Opportunistic flooding in low-duty-cycle wireless sensor networks with unreliable links

Shuo Guo, Liang He, Yu Gu, Bo Jiang, Tian He

Research output: Contribution to journalArticlepeer-review

95 Scopus citations

Abstract

Flooding service has been investigated extensively in wireless networks to efficiently disseminate network-wide commands, configurations, and code binaries. However, little work has been done on low-duty-cycle wireless sensor networks in which nodes stay asleep most of the time and wake up asynchronously. In this type of network, a broadcasting packet is rarely received by multiple nodes simultaneously, a unique constraining feature that makes existing solutions unsuitable. In this paper, we introduce Opportunistic Flooding, a novel design tailored for low-duty-cycle networks with unreliable wireless links and predetermined working schedules. Starting with an energy-optimal tree structure, probabilistic forwarding decisions are made at each sender based on the delay distribution of next-hop receivers. Only opportunistically early packets are forwarded via links outside the tree to reduce the flooding delay and redundancy in transmission. We further propose a forwarder selection method to alleviate the hidden terminal problem and a link-quality-based backoff method to resolve simultaneous forwarding operations. We show by extensive simulations and test-bed implementations that Opportunistic Flooding is close to the optimal performance achievable by oracle flooding designs. Compared with Improved Traditional Flooding, our design achieves significantly shorter flooding delay while consuming only 20-60% of the transmission energy.

Original languageEnglish (US)
Article number6552199
Pages (from-to)2787-2802
Number of pages16
JournalIEEE Transactions on Computers
Volume63
Issue number11
DOIs
StatePublished - Nov 1 2014

Keywords

  • Wireless sensor networks
  • flooding
  • low-duty-cycle networks

Fingerprint Dive into the research topics of 'Opportunistic flooding in low-duty-cycle wireless sensor networks with unreliable links'. Together they form a unique fingerprint.

Cite this