Queueing Theory Based Minimum Spanning Tree for Energy Consumption in Wireless Network

Wireless networks consist of number of sensor nodes which are equipped with data transceivers that enable them to communicate with each other to perform collaborative sensing tasks over a given area. Data collection is one of the important factors that affect data transmission and processing in wireless sensor networks. This paper discourses this issue by resources of the paths delay analysis. Queueing theory for wireless networks are of various kinds that cater to various different needs of researchers and scientists. Since each of these have a unique set of advantages and disadvantages, it becomes necessary for us to understand which of these might suit a particular scenario best. Queueing theory model the connectivity time packet sending time it could be loss of the data transmission. Our proposed model use M/M/1/N type queueing network model with holding nodes for wireless network and strategy approximate iterative algorithms. Experimental consequences show that the model is reliable with the real data. Queueing model leads to high energy consumption on their network. Our proposed method has to implement this problem and use efficient data collection using queueing model on the network. Also using the Minimum Spanning Tree (MST) its more than one geometry based on the link configuration. There are two channels like vertical channel Take a different parameter to show the result like as throughput, delivery ratio, delay, energy consumption, and then data collection efficient on networks.