Study of Various Techniques to Identify Active Devices and their Channels and Introducing an Efficient Way to Find Some Active Devices and their Channels in an IoT Networks
Abstract – As we know that the devices used in any Internet of Things (IoT) network are low power electronic devices. An Internet of Things (IoT) network may contain huge number of devices in an small area for example an playground, or in a park. These devices can send a many king of traffic in playground for example some runner are running on a track in this case IoT devices can be in player’s shoes and in the same time a player in discus throwing is through a disk in the same ground in this case the IoT devices can be in any wearable device of player and also can be inside the disk. To track the devices which are active and also track their path simultaneously we need a base station which will receive data continuously and make their path. To get the continuous pattern of data transmission through active devices, we need to develop a structured-method of continuous path estimation that can detect the active devices that are sending signals and on the basis of their signals method can calculate the their paths accurately. In this paper we are proposing a method that take small number of signal sequence to track a path thus can track large number of IoT devices. To determine the path from small number of signature sequence, we studied the group sparsity estimation problem. We found that a minimum number of signature sequence is needed to find the path of user activity, below this the serving device (or server) cannot estimate the user activity correctly. He we are proposing an efficient method to detect the active devices along with their activity path based on a smoothing method that is a solution of high-dimensional structured estimation problem. Our method is estimating on the basis activity signature sequence length, the smoothing parameter, result accuracy and cost of computation tradeoff. After the discussion paper has a numerical result to proof the accuracy of our theory and results.
Keywords – Internet of Things (IoT), Sparsity of channel, Active Device (IoT) Identification and
Tracking their path, Sport Ground