TY - GEN
T1 - Fast and Efficient Cluster Based Map for Ship Tracking
AU - Akbar, Andi M.Ali Mahdi
AU - Purnama, I. Ketut Eddy
AU - Nugroho, Supeno Mardi Susiki
AU - Hariadi, Mochamad
N1 - Publisher Copyright:
© 2018 IEEE.
PY - 2018/7/2
Y1 - 2018/7/2
N2 - Automatic Identification System (AIS) is a system designed to improve maritime security by enabling the ship navigator to view the identity, position, and direction of other ships nearby. AIS data can be used to monitor ship activities. AIS data send simultaneously from multiple ship at very fast intervals. With the increased amount of data received, the performance of data retrieval using traditional RDBMS often decreased significantly. Also, storing geospatial data in traditional RDBMS or NoSQL lead to persistence of data, which is not required when tracking ship position, as majority of ship always moving. The increased amount of ship shown in monitoring map make it less informative, hence affecting users who use monitoring system. This paper proposes a fast cluster-based method to store and query AIS geospatial information using Redis and also maps it as a cluster into a web-based map to provide a faster and more efficient display.
AB - Automatic Identification System (AIS) is a system designed to improve maritime security by enabling the ship navigator to view the identity, position, and direction of other ships nearby. AIS data can be used to monitor ship activities. AIS data send simultaneously from multiple ship at very fast intervals. With the increased amount of data received, the performance of data retrieval using traditional RDBMS often decreased significantly. Also, storing geospatial data in traditional RDBMS or NoSQL lead to persistence of data, which is not required when tracking ship position, as majority of ship always moving. The increased amount of ship shown in monitoring map make it less informative, hence affecting users who use monitoring system. This paper proposes a fast cluster-based method to store and query AIS geospatial information using Redis and also maps it as a cluster into a web-based map to provide a faster and more efficient display.
KW - AIS
KW - Automatic Identification System
KW - Geohash
KW - Redis
KW - Server side cluster
KW - Ship Tracking
UR - http://www.scopus.com/inward/record.url?scp=85066474617&partnerID=8YFLogxK
U2 - 10.1109/CENIM.2018.8710934
DO - 10.1109/CENIM.2018.8710934
M3 - Conference contribution
AN - SCOPUS:85066474617
T3 - 2018 International Conference on Computer Engineering, Network and Intelligent Multimedia, CENIM 2018 - Proceeding
SP - 265
EP - 269
BT - 2018 International Conference on Computer Engineering, Network and Intelligent Multimedia, CENIM 2018 - Proceeding
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2018 International Conference on Computer Engineering, Network and Intelligent Multimedia, CENIM 2018
Y2 - 26 November 2018 through 27 November 2018
ER -