Wireless Sensor Network Cost Heuristic Function using Fuzzy Logic Enhanced A* Routing Algorithm
Niha Fariya, Madhulika Sharma, Pervez Ahmad · 2019 International Conference on Smart Systems and Inventive Technology (ICSSIT) · 2019
The wireless technology has taken a big leap in recent time and in today's world, we are advancing towards the use of wireless networks. One of such network is called Wireless Sensor Network (WSN). WSN consists of small sensor nodes; these nodes can be said the backbone of the network. These sensor nodes collect the data of their surroundings and send this data to sink node where it is processed to be sent to the control station or over the internet further. A WSN consists of five main components – One or more Sensor Nodes, Central Processing Unit, Transceiver, Memory and Battery. A sensor node is static or dynamic equipment which is capable of collecting its surrounding data and send it to its neighbour nodes. While WSN comes with many advantages, it has got some constraints as it has limited memory, energy and computation capabilities. Sensor Nodes are based on battery power supply. These small batteries have some initial power which is dissipated whenever there a communication takes place. Much more communications would take place in the lifetime of the network and the battery will get exhausted eventually. Most of the times, the nodes would be placed at a difficult or hostile terrain where it would be hard to reach to recharge or replace these batteries. So the researchers need to consider preventing the battery life by developing effective routing algorithms. Recent integration of Microelectromechanical Systems (MEMS) with WS communications has highlighted the significance of WSNs as an essential reporting device but these sensors are resource constrained in terms of power supply. To enhance the network lifetime we have proposed the enhanced A* routing algorithm. We have used a Fuzzy Logic to calculate the heuristic value of a node to make it a participant node in the routing process. These parameters include packet reception rate, residual energy and node buffer state and based on these parameters the sink node evaluates the node status by fuzzy rules for the current routing schedule. If the heuristic value of the node is less than the threshold energy it does not participate in the process and network load is balanced. A three input based fuzzy logic algorithm generates the node status and this is used as cost heuristic function to determine the choice of suitable nodes to find the optimal path. By using this method the node which has less power can sustain the whole life of the network as until unless all other nodes do not reach its energy level it does not participate in the process of routing.