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Task Offloading for End-Edge-Cloud Orchestrated Computing in Mobile Networks
- Source :
- WCNC
- Publication Year :
- 2020
- Publisher :
- IEEE, 2020.
-
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.
- 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
Subjects
Details
- Database :
- OpenAIRE
- Journal :
- 2020 IEEE Wireless Communications and Networking Conference (WCNC)
- Accession number :
- edsair.doi...........3a0c8f3da8fca0500ede2ebfa9c0fca9