Data Redundancy-Control Energy-Efficient Multi-Hop Framework for Wireless Sensor Networks

Wireless Sensor Network (WSN) is an emerging technology that has attractive intelligent sensor-based applications. In these intelligent sensor-based networks, control-overhead management and elimination of redundant inner-network transmissions are still challenging because the current WSN protocols are not data redundancy-aware. The clustering architecture is an excellent choice for such challenges because it organizes control traffic, improves scalability, and reduces the network energy by reducing inner-network communication. However, the current clustering protocols periodically forward the data and consume more energy due to data redundancy. In this paper, we design a novel cluster-based redundant transmission control clustering framework that checks the redundancy of the data through the statistical tests with an appropriate degree of confidence. After that, the cluster-head separates and deletes the redundant data from the available data sets before sending it to the next level. We also designed a spatiotemporal multi-cast dynamic cluster-head role rotation that is capable of easily adjusting the non-associated cluster member nodes. Moreover, the designed framework carefully selects the forwarders based on the transmission strength and effectively eliminates the back-transmission problem. The proposed framework is compared with the recent schemes using different quality measures and we found that our proposed framework performs favorably against the existing schemes for all of the evaluation metrics.