A game-theoretic joint optimal pricing and resource allocation for Mobile Edge Computing in NOMA-based 5G networks and beyond

被引:20
|
作者
Roostaei, Razie [1 ]
Dabiri, Zahra [1 ]
Movahedi, Zeinab [1 ]
机构
[1] Iran Univ Sci & Technol, Sch Comp Engn, Tehran, Iran
关键词
Mobile Edge Computing; Offloading; Pricing; Resource allocation; Game theory; OPTIMIZATION; STRATEGY; FOG;
D O I
10.1016/j.comnet.2021.108352
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
Mobile Edge Computing is a new computing paradigm that offers cloud computation capabilities at the edge of the mobile network. Due to the proximity to Mobile Users (MUs), the edge cloud can be accessed with low latency by resource-limited mobile devices with the aim of extending their capabilities through computation offloading. Despite its unique features, the efficiency of offloading is highly influenced by the purchasing power of MUs as well as the competition arisen to access both limited communication and computation resources. However, since the MUs' demands for these resources change dynamically, the pricing approaches should be capable of adapting in real-world scenarios. To address the aforementioned challenges, we propose a game-based distributed scheme to jointly and dynamically allocate and price resources required for proper offloading in a two-tier NOMA-based mobile system. To this end, we consider the incentives of both the edge provider and MUs as well as conflicts arising from their interactions. Under the proposed scheme, MUs should pay not only based on the given resources but also based on their transmission power level as a punishment for their produced interference. We formulate the interactions among the monopolist edge provider and MUs using the Stackelberg game. Further, the power allocation in NOMA and the competition of MUs over computation resources are modeled using game theory and shown admitting the potential and the weakly coupled constraint game, respectively. Furthermore, we prove the existence and uniqueness of the equilibrium of both corresponding games and calculate it for both the edge provider and MUs. Simulation results demonstrate the efficiency of the proposed approach in terms of the utility of MUs and the edge provider, average allocated communication and computation resources, optimal pricing, and the number of rejected MUs under different purchasing power.
引用
收藏
页数:15
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