4.7 Article

COMPUTING RESOURCE PROVISIONING AT THE EDGE: AN OVERBOOKING-ENABLED TRADING PARADIGM

期刊

IEEE WIRELESS COMMUNICATIONS
卷 29, 期 5, 页码 68-76

出版社

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/MWC.104.2100380

关键词

Decision making; Servers; Task analysis; Resource management; Forward contracts; Dynamic scheduling; Smart devices

资金

  1. National Natural Science Foundation of China [62271424, 61971365]
  2. Natural Sciences and Engineer-ing Research Council of Canada (NSERC) [RGPIN2018-06254]
  3. Canada Research Chair Program

向作者/读者索取更多资源

This article discusses the challenges of resource trading in IoT devices and proposes an overbooking-enabled solution. It presents a framework and a case study to demonstrate the effectiveness of the proposed approach in improving resource utilization and profit.
The arrival of the Internet of Things (IoT) era calls for cost-effective resource provisioning techniques to secure necessary computing resources in supporting dynamic and computation-intensive applications on diverse IoT devices, where resource trading in edge networks brings a viable prospect. While conventional onsite spot trading may facilitate this paradigm, the inherent extra latency of onsite decision making and unreliable network significantly limit resource trading efficiency and the eventual resource utilization rate. More importantly, the no show of confirmed resource buyers incurred by unreliable network conditions, can result in negative impacts on trading performance and resource usage. To this end, resource overbooking is adopted that provides an effective solution in handling no shows while substantially improving resource utilization rate. In this article, an interesting overbooking-enabled resource trading paradigm in mobile edge networks is proposed, allowing pre-negotiated forward contracts between the edge server (seller) and a number of overbooked smart devices (buyers), which will be fulfilled during future trading. Specifically, a framework associated with the proposed trading paradigm is introduced first to provide a comprehensive view of the relevant key issues. Then a case study is presented that elaborates how the proposed trading can be implemented in practice. Extensive simulation results and analysis demonstrate that the overbooking-enabled trading paradigm achieves both time and energy efficiency, as well as substantial resource utilization and profit improvements.

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