CPAC: Energy-efficient data collection through adaptive selection of compression algorithms for sensor networks

Hyung June Lee, Hyun Seok Kim, Ik Joon Chang

Research output: Contribution to journalArticlepeer-review

4 Scopus citations

Abstract

We propose a technique to optimize the energy efficiency of data collection in sensor networks by exploiting a selective data compression. To achieve such an aim, we need to make optimal decisions regarding two aspects: (1) which sensor nodes should execute compression; and (2) which compression algorithm should be used by the selected sensor nodes. We formulate this problem into binary integer programs, which provide an energy-optimal solution under the given latency constraint. Our simulation results show that the optimization algorithm significantly reduces the overall network-wide energy consumption for data collection. In the environment having a stationary sink from stationary sensor nodes, the optimized data collection shows 47% energy savings compared to the state-of-the-art collection protocol (CTP). More importantly, we demonstrate that our optimized data collection provides the best performance in an intermittent network under high interference. In such networks, we found that the selective compression for frequent packet retransmissions saves up to 55% energy compared to the best known protocol.

Original languageEnglish
Pages (from-to)6419-6442
Number of pages24
JournalSensors (Switzerland)
Volume14
Issue number4
DOIs
StatePublished - 9 Apr 2014

Keywords

  • Data collection
  • Energy efficiency
  • Selective compression
  • Sensor networks

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