TY - GEN
T1 - Design of distributed calculation scheme using network address translation for ad-hoc wireless positioning network
AU - Kajimura, Jumpei
AU - Ishida, Shigemi
AU - Tagashira, Shigeaki
AU - Fukuda, Akira
N1 - Funding Information:
Acknowledgments. This work was supported in part by JSPS KAKENHI Grant Numbers 15H05708, 15K12021, 16K16048, and 17H01741, and the Cooperative Research Project of the Research Institute of Electrical Communication, Tohoku University.
Publisher Copyright:
© 2017, Springer International Publishing AG.
PY - 2017
Y1 - 2017
N2 - We have developed an ad-hoc wireless positioning network (AWPN) to realize on-demand indoor location-based services [10]. This paper extends our AWPN to handle huge number of localization requests. In AWPN, WiFi APs measure received signal strength (RSS) of WiFi signals and send the RSS information to a localization server via a WiFi mesh network. The maximum number of WiFi devices is therefore limited by computational resources on the localization server. We push this limit by introducing a new distributed calculation scheme: we use the MapReduce computation framework and perform map processes on APs and reduce processes on localization servers. We also utilize a network router capable of network address translation (NAT) for shuffle processes to provide scalability. We implemented and evaluated our distributed calculation scheme to demonstrate that our scheme almost evenly distributes localization calculations to multiple localization servers with approximately 26% variations.
AB - We have developed an ad-hoc wireless positioning network (AWPN) to realize on-demand indoor location-based services [10]. This paper extends our AWPN to handle huge number of localization requests. In AWPN, WiFi APs measure received signal strength (RSS) of WiFi signals and send the RSS information to a localization server via a WiFi mesh network. The maximum number of WiFi devices is therefore limited by computational resources on the localization server. We push this limit by introducing a new distributed calculation scheme: we use the MapReduce computation framework and perform map processes on APs and reduce processes on localization servers. We also utilize a network router capable of network address translation (NAT) for shuffle processes to provide scalability. We implemented and evaluated our distributed calculation scheme to demonstrate that our scheme almost evenly distributes localization calculations to multiple localization servers with approximately 26% variations.
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U2 - 10.1007/978-3-319-68282-2_3
DO - 10.1007/978-3-319-68282-2_3
M3 - Conference contribution
AN - SCOPUS:85031397141
SN - 9783319682815
T3 - Communications in Computer and Information Science
SP - 33
EP - 48
BT - Information Search, Integration, and Personlization - 11th International Workshop, ISIP 2016, Revised Selected Papers
A2 - Laurent, Dominique
A2 - Spyratos, Nicolas
A2 - Petit, Jean-Marc
A2 - Kotzinos, Dimitris
A2 - Tanaka, Yuzuru
PB - Springer Verlag
T2 - 11th International Workshop on Information Search, Integration, and Personlization, ISIP 2016
Y2 - 1 November 2016 through 4 November 2016
ER -