Big Data Reduction and Optimization in Sensor Monitoring Network

Algorithm 1

Data compression based on the temporal and spatial correlation.

Temporal correlation data compression

  If 𝑅_𝑣𝑆^𝑇𝑎_𝐼,𝑆^𝑇𝑏_𝐼<𝜀

  Then record and transmit the changes

    Δ𝑆^{𝑇𝑎→𝑇𝑏}_𝐼=𝑆^𝑇𝑏_𝐼−𝑆^𝑇𝑎_𝐼

  And update the original sensing information

    𝑆^𝑇𝑏_𝐼=𝑆^𝑇𝑎_𝐼

  If 𝑅_𝑣𝑆^𝑇𝑎_𝐼,𝑆^𝑇𝑏_𝐼>𝜀 and 𝐷_𝑘(⋅)<𝜀_𝑘

  Then record the changes

    Δ𝑆^𝑇𝑎_𝐼,𝑘=𝑆^𝑇𝑏_𝐼,𝑘−𝑆^𝑇𝑎_𝐼,𝑘

  And update the original sensing information

    𝑆^𝑇𝑎_𝐼,𝑘=𝑆^𝑇𝑏_𝐼,𝑘

Spatial correlation data compression

  If 𝑅_ℎ𝑆^𝑇𝑗_𝐼,𝑆^𝑇𝑗_𝐿<𝛿

  Then record and transmit the changes

    Δ𝑆^𝑇𝑗_𝐼=𝑆^𝑇𝑗_𝐼−𝑆^𝑇𝑗_𝐿

  And update the original sensing information

    𝑆^𝑇𝑗_𝐼=𝑆^𝑇𝑗_𝐿

  If 𝑅_ℎ𝑆^𝑇𝑗_𝐼,𝑆^𝑇𝑗_𝐿>𝛿 and 𝐷_𝑘(⋅)<𝛿_𝑘

  Then record the changes

    Δ𝑆^𝑇𝑗_𝐼,𝐿=𝑆^𝑇𝑗_𝐼−𝑆^𝑇𝑗_𝐿

  And update the original sensing information

    𝑆^𝑇𝑗_𝐼,𝑘=𝑆^𝑇𝑗_𝐼,𝐿