Multi-hop optimized routing algorithm and load balanced fuzzy clustering in wireless sensor networks

Now-a-days, wireless sensor node acts as a basement for a higher level industrial internet of things application. Any kind of real time IoT applications sense the data using already in-built sensors. In real time physical environment, sensors are having minimum amount of power for their operations such as sensing, communicating and processing the data. Many researches are carried out to improve the energy efficiency of sensor nodes and improves their network lifetime. More concentration is needed on clustering and routing part of the communication to go for energy saving. We have proposed an algorithm based on fuzzy and unequal clustering (FBUCA) and a three tier multi-hop optimized routing technique (TM-ORT) to improve the efficiency of the network. Energy consumption and data reliability are stabilized by QOS based multi-hop routing protocols. Whenever clustering plays a main role, load balancing among the clusters has to be important to concentrate. Load balancing has been achieved by choosing best parameters for fuzzy based clustering to select an efficient cluster head for data aggregation and routing. We have done experimental simulations and concluded the results in terms of performance metrics such as standard deviation (SD), First node Die (FND), total energy consumption (TEC) and average energy consumption (AEC).

Automated summary

The research focuses on improving the energy efficiency and network lifetime of sensor nodes, as well as enhancing network efficiency through fuzzy clustering and multi-hop routing. Emphasis is placed on clustering and routing parts of communication for energy saving. Experimental simulations show that energy consumption and data reliability can be stabilized through load balancing and optimization of parameters.