An Efficient Routing Mechanism for Node Localization, Cluster Based Approach and Data Aggregation to Extend WSN Lifetime

Abstract

The Last decade the demand for wireless communication has increased massively. Wireless Sensor Networks (WSN) have turned out as a potential solution for various real-time applications namely environmental monitoring, health and military applications. These networks follow the random placement strategy hence, identifying the location of sensor nodes is a tedious task. Moreover, these networks suffer from various issues such as limited power resources. This work, focusses on the sensor node localization and network lifetime enhancement of Wireless Sensor Networks (WSN). In localization, security is an important issue, so a trust-based model to secure localization is investigated in this work. Further, energy aware clustering and Cluster Head (CH) selection has been undertaken to prolong the lifetime of the network. Finally, a data aggregation model which decreases the network energy depletion by discarding the redundant data is presented. The outcome of the model which is proposed has been assessed and expressed in the form of localization error, energy depletion and alive node. The comparative analysis shows that the localization error for varied anchor nodes is obtained as 1.51, 2.28, 2.52 and 1.25 using existing techniques DMA (Distance Mapping Algorithm), MDS-Map (Multidimensional Scaling), DV-Hop (Distance Vector-Hop) and Proposed Approach, respectively. Similarly, the average energy consumption is obtained as 1.02, 1.67, 1.90 and 0.82 using DMA (Distance Mapping Algorithm), MDS-Map (Multidimensional Scaling), DV-Hop (Distance Vector-Hop) and Proposed Hybrid Approach. The comparative analysis shows that proposed hybrid approach of localization, CH (Cluster Head) formation and aggregation attains better performance when compared with existing techniques in WSN(Wireless Sensor Networks).

High uncertainty aware localization and error optimization of mobile nodes for wireless sensor networks

“…However, hardware needs to make this design more complex and the transformation of this approach for mobile nodes is a very complicated process. In [33], data aggregation and clustering-based methods are presented to improve the lifetime of the network based on the node localization and routing mechanism. In [34], a grid clustering method is presented to identify sensor node locations based on the genetic algorithm.…”