Integration of Range-Based and Range-Free Localization Algorithms in Wireless Sensor Networks for Mobile Clouds

Usually, in mobile server cloud computing (MSCC) environments, there exist enormous sensors conducting various tasks. Localization of sensor nodes using the technologies in Wireless Sensor Network (WSN) is critical to both cloud infrastructure operations and most applications. Specifically, in WSN, Malguki (the method´s name, Malguki, means ´spring´) is an effective range-based algorithm which can compute the location of a node using noisy distance estimations. However, through simulation, we found that, in original Malguki algorithm that uses an iterative process to locate unknown nodes, the initial positions of unknown nodes in iteration are evenly and randomly selected, which may cause large average localization error. Considering the mentioned weak point, this paper proposes to enhance the Malguki with a simple range-free Centroid localization algorithm, which intentionally obtains initial positions of unknown nodes in iteration by Centroid algorithm. Simulation results show that the integration of range-based and range-free localization algorithm, Centroid Malguki always performs better than original Malguki algorithm.