Power-driven image compression in wireless sensor networks

Sengkyoun Jo, Muhammad Ikram, Ilgu Jung, Won Ryu, Jinsul Kim

Research output: Contribution to journalArticlepeer-review


In WSNs, wirelessly interconnected devices enable multimedia content such as video and audio streams to be ubiquitously retrieved, and still images along with scalar data from surroundings for a wide range of applications are constrained by the processing, memory, and power resources. Image compression through low-complexity and resource-efficient transforms has been addressed by several researchers to prolong the network lifetime where power conservation is achieved through sharing computational load among sensor nodes and by adjusting the transmission ranges of camera nodes. However, these schemes are not adaptive to the presence and changes in the power-level of computational sensor nodes or to the amount of computational load. We propose a resource and power efficient distributed image compression algorithm that dynamically configures the network according to the power levels, and a forwarding strategy that is based on the entropy of the image. The simulation results show that our adaptive distributed image compression scheme significantly prolongs the network lifetime and improves the network utilization efficiency, while maintaining an adequate image quality.
Original languageEnglish
Pages (from-to)28-33
Number of pages6
JournalAdvanced science and technology letters
Publication statusPublished - 2013
Externally publishedYes


  • wireless sensor networks
  • image compression
  • power efficiency
  • network lifetime


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