TY - GEN
T1 - Improved range-free localization methods for wireless sensor networks
AU - Kristalina, Prima
AU - Wirawan,
AU - Hendrantoro, Gamantyo
PY - 2011
Y1 - 2011
N2 - Localization in wireless sensor networks (WSNs) is an essential service, important as both a goal and a mean. It is a goal for WSNs in order to label reported data and a mean for most WSNs to implement networks management services. In distributed localization, there could be a small number of nodes, which have a priori knowledge about their position, called reference nodes and most of the other nodes which do not know their location. Range-free localization technique is the cost-effective technique because it does not require sensors to be equipped with any hardware, but use less information than range-based algorithm. Centroid algorithm is one of the range-free technique, where the references send out their position information to neighbor nodes at periodic intervals. The position of unknown node is then estimated to be centroid of the reference nodes. In this paper, we propose the improved centroid algorithm by selecting the neighbor references based on the connectivity of unknown node and them. Simulation results show that the localization error of unknown nodes is reduced by the proposed method.
AB - Localization in wireless sensor networks (WSNs) is an essential service, important as both a goal and a mean. It is a goal for WSNs in order to label reported data and a mean for most WSNs to implement networks management services. In distributed localization, there could be a small number of nodes, which have a priori knowledge about their position, called reference nodes and most of the other nodes which do not know their location. Range-free localization technique is the cost-effective technique because it does not require sensors to be equipped with any hardware, but use less information than range-based algorithm. Centroid algorithm is one of the range-free technique, where the references send out their position information to neighbor nodes at periodic intervals. The position of unknown node is then estimated to be centroid of the reference nodes. In this paper, we propose the improved centroid algorithm by selecting the neighbor references based on the connectivity of unknown node and them. Simulation results show that the localization error of unknown nodes is reduced by the proposed method.
KW - WSNs
KW - localization
KW - weighted centroid
UR - http://www.scopus.com/inward/record.url?scp=80054047113&partnerID=8YFLogxK
U2 - 10.1109/ICEEI.2011.6021625
DO - 10.1109/ICEEI.2011.6021625
M3 - Conference contribution
AN - SCOPUS:80054047113
SN - 9781457707520
T3 - Proceedings of the 2011 International Conference on Electrical Engineering and Informatics, ICEEI 2011
BT - Proceedings of the 2011 International Conference on Electrical Engineering and Informatics, ICEEI 2011
T2 - 2011 International Conference on Electrical Engineering and Informatics, ICEEI 2011
Y2 - 17 July 2011 through 19 July 2011
ER -