부산대학교 도서관

Node localization is one of the most essential features of wireless sensor networks (WSNs). Vavarious localization algorithms exist for densely deployed 3-D wireless sensor networks. However, for a sparse 3-D network, range-based localization is still a challenging task because it is difficult to find sufficient anchor nodes and distance information among nodes in a sparse 3-D network. To mitigate the sparseness issues in 3-D sensor networks, we present a component-based localization method in this paper in which we split the entire network into small overlapping sub-networks called components and assign local coordinates to each component. Then, we merge these small components to make a globally coordinated system. With a meager anchor ratio, we localize the whole network. We define merging conditions according to the number of common nodes, actual measured distances among nodes, and the calculated distance based on the local coordinates of the nodes. We assess how well our proposed algorithm performs by conducting extensive simulations. The outcomes confirm that the proposed algorithm works comparatively better in a sparse 3-D sensor network than in a densely deployed 3-D sensor network. Our algorithm localizes more than 83% of nodes at a node degree of 10 having 5% anchor ratio; however, other algorithms localize only 18%-79% in the same scenario.