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Container Database Management

Container Database Management. Zheng Liu, Sheng Liu CSE 534:Advanced computer networks. Project Goals. Design and construct of a system that reduce the redundant data in container sensor network database. Design an algorithm that reduce the packets transmission of redundant data from motes.

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Container Database Management

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  1. Container Database Management Zheng Liu, Sheng Liu CSE 534:Advanced computer networks

  2. Project Goals • Design and construct of a system that reduce the redundant data in container sensor network database. • Design an algorithm that reduce the packets transmission of redundant data from motes

  3. S Motivation • Usually international shipping takes about 50 days. That is 50*24*3,600=4,320,000 seconds.

  4. Motivation • Assume that each mote sends a packet every 10 seconds. That is 432,000 packets in total. • Based on the actual data, the size of 200,000 packets is about 19MB. • So the size of the data generated by one mote in 50 days is approximately 41MB

  5. Motivation • According to our research, one ship carry up to 15000 containers. • Each container carries about 50 motes (in real world it might be more) • So the size of the database generated in the shipping procedure might be more than 30TB!

  6. 3 1 Waste of energy to transmit Unnecessary data Waste of Storage Space 2 Difficult to analysis data Problems Big Mount Of Redundant data

  7. Strategy • Assume that current temperature is Vtm, current humidity is Vhu, current light lumen is Vli. • The changing rates are Ctm, Chu, Cli • So, the data set that meets the algorithm (|Vtm Ctm|>A) || (|Vhu Chu |>B) || (|Vli Cli |)>C will be “survive”, others will be replaced by one set. • Compare the event detection rate of the database before and after the reduction take place

  8. Event simulations • Event 1 Temperature and light change (simulation of fire, sunlight) • Event 2 Only humidity changes • Event 3 Temperature and humidity change (rain, door opened, animals invasion)

  9. Results • After process with database, we achieve 87% of the data space efficiency. • Original file is 18,768KB, database size become 2,439KB after the reduction. • Events detected remain the same after the process.

  10. Future works • Experiment base on actual events • Base on the actual data, modify the programs on motes to reduce redundant transmission of unnecessary data to achieve energy efficiency.

  11. Thank you.

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