移动边缘计算支持的边缘云系统中基于游戏的定价和任务卸载
Game-based Pricing and Task Offloading in Mobile Edge Computing Enabled Edge-Cloud Systems
摘要：
移动边缘计算（MEC）作为物联网（IoT）的重要使能技术，为IoT移动设备（MD）提供了强大的外部计算和存储资源。然而，针对开放交换市场的分布式任务卸载和价格竞争机制尚未建立，这已成为MEC在物联网市场应用的巨大障碍。在本文中，我们制定了一个分布式的机制，以分析在MEC启用边缘云系统中的OSP和物联网MD之间的交互，通过应用多领导者多追随者两层Stackelberg博弈理论。首先证明了Stackelberg均衡的存在性，然后提出了两种分布式算法，即迭代最近卸载算法（IPOA）和迭代Stackelberg博弈定价算法（ISPA）。IPOA解决了物联网MD之间的跟随者非合作博弈，ISPA使用逆向归纳来处理OSP之间的价格竞争。实验结果表明，与传统的任务卸载方案相比，IPOA能显著降低物联网MD的负效用，无政府状态的无政府代价始终小于150%.此外，研究结果还表明，ISPA是可靠的，以提高收入的OSP。
英文摘要：
As a momentous enabling of the Internet of things (IoT), mobile edge computing (MEC) provides IoT mobile devices (MD) with powerful external computing and storage resources. However, a mechanism addressing distributed task offloading and price competition for the open exchange marketplace has not been established properly, which has become a huge obstacle to MEC's application in the IoT market. In this paper, we formulate a distributed mechanism to analyze the interaction between OSPs and IoT MDs in the MEC enabled edge-cloud system by appling multi-leader multi-follower two-tier Stackelberg game theory. We first prove the existence of the Stackelberg equilibrium, and then we propose two distributed algorithms, namely iterative proximal offloading algorithm (IPOA) and iterative Stackelberg game pricing algorithm (ISPA). The IPOA solves the follower non-cooperative game among IoT MDs and ISPA uses backward induction to deal with the price competition among OSPs. Experimental results show that IPOA can markedly reduce the disutility of IoT MDs compared with other traditional task offloading schemes and the price of anarchy is always less than 150\%. Besides, results also demonstrate that ISPA is reliable in boosting the revenue of OSPs.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
