WirelessSensor Network (WSN) are said to be a complex homogeneous telecommunicationsystem that has numerous tiny distributed battery controlled devices named as sensors.The sensor nodes collaborate very well with each other in order to do sensingand computing tasks, they communicate and interact wirelessly. The lifetime ofWSN is mostly affected by the confinements of its sensors/nodes devices. Thusfar, power insufficiency is a major challenge of research in the area of WSN’slifetime. The way to optimize WSN’s lifetime clustering approaches andhierarchal routing protocols have been proposed.
This enables the transformation from homogeneousto heterogeneous deployment. It is known that heterogeneous networks are moreuseful in WSN. Therefore, it gathers the sensor nodes into many groups namedclusters. Each of these clusters has only a single connected node ofcentralization called cluster head. One keychallenge of WSN is performance optimization of its sensor nodes in order toreduce energy scarcity.
Consequently, lengthening the network lifetime. For thepurpose of extending the lifetime, WSN clustering algorithm based flowerpollination optimization algorithm was proposed used. Another importantenhancement for the WSN lifetime is by connecting the cluster nodes inconsideration to the suitable cluster head. Flower pollination optimizes thecreation of clusters, it is the aim of the intra-cluster distances and based onthat optimization (fitness) function it optimally can connect the cluster’snodes to each cluster. Furthermore, it chooses the best cluster headsdistribution that makes sure an optimized route with the least communicationlinks’ cost between nodes in every cluster. The proceduresfor optimizing the WSN are as follows: Network model; where it first deploys aWSN environment with a sized area (M x N). Then in the WSN deployedfield which is a static deployment, the energy controlled stationary sensordevices are scattered arbitrarily.
Additionally, assuming that the sensors aresending data to the intended node regularly and that these nodes are locatednear to each other with having correlated data. Then Energy Model; accordingto the first order radio energy model the nodes are set with their initialized energiesof all the nodes. In symmetrical communication channels the nodes are transferringmessage with k bits with a distance of d, thus, consume energy. Accordingto the distance between sender and receiver the calculation of energy was done.
After that the CH selection process starts; in which each cluster taken from theflower pollination clustering a cluster head is candidate to be selected, theone with the most remaining energy. Next the cluster formation; as for thispart, the cluster formation completely depends on flower pollinationoptimization algorithm as it searches to get the best distribution of nodes onclusters. The aim of the fitness function is utilized to reduce theintra-cluster density with least distance between nodes in the same cluster. Lastprocedure is the Data Transmission; whereas the sink node is directly connectedwith each CH, the sink node is a base station that is a high-energy node,placed farther from the sensor nodes in the points (Xsink, Ysink).The sensor nodes transfer their data packets straight to CH and each of theseCH get data from all of its cluster nodes.
Hence, to do important iterationsfor compression and it is directly associated with the sink node in order toforward the accumulated data packets. Therefore, the nodes die when they nolonger have energy.