TY - GEN
T1 - Self-organizing map using classification method for services in multilayer computing environments
AU - Iwai, Tomomu
AU - Ohno, Yuta
AU - Niwa, Akira
AU - Nakamura, Yuichi
AU - Sakai, Keiya
AU - Matsui, Kanae
AU - Nishi, Hiroaki
N1 - Funding Information:
ACKNOWLEDGMENT This work was supported by Technology Foundation of the R&D project “Design of Information and Communication Platform for Future Smart Community Services” by the Ministry of Internal Affairs and Communications of Japan. Moreover, the authors express their gratitude to MEXT/JSPS KAKENHI Grant (B) Numbers JP17H01739.
Funding Information:
This work was supported by Technology Foundation of the R&D project “Design of Information and Communication Platform for Future Smart Community Services” by the Ministry of Internal Affairs and Communications of Japan. Moreover, the authors express their gratitude to MEXT/JSPS KAKENHI Grant (B) Numbers JP17H01739.
Publisher Copyright:
© 2018 IEEE.
PY - 2018/12/26
Y1 - 2018/12/26
N2 - The increasing amount of data running in cloud-computing environments has started inflating networks. To solve the problems caused by network inflation (e.g., latency and privacy), new types of computing environments with multiple layers have been proposed. However, service placement inside these multilayer computing environments has not been proposed. Nodes inside multilayer computing environments have different preferences, and the services deployed also have restrictions on deployment. Therefore, services must be placed carefully inside the computing environment. To place these services, we introduce a service classification method according to their properties and restrictions. However, when accommodating dynamic placement, rapid classification is needed to avoid serious damage caused by restriction changes. Therefore, we propose a classifying method using k-Nearest Neighbor Classification (k-NN). In addition, to accelerate the process, we use a dimension reduction method called Self-Organizing Maps (SOM) to preprocess the data. The proposed classification method is expected to be used as the primary step in service placement. The method will supply service placers with the identification of which layer services should be deployed.
AB - The increasing amount of data running in cloud-computing environments has started inflating networks. To solve the problems caused by network inflation (e.g., latency and privacy), new types of computing environments with multiple layers have been proposed. However, service placement inside these multilayer computing environments has not been proposed. Nodes inside multilayer computing environments have different preferences, and the services deployed also have restrictions on deployment. Therefore, services must be placed carefully inside the computing environment. To place these services, we introduce a service classification method according to their properties and restrictions. However, when accommodating dynamic placement, rapid classification is needed to avoid serious damage caused by restriction changes. Therefore, we propose a classifying method using k-Nearest Neighbor Classification (k-NN). In addition, to accelerate the process, we use a dimension reduction method called Self-Organizing Maps (SOM) to preprocess the data. The proposed classification method is expected to be used as the primary step in service placement. The method will supply service placers with the identification of which layer services should be deployed.
KW - Edge computing
KW - Fog computing
KW - IoT services
KW - Self-organizing maps
KW - Service classification
UR - http://www.scopus.com/inward/record.url?scp=85061534329&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85061534329&partnerID=8YFLogxK
U2 - 10.1109/IECON.2018.8591565
DO - 10.1109/IECON.2018.8591565
M3 - Conference contribution
AN - SCOPUS:85061534329
T3 - Proceedings: IECON 2018 - 44th Annual Conference of the IEEE Industrial Electronics Society
SP - 4193
EP - 4198
BT - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 44th Annual Conference of the IEEE Industrial Electronics Society, IECON 2018
Y2 - 20 October 2018 through 23 October 2018
ER -