TY - JOUR
T1 - Joint Task Offloading and Resource Allocation for Cooperative Mobile-Edge Computing Under Sequential Task Dependency
AU - Li, Xiang
AU - Fan, Rongfei
AU - Hu, Han
AU - Zhang, Ning
N1 - Publisher Copyright:
© 2014 IEEE.
PY - 2022/12/1
Y1 - 2022/12/1
N2 - The emergence of mobile-edge computing (MEC) makes it possible to run intelligent applications on Internet of Things (IoT) devices. However, due to blockage or deep fading, one IoT device may not have direct link with the edge server. In this case, many surrounding wireless devices can serve as a cooperative node. In this article, we study a cooperative MEC system running sequential task, which is composed of a series of subtasks and can support many intelligent applications. To minimize the energy consumption of the IoT device and cooperative node, a task offloading policy together with the allocation of communication and computation resources is designed jointly. The cases when the cooperative node has no/has private task to complete are investigated, which are denoted as cases I and II, respectively. Although both cases involve the optimization of integer variables, their optimal solutions are achieved. For the first case, the associated problem is simplified equivalently and then decomposed into two levels, with the upper level dealing with integer variables and the lower level handling continuous variables. Bisection search is employed to reach optimality in the lower level and the searching space is compressed in the upper level. For the second case, the associated problem is subdivided into three subproblems. To solve every subproblem optimally, a similar operation like case I is followed, with a semiclosed form solution derived in the lower level. Numerical results verify the effectiveness of our proposed methods compared with benchmark methods and our effort on reducing computation complexity.
AB - The emergence of mobile-edge computing (MEC) makes it possible to run intelligent applications on Internet of Things (IoT) devices. However, due to blockage or deep fading, one IoT device may not have direct link with the edge server. In this case, many surrounding wireless devices can serve as a cooperative node. In this article, we study a cooperative MEC system running sequential task, which is composed of a series of subtasks and can support many intelligent applications. To minimize the energy consumption of the IoT device and cooperative node, a task offloading policy together with the allocation of communication and computation resources is designed jointly. The cases when the cooperative node has no/has private task to complete are investigated, which are denoted as cases I and II, respectively. Although both cases involve the optimization of integer variables, their optimal solutions are achieved. For the first case, the associated problem is simplified equivalently and then decomposed into two levels, with the upper level dealing with integer variables and the lower level handling continuous variables. Bisection search is employed to reach optimality in the lower level and the searching space is compressed in the upper level. For the second case, the associated problem is subdivided into three subproblems. To solve every subproblem optimally, a similar operation like case I is followed, with a semiclosed form solution derived in the lower level. Numerical results verify the effectiveness of our proposed methods compared with benchmark methods and our effort on reducing computation complexity.
KW - Cooperative mobile-edge computing (MEC)
KW - joint allocation of communication and computation resources
KW - sequential task
KW - task offloading
UR - http://www.scopus.com/inward/record.url?scp=85134236075&partnerID=8YFLogxK
U2 - 10.1109/JIOT.2022.3188933
DO - 10.1109/JIOT.2022.3188933
M3 - Article
AN - SCOPUS:85134236075
SN - 2327-4662
VL - 9
SP - 24009
EP - 24029
JO - IEEE Internet of Things Journal
JF - IEEE Internet of Things Journal
IS - 23
ER -