TY - JOUR
T1 - Green resource allocation for mobile edge computing
AU - Meng, Anqi
AU - Wei, Guandong
AU - Zhao, Yao
AU - Gao, Xiaozheng
AU - Yang, Zhanxin
N1 - Publisher Copyright:
© 2022 Chongqing University of Posts and Telecommunications
PY - 2023/10
Y1 - 2023/10
N2 - We investigate the green resource allocation to minimize the energy consumption of the users in mobile edge computing systems, where task offloading decisions, transmit power, and computation resource allocation are jointly optimized. The considered energy consumption minimization problem is a non-convex mixed-integer non-linear programming problem, which is challenging to solve. Therefore, we develop a joint search and Successive Convex Approximation (SCA) scheme to optimize the non-integer variables and integer variables in the inner loop and outer loop, respectively. Specifically, in the inner loop, we solve the optimization problem with fixed task offloading decisions. Due to the non-convex objective function and constraints, this optimization problem is still non-convex, and thus we employ the SCA method to obtain a solution satisfying the Karush-Kuhn-Tucker conditions. In the outer loop, we optimize the offloading decisions through exhaustive search. However, the computational complexity of the exhaustive search method is greatly high. To reduce the complexity, a heuristic scheme is proposed to obtain a sub-optimal solution. Simulation results demonstrate the effectiveness of the developed schemes.
AB - We investigate the green resource allocation to minimize the energy consumption of the users in mobile edge computing systems, where task offloading decisions, transmit power, and computation resource allocation are jointly optimized. The considered energy consumption minimization problem is a non-convex mixed-integer non-linear programming problem, which is challenging to solve. Therefore, we develop a joint search and Successive Convex Approximation (SCA) scheme to optimize the non-integer variables and integer variables in the inner loop and outer loop, respectively. Specifically, in the inner loop, we solve the optimization problem with fixed task offloading decisions. Due to the non-convex objective function and constraints, this optimization problem is still non-convex, and thus we employ the SCA method to obtain a solution satisfying the Karush-Kuhn-Tucker conditions. In the outer loop, we optimize the offloading decisions through exhaustive search. However, the computational complexity of the exhaustive search method is greatly high. To reduce the complexity, a heuristic scheme is proposed to obtain a sub-optimal solution. Simulation results demonstrate the effectiveness of the developed schemes.
KW - Green communications
KW - Mixed-integer programming
KW - Mobile edge computing
KW - Resource allocation
UR - https://www.scopus.com/pages/publications/85133249735
U2 - 10.1016/j.dcan.2022.03.001
DO - 10.1016/j.dcan.2022.03.001
M3 - Article
AN - SCOPUS:85133249735
SN - 2468-5925
VL - 9
SP - 1190
EP - 1199
JO - Digital Communications and Networks
JF - Digital Communications and Networks
IS - 5
ER -