Smart Routing for WSN for the Energy Balanced Routing over Hierarchical Deployments

the data aggregation is the method of combining the data streams coming from multiple nodes. The data aggregation methods reduce the routing decision cost implied by the routers or nodes in the path. The data aggregation can be proven to be efficient in the terms of energy efficiency or transmission efficiency. The proposed model is entirely based upon the data aggregation and data forwarding technique. In this research project, we have tried to develop the new era aggregation model for the wireless sensor networks. The proposed model is intended to enhance the energy efficiency by improving the aggregation model for the sensor networks to enable the efficient delivery mechanism for the data. The WSNs are the directed graph networks, where the data is being sent into the similar direction of base transceiver station (BTS). Because the data in the directed graph networks flow in a particular direction, it always made the aggregation method efficient. The proposed model aggregation model is based upon the smart amalgamation of heuristic and greedy algorithm based aggregation. The greedy allows the algorithm to cover any number of data streams for the aggregation, whereas heuristic is responsible for the group formation before going for the aggregation. The multiple aggregation groups are produced by using the heuristic approach in the proposed model. So in this thesis, we have proposed and implemented the smart heuristic and greedy based hybrid aggregation and data transmission algorithm. The proposed model has shown its effectiveness in the case of aggregation and data transmission. The proposed model has proved its efficiency in the form of network load, route persistence, energy consumption and latency. The proposed model has proved it better than the previous approaches on the basis of the above listed performance parameters. Keywords— data aggregation, energy efficient WSN, wireless sensor network, minimum latency, route adequacy.