Improving Localization Accuracy in Wireless Sensor Networks
The most fundamental problem of wireless sensor networks is localization (finding the geographical location of the sensors). Most of the localization algorithms proposed for sensor networks are based on Sequential Monte Carlo (SMC) method. To achieve high accuracy in localization it requires high seed node density and it also suffers from low sampling efficiency. There are some papers which solves this problems but they are not energy efficient. Another approach The Bounding Box method was used to reduce the scope of searching the candidate samples and thus reduces the time for finding the set of valid samples.