TY - GEN
T1 - Power-Aware server location decision in server migration service
AU - Fukushima, Yukinobu
AU - Yokohira, Tokumi
AU - Murase, Tutomu
AU - Suda, Tatsuya
N1 - Publisher Copyright:
© 2016 IEEE.
PY - 2016/11/30
Y1 - 2016/11/30
N2 - The server migration service (SMS) is an optional service that improves communication QoS of the IaaS cloud service. In the SMS, small-scale data centers (micro data centers) called work places (WPs) are deployed at various locations in the network. In the SMS, a network application (a NW-App) consists of one or more server-side processes of the application (servers) and one or more client-side processes of the application (clients). In the SMS, servers migrate among WPs in order to improve communication QoS between the servers and their clients, unlike in the IaaS cloud service where locations of the servers are always fixed at a data center in the network. In our previous study, we developed an integer programming model and solved it to determine when and to which WPs servers should migrate in the SMS in order to minimize the financial penalty, i.e., SMS provider's financial loss due to degradation of the communication QoS. In this paper, we consider the electricity power cost, an important component of the operational cost of the SMS, in addition to the financial penalty considered in our previous study, in determining when and to which WPs servers should migrate in the SMS. In this paper, we define the operational cost of the SMS as the sum of the financial penalty and electricity power cost and consider a power-Aware server location decision problem in order to minimize the operational cost of the SMS. We formulate the problem as a mixed-integer programming model and solve the model numerically. Numerical examples show that our mixed-integer programming model optimally determines the locations of the servers and decreases the operational cost by up to 15.5% compared to our previous integer programming model, where the power cost was not considered.
AB - The server migration service (SMS) is an optional service that improves communication QoS of the IaaS cloud service. In the SMS, small-scale data centers (micro data centers) called work places (WPs) are deployed at various locations in the network. In the SMS, a network application (a NW-App) consists of one or more server-side processes of the application (servers) and one or more client-side processes of the application (clients). In the SMS, servers migrate among WPs in order to improve communication QoS between the servers and their clients, unlike in the IaaS cloud service where locations of the servers are always fixed at a data center in the network. In our previous study, we developed an integer programming model and solved it to determine when and to which WPs servers should migrate in the SMS in order to minimize the financial penalty, i.e., SMS provider's financial loss due to degradation of the communication QoS. In this paper, we consider the electricity power cost, an important component of the operational cost of the SMS, in addition to the financial penalty considered in our previous study, in determining when and to which WPs servers should migrate in the SMS. In this paper, we define the operational cost of the SMS as the sum of the financial penalty and electricity power cost and consider a power-Aware server location decision problem in order to minimize the operational cost of the SMS. We formulate the problem as a mixed-integer programming model and solve the model numerically. Numerical examples show that our mixed-integer programming model optimally determines the locations of the servers and decreases the operational cost by up to 15.5% compared to our previous integer programming model, where the power cost was not considered.
KW - Cloud computing
KW - Financial loss
KW - Operational cost
KW - Optimal server locations
KW - Power consumption
KW - QoS
KW - Server migration service (SMS)
UR - https://www.scopus.com/pages/publications/85015747483
UR - https://www.scopus.com/pages/publications/85015747483#tab=citedBy
U2 - 10.1109/ICTC.2016.7763457
DO - 10.1109/ICTC.2016.7763457
M3 - Conference contribution
AN - SCOPUS:85015747483
T3 - 2016 International Conference on Information and Communication Technology Convergence, ICTC 2016
SP - 150
EP - 155
BT - 2016 International Conference on Information and Communication Technology Convergence, ICTC 2016
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2016 International Conference on Information and Communication Technology Convergence, ICTC 2016
Y2 - 19 October 2016 through 21 October 2016
ER -