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| Title | A Survey On Auction Based Approaches For Resource Allocation And Pricing In Emerging Edge Technologies |
|---|---|
| ID_Doc | 5222 |
| Authors | Kumar D.; Baranwal G.; Vidyarthi D.P. |
| Year | 2022 |
| Published | Journal of Grid Computing, 20, 1 |
| DOI | http://dx.doi.org/10.1007/s10723-021-09593-9 |
| Abstract | The advancements in sensing technologies, smart devices, wearable gadgets, and communication paradigm enable the vision of the internet of things, smart city, virtual and augmented reality, pervasive healthcare, to name a few. These applications have strict requirements of low latency delivery, high data rate, and instant response. To support this, various new technologies, such as fog computing, mobile edge computing, cloudlet, Micro, and Nano centers, mini and micro clouds, etc., have emerged. The entire set of emerging edge computing paradigms are commonly referred as "edge technologies" in which computational resources and storage are closer to the user/terminal devices somewhere between the device and the cloud data center. The edge technologies aim to deliver computing services with minimal delay by reducing the downward and upward time and data traffic volume. Like cloud service providers, edge service providers are emerging, and a market of edge computing resources has been created. Therefore, Auction theory, a subfield of Economics, is being widely applied for the allocation of resources in emerging edge technologies. This work presents a comprehensive survey on auction-based resource allocation and pricing approaches in emerging edge technologies. An overview of edge technologies and auction theory is given, followed by a thorough review and comparison of the existing auction-based approaches applied in edge technologies for resource allocation and pricing in terms of economic properties. Various open research issues have been deliberated to set the future research direction at the end. © 2021, The Author(s), under exclusive licence to Springer Nature B.V. |
| Author Keywords | Auction theory; Edge technologies; Internet of things; Resource provisioning; Smart everything |
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