PhD students' day — CITI lab


Data Aggregation in Wireless Sensor Networks: Compressing or Forecasting? # max 140 characters

by Jin Cui

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Details

UrbaNet team
2nd year

Keywords

Data Aggregation
Temporal Series
Compressive Sensing

Advisors

Fabrice Valois


Data aggregation is a key problem in wireless sensor networks due to both energy-constrained and bandwidth-constrained.

We highlight the aggregation benefits in network layer and MAC layer by modeling the energy consumption for some energy-efficient routing protocols and MAC protocols. Besides, we define two parameters, aggregation ratio and packet size coefficient, to evaluate the efficiency of an aggregation method, and we discuss their trade-off.

Additionally, we propose comparison between A-ARMA and compressive sensing, which are on behalf of the state-of-the-art forecasting aggregation and compressing aggregation respectively.


Acknowledgements

CITI lab

INSA Lyon

Inria

HiKoB

INSA Valor

Rhône Alpes region