TY - GEN
T1 - Coalition Formation Game for Task Offloading in Edge Computing with Considering Individual Rationality and Collective Rationality of Users
AU - Zhou, Yubin
AU - Liu, Tong
AU - Zhu, Yanmin
AU - Gao, Honghao
AU - Yang, Yuanyuan
N1 - Publisher Copyright: © 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - With the development of 5G, edge computing has raised as a promising technology to satisfy the requirements of computation-intensive and delay-sensitive applications. In this work, we try to propose a task offloading strategy for end users, with considering their individual rationality and collective rationality at the same time. Specially, a user only with individual rationality aims to minimize the completion time of its own task, while a user only with collective rationality aims to minimize the total task completion time achieved by the system. The problem is particularly difficult, as there exist essential conflicts between the individual utility of each user and the collective utility of the system, which cannot be optimized simultaneously. To overcome the difficulties, we first reformulate the problem as a coalition formation game. Then, we propose an iterative algorithm, in which each user can make its task offloading decision in a decentralized way. Additionally, we rigorously prove the properties achieved by our algorithm in terms of stability, optimality, and convergence rate. Extensive simulations are also conducted to validate the performance of our algorithm compared with baselines.
AB - With the development of 5G, edge computing has raised as a promising technology to satisfy the requirements of computation-intensive and delay-sensitive applications. In this work, we try to propose a task offloading strategy for end users, with considering their individual rationality and collective rationality at the same time. Specially, a user only with individual rationality aims to minimize the completion time of its own task, while a user only with collective rationality aims to minimize the total task completion time achieved by the system. The problem is particularly difficult, as there exist essential conflicts between the individual utility of each user and the collective utility of the system, which cannot be optimized simultaneously. To overcome the difficulties, we first reformulate the problem as a coalition formation game. Then, we propose an iterative algorithm, in which each user can make its task offloading decision in a decentralized way. Additionally, we rigorously prove the properties achieved by our algorithm in terms of stability, optimality, and convergence rate. Extensive simulations are also conducted to validate the performance of our algorithm compared with baselines.
KW - Edge computing
KW - coalition formation game
KW - collective rationality
KW - individual rationality
KW - task offloading
UR - https://www.scopus.com/pages/publications/85137271607
U2 - 10.1109/ICC45855.2022.9838391
DO - 10.1109/ICC45855.2022.9838391
M3 - Conference contribution
T3 - IEEE International Conference on Communications
SP - 1647
EP - 1652
BT - ICC 2022 - IEEE International Conference on Communications
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2022 IEEE International Conference on Communications, ICC 2022
Y2 - 16 May 2022 through 20 May 2022
ER -