| Autor: |
Yan Chen, Yanjing Sun, Tianxin Feng, Song Li |
| Jazyk: |
angličtina |
| Rok vydání: |
2020 |
| Předmět: |
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| Zdroj: |
IEEE Access, Vol 8, Pp 112659-112673 (2020) |
| Druh dokumentu: |
article |
| ISSN: |
2169-3536 |
| DOI: |
10.1109/ACCESS.2020.3002813 |
| Popis: |
Edge computing brings powerful computing ability to the proximity of IoT devices to guarantee latency constraints, making it one essential technology for supporting intelligent applications in future Internet of Things (IoT). Collaboration among edge computing servers (ECSs) with limited resources is an efficient solution to enhance the capability of edge network, and placement of ECSs and service functions (SFs) impose significant influences on system performance. This paper explores the collaboration among ECSs by considering the simultaneous and heterogeneous consumption of different computing resources. The service deployment and application assignment in regional edge computing enabled IoT (EdgeIoT) are investigated. A collaborative service deployment and application assignment (ColSDA) algorithm is proposed to render the final edge service deployment strategy, including the placement of ECSs and SFs as well as the assignment of applications to ECSs. In ColSDA, the minimum number of ECSs to be placed is obtained by the proposed minimum resource ration increase (MinRI) algorithm. Computing loads are then balanced by the load-balancing reassignment (LBRA) algorithm. After placing ECSs, a search and swap (SeSw) algorithm is proposed to further increase the number of tasks processed by locally deployed ECSs. Simulation results demonstrate that the number of required ECSs under the premise of guaranteeing the quality of service (QoS) can be significantly reduced by establishing collaboration among ECSs. Besides, the proposed ColSDA algorithm can provide the service deployment and application assignment strategy for a given region EdgeIoT as expected. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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