1. Task Offloading for End-Edge-Cloud Orchestrated Computing in Mobile Networks
- Author
-
Xiuhua Li, Chuan Sun, Hui L, Junhao We, Qingyu Xiongl, Xiaofei Wang, and Victor C. M. Leun
- Subjects
Mobile edge computing ,Computer science ,Heuristic (computer science) ,business.industry ,Quality of service ,Distributed computing ,020302 automobile design & engineering ,020206 networking & telecommunications ,Cloud computing ,02 engineering and technology ,0203 mechanical engineering ,Server ,0202 electrical engineering, electronic engineering, information engineering ,Resource allocation ,Cache ,Enhanced Data Rates for GSM Evolution ,business - Abstract
Recently, mobile edge computing has received widespread attention, which provides computing infrastructure via pushing cloud computing, network control, and storage to the network edges. To improve the resource utilization and Quality of Service, we investigate the issue of task offloading for End-EdgeCloud orchestrated computing in mobile networks. Particularly, we jointly optimize the server selection and resource allocation to minimize the weighted sum of the average cost. A cost minimization problem is formulated underjoint the constraints of cache resource and communication/computation resource of edge servers. The resultant problem is a Mixed-Integer Non-linear Programming, which is NP-hard. To tackle this problem, we decompose it into simpler subproblems for server selection and resource allocation, respectively. We propose a low-complexity hierarchical heuristic approach to achieve server selection, and a Cauchy-Schwards Inequality based closed-form approach to efficiently determine resource allocation. Finally, simulation results demonstrate the superior performance of the proposed scheme on reducing the weighted sum of the average cost in the network.
- Published
- 2020