A lightweight, self-adaptive lock gate designation scheme for data collection in long-thin wireless sensor networks

You Chiun Wang*, Che Hsi Chuang, Yu-Chee Tseng, Chien Chung Shen

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

8 Scopus citations


Constrained by the physical environments, the long-thin topology has recently been promoted for many practical deployments of wireless sensor networks (WSNs). In general, a long-thin topology is composed of a number of long branches of sensor nodes, where along a branch each sensor node has only one potential parent node toward the sink node. Although data aggregation may alleviate excessive packet contention, the maximum payload size of a packet and the dynamically changing traffic loads may severely affect the amount of sensor readings that may be collected along a long branch of sensor nodes. In addition, many practical applications of long-thin WSNs demand the exact sensor readings at each location along the deployment areas for monitoring and analysis purposes, so sensor readings may not be aggregated when they are collected. This paper proposes a lightweight, self-adaptive scheme that designates multiple collection nodes, termed lock gates, along a long-thin network to collect sensor readings sent from their respective upstream sensor nodes. The self-adaptive lock gate designation scheme balances between the responsiveness and the congestion of data collection while mitigating the funneling effect. The scheme also dynamically adapts the designation of lock gates to accommodate the time-varying sensor reading generation rates of different sensor nodes. A testbed of 100 Jennic sensor nodes is developed to demonstrate the effectiveness of the proposed lock gate designation scheme.

Original languageEnglish
Pages (from-to)47-62
Number of pages16
JournalWireless Communications and Mobile Computing
Issue number1
StatePublished - 1 Jan 2013


  • data collection
  • lock gates
  • long-thin networks
  • wireless sensor networks

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