TY - GEN
T1 - Dynamic Task Offload System Adapting to the State of Network Resources in Mobile Edge Computing
AU - Satake, Hayata
AU - Kobayashi, Yuki
AU - Tani, Ryotaro
AU - Shigeno, Hiroshi
N1 - Funding Information:
ACKNOWLEDGEMENT Part of this work was carried out under the Cooperative Research Project Program of the Research Institute of Electrical Communication, Tohoku University.
Publisher Copyright:
© 2020 IEEE.
PY - 2020/3
Y1 - 2020/3
N2 - In disaster situation, collecting information about victims and disaster area quickly is required. However, it is expected that the communication environment is not fully prepared because communication facilities may be damaged. Mobile Edge Computing (MEC) is attracting attention, in which servers are distributed to the vicinity of end users. Thus, dynamic task offloading adapting to changes of network resources is useful in unstable network. This paper proposes a dynamic task offload system based on the state of network. The proposed offload system consists of two mechanisms. First mechanism is Software Defined Mobile Edge Computing (SDMEC) architecture. Second mechanism is dynamic task placement based on the state of network resources. We formulated an optimization problem to minimize the total response time while application execution. In the proposed offload system, multiple tasks are placed dynamically depending on the load of servers and network resources to minimize response time of application. We implemented the prototype of the proposed offload system and evaluated its performance.
AB - In disaster situation, collecting information about victims and disaster area quickly is required. However, it is expected that the communication environment is not fully prepared because communication facilities may be damaged. Mobile Edge Computing (MEC) is attracting attention, in which servers are distributed to the vicinity of end users. Thus, dynamic task offloading adapting to changes of network resources is useful in unstable network. This paper proposes a dynamic task offload system based on the state of network. The proposed offload system consists of two mechanisms. First mechanism is Software Defined Mobile Edge Computing (SDMEC) architecture. Second mechanism is dynamic task placement based on the state of network resources. We formulated an optimization problem to minimize the total response time while application execution. In the proposed offload system, multiple tasks are placed dynamically depending on the load of servers and network resources to minimize response time of application. We implemented the prototype of the proposed offload system and evaluated its performance.
KW - Mobile Edge Computing
KW - Offloading
KW - OpenFlow
KW - SDN
UR - http://www.scopus.com/inward/record.url?scp=85091976743&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85091976743&partnerID=8YFLogxK
U2 - 10.1109/PerComWorkshops48775.2020.9156233
DO - 10.1109/PerComWorkshops48775.2020.9156233
M3 - Conference contribution
AN - SCOPUS:85091976743
T3 - 2020 IEEE International Conference on Pervasive Computing and Communications Workshops, PerCom Workshops 2020
BT - 2020 IEEE International Conference on Pervasive Computing and Communications Workshops, PerCom Workshops 2020
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2020 IEEE International Conference on Pervasive Computing and Communications Workshops, PerCom Workshops 2020
Y2 - 23 March 2020 through 27 March 2020
ER -