A secure positioning algorithm against Sybil attack in wireless sensor networks based on number allocating

Author(s):  
Qing Tang ◽  
Jian Wang
2018 ◽  
Vol 2018 ◽  
pp. 1-10 ◽  
Author(s):  
Xiaogang Qi ◽  
Xiaoke Liu ◽  
Lifang Liu

Wireless sensor networks (WSNs) are widely used in various fields to monitor and track various targets by gathering information, such as vehicle tracking and environment and health monitoring. The information gathered by the sensor nodes becomes meaningful only if it is known where it was collected from. Considering that multilateral algorithm and MDS algorithm can locate the position of each node, we proposed a localization algorithm combining the merits of these two approaches, which is called MA-MDS, to reduce the accumulation of errors in the process of multilateral positioning algorithm and improve the nodes’ positioning accuracy in WSNs. It works in more robust fashion for noise sparse networks, even with less number of anchor nodes. In the MDS positioning phase of this algorithm, the Prussian Analysis algorithm is used to obtain more accurate coordinate transformation. Through extensive simulations and the repeatable experiments under diverse representative networks, it can be confirmed that the proposed algorithm is more accurate and more efficient than the state-of-the-art algorithms.


2014 ◽  
Vol 668-669 ◽  
pp. 1194-1197 ◽  
Author(s):  
Yan Feng ◽  
Bo Yi

The three-dimensional positioning algorithm has become a hot research direction in wireless sensor networks localization algorithms, however the existing 3D positioning algorithms have general shortcomings, such as high complexity, low positioning accuracy, great energy consumption. Aiming at the existing problems of 3D localization algorithm, we propose an decentralized 3D positioning algorithm based on RSSI ranging and free ranging mechanism. The algorithm firstly use measured RSSI to establish beacon node neighborhood. Then the method adopts regional division to obtain initial location information for unknown nodes. Finally, the method use the iterative optimization process to achieve a position information updates. Simulation results demonstrate that proposed algorithm is feasible and has better localization accuracy.


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