Genetic-Algorithm-Based Service Function Deployment for Edge Computing
| Autor: | Bo-Hun Chen, 陳柏琿 |
|---|---|
| Rok vydání: | 2018 |
| Druh dokumentu: | 學位論文 ; thesis |
| Popis: | 106 In recent years, the mobile data traffic has a tremendous growth, especially most of these traffic originate from highly interactive applications such as virtual reality, Internet of Things (IoT) and Machine-Type Communication(MTC). The demand for low-latency communications has been considered as one of critical issue for fifth-generation standardization. In order to satisfy the demand of low-latency, the concept of mobile edge computing is recently emerged by placing computation resource to the edge network. With the technology of virtualization, service providers can rent computation resource from the infrastructure of network operator, and network operators also can deploy service functions(SFs) to the edge network to reduce the network latency. However, how to appropriately deploy these service functions into edge network will be a problem. We propose GASDE, a high-performance approach for deploying service functions into the edge network. GASDE uses genetic-algorithm(GA) to reduce network delay and cost of deployment, which considers the situation multi-tenancy would deploy their service functions into edge network. The result of simulation shows that when compared with other two strategies: GRE and DCB has the better performance of network delay and cost of deployment no matter in considering the case of only edge computing or cloud edge computing. We also implement a service function edge platform in XenServer to verify our works are more comprehensive and realistic. |
| Databáze: | Networked Digital Library of Theses & Dissertations |
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