A weighted and distributed algorithm for multi-hop localization

Abstract

Multi-hop wireless sensor networks are widely used in many location-dependent applications. Most applications assume the knowledge of geographic location of sensor nodes; however, in practical scenarios, the high accuracy on position estimates of sensor nodes is still a great challenge. In this research, we propose a hop-weighted scheme that can be useful in distance-based distributed multi-hop localization. The hop-weighted localization approach generates spatial locations around position estimates of unknown sensors and computes local functions that minimize distance errors among hop-weighted and static neighboring sensors. The iterative process of each unknown sensor to re-estimate its own location allows a significant reduction of initial position estimates. Simulations demonstrate that this weighted localization approach, when compared with other schemes, can be suitable to be used as a refinement stage to improve localization in both isotropic and anisotropic networks. Also, under rough initial position estimates, the proposed algorithm achieves root mean square error values less than the radio range of unknown sensors, in average, with only a few iterations.

A Weighted and Distributed Algorithm for Range-Based Multi-Hop Localization Using a Newton Method

“…This is because the SOCP algorithm is highly dependent on the number and location of the anchors. On average, the DV-Hop+DWDSCL [38] obtains the best accuracy performance with 23.36 m followed by the combination DV-Hop-RWNM with 24.04 m. Moreover, this last combination outperforms others in rate of convergence with only 4.25 iterations, in average, which implies more saving energy for the entire network as shown Table 2. Now, keeping both the position set of unknown sensors and anchors positions for each one of the 10 benchmark networks and also taking the same set of range connections (i.e., R = 35 m), the distance errors among neighboring sensors are now affected with n f e = 0.3, and the results are depicted in Figure 4.…”

“…This is because the SOCP algorithm is highly dependent on the number and location of the anchors. On average, the DV-Hop+DWDSCL [ 38 ] obtains the best accuracy performance with 23.36 m followed by the combination DV-Hop-RWNM with 24.04 m. Moreover, this last combination outperforms others in rate of convergence with only 4.25 iterations, in average, which implies more saving energy for the entire network as shown Table 2 .…”

“…Finally, Equation (41) is used to calculate the average RMSE (RMSEavg) of the 10 networks and also the average of the numbers of iterations (Iter_avg) is obtained. The next step consists of testing the same combination (R = 35 m and n f e = 0.1), but now adding 10% of outliers to noisy distances with (38). This process is repeated until reaching 50% of outliers in noisy distances.…”

Node Localization Algorithm Based on Modified Archimedes Optimization Algorithm in Wireless Sensor Networks

“…The DV-Hop localization algorithm is one of the most famous range-free localization algorithms in WSNs [24][25][26] due to its high robustness and simplicity. But, the DV-Hop algorithm has a lower localization accuracy in complex environment.…”