw sensor readings from their local regions and forward the answers containing aggregated data using geographical routing. A prototype of 2G was implemented on MICAz motes, and experimental results in realistic conditions proved that data collection reaches significantly higher delivery rates than with GEAR, the geographical routing protocol leveraged by 2G. Additionally, simulation results for larger scale networks demonstrate that 2G outperforms GEAR in terms of network lifetime.

Original languageEnglish
Title of host publication24th Annual ACM Symposium on Applied Computing, SAC 2009
Pages1214-1218
Number of pages5
DOIs
Publication statusPublished - 2009
Event24th Annual ACM Symposium on Applied Computing, SAC 2009 - Honolulu, HI, United States
Duration: 2009 Mar 82009 Mar 12

Publication series

NameProceedings of the ACM Symposium on Applied Computing

Conference

Conference24th Annual ACM Symposium on Applied Computing, SAC 2009
CountryUnited States
CityHonolulu, HI
Period09/3/809/3/12

Keywords

  • Routing protocol
  • Self-organization
  • Transaction cluster-heads
  • Wireless sensor networks

ASJC Scopus subject areas

  • Software

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  • Cite this

    Rajgure, N., Platon, E., Borcea, C., & Honiden, S. (2009). Geographical data collection in sensor networks with self-organizing transaction cluster-heads. In 24th Annual ACM Symposium on Applied Computing, SAC 2009 (pp. 1214-1218). (Proceedings of the ACM Symposium on Applied Computing). https://doi.org/10.1145/1529282.1529553