Improving the Accuracy of Location Algorithms in Wireless Sensor Networks with DTN and Grey Prediction Model
Author(s):
Neha Dhiyani , Noida Institute of Eng. & Technology, Greater NOIDA; Surya Prakash Sharma, Noida Institute of Eng. & Technology, Greater NOIDA
Keywords:
Localization, KNN (K-Nearest Neighbors), SMP (Smallest Polygon), DTN (Dynamic Triangular Node), RSSI (Received Signal Strength Indication)
Abstract:
This paper presents a DTN location algorithm that uses wireless sensor network and employs grey prediction to improve the accuracy of different location algorithms (KNN, SMP, TN, and DTN). Results have verified that grey prediction can predict the tendency of RSSI and reduce the fluctuation of RSSI when mobile user is moving. DTN cooperates with grey prediction achieved smallest mean distance error for run-time and off-line stage when mobile user goes away from the fixed sensor node. Localization algorithms integrated with grey prediction at run-time also have smaller mean distance error than location methods without grey prediction.
Other Details:
Manuscript Id | : | IJSTEV3I7023
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Published in | : | Volume : 3, Issue : 7
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Publication Date | : | 01/02/2017
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Page(s) | : | 14-18
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