TY - GEN
T1 - Estimation of sensor network topology using ant colony optimization
AU - Takahashi, Kensuke
AU - Kurihara, Satoshi
AU - Hirotsu, Toshio
AU - Sugawara, Toshiharu
PY - 2009
Y1 - 2009
N2 - We propose a method for estimating sensor network topology using only time-series sensor data without prior knowledge of the locations of sensors. Along with the advances in computer equipment and sensor devices, various sensor network applications have been proposed. Topology information is often mandatory for predicting and assisting human activities in these systems. However, it is not easy to configure and maintain this information for applications in which many sensors are used. The proposed method estimates the topology accurately and efficiently using ant colony optimization (ACO). Our basic premise is to integrate ACO with the reliability of acquired sensor data for the adjacency to construct the accurate topology. We evaluated our method using actual sensor data and showed that it is superior to previous methods.
AB - We propose a method for estimating sensor network topology using only time-series sensor data without prior knowledge of the locations of sensors. Along with the advances in computer equipment and sensor devices, various sensor network applications have been proposed. Topology information is often mandatory for predicting and assisting human activities in these systems. However, it is not easy to configure and maintain this information for applications in which many sensors are used. The proposed method estimates the topology accurately and efficiently using ant colony optimization (ACO). Our basic premise is to integrate ACO with the reliability of acquired sensor data for the adjacency to construct the accurate topology. We evaluated our method using actual sensor data and showed that it is superior to previous methods.
UR - http://www.scopus.com/inward/record.url?scp=78650736738&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=78650736738&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-04921-7_27
DO - 10.1007/978-3-642-04921-7_27
M3 - Conference contribution
AN - SCOPUS:78650736738
SN - 3642049206
SN - 9783642049200
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 263
EP - 272
BT - Adaptive and Natural Computing Algorithms - 9th International Conference, ICANNGA 2009, Revised Selected Papers
T2 - 9th International Conference on Adaptive and Natural Computing Algorithms, ICANNGA 2009
Y2 - 23 April 2009 through 25 April 2009
ER -