Three Dynamic Pricing Schemes for Resource Allocation of Edge Computing for IoT Environment
- Authors
- Baek B.; Lee J.; Peng Y.; Park S.
- Issue Date
- May-2020
- Publisher
- Institute of Electrical and Electronics Engineers Inc.
- Keywords
- Bid-proportional pricing; dynamic pricing; edge computing; fairness-seeking differentiated pricing; Internet of Things (IoT)
- Citation
- IEEE Internet of Things Journal, v.7, no.5, pp.4292 - 4303
- Journal Title
- IEEE Internet of Things Journal
- Volume
- 7
- Number
- 5
- Start Page
- 4292
- End Page
- 4303
- URI
- https://scholarworks.bwise.kr/gachon/handle/2020.sw.gachon/53435
- DOI
- 10.1109/JIOT.2020.2966627
- ISSN
- 2327-4662
- Abstract
- With the widespread use of Internet of Things (IoT), edge computing has recently emerged as a promising technology to tackle low-latency and security issues with personal IoT data. In this regard, many works have been concerned with computing resource allocation of the edge computing server, and some studies have conducted to the pricing schemes for resource allocation additionally. However, few works have attempted to address the comparison among various kinds of pricing schemes. In addition, some schemes have their limitations such as fairness issues on differentiated pricing schemes. To tackle these limitations, this article considered three dynamic pricing mechanisms for resource allocation of edge computing for the IoT environment with a comparative analysis: BID-proportional allocation mechanism (BID-PRAM), uniform pricing mechanism (UNI-PRIM), and fairness-seeking differentiated pricing mechanism (FAID-PRIM). BID-PRAM is newly proposed to overcome the limitation of the auction-based pricing scheme; UNI-PRIM is a basic uniform pricing scheme; FAID-PRIM is newly proposed to tackle the fairness issues of the differentiated pricing scheme. BID-PRAM is formulated as a noncooperative game. UNI-PIM and FAID-PRIM are formulated as a single-leader-multiple-followers Stackelberg game. In each mechanism, the Nash equilibrium (NE) or Stackelberg equilibrium (SE) solution is given with the proof of existence and uniqueness. Numerical results validate the proposed theorems and present a comparative analysis of three mechanisms. Through these analyses, the advantages and disadvantages of each model are identified, to give edge computing service providers guidance on various kinds of pricing schemes. © 2014 IEEE.
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