Pricing and Budget Allocation for IoT Blockchain With Edge Computing

Abstract

Attracted by the inherent security and privacy protection of the blockchain, incorporating blockchain into Internet of Things (IoT) has been widely studied in these years. However, the mining process requires high computational power, which prevents IoT devices from directly participating in blockchain construction. For this reason, edge computing service is introduced to help build the IoT blockchain, where IoT devices could purchase computational resources from the edge servers. In this paper, we consider the case that IoT devices also have other tasks that need the help of edge servers, such as data analysis and data storage. The profits they can get from these tasks is closely related to the amounts of resources they purchased from the edge servers. In this scenario, IoT devices will allocate their limited budgets to purchase different resources from different edge servers, such that their profits can be maximized. Moreover, edge servers will set "best" prices such that they can get the biggest benefits. Accordingly, there raise a pricing and budget allocation problem between edge servers and IoT devices. We model the interaction between edge servers and IoT devices as a multi-leader multi-follower Stackelberg game, whose objective is to reach the Stackelberg Equilibrium (SE). We prove the existence and uniqueness of the SE point, and design efficient algorithms to reach the SE point. In the end, we verify our model and algorithms by performing extensive simulations, and the results show the correctness and effectiveness of our designs.

Recent Advances of Blockchain and Its Applications

“…Liu et al [116] proposed a deep reinforcement learning approach that can help maximize on-chain transaction throughput of the blockchain system by selecting the block producers and consensus algorithms as well as adjusting the block size and block interval. Yun et al [117] proposed Deep Q Network Shard based Blockchain (DQNSB) scheme that dynamically finds the optimal throughput by selecting transaction sharding methods, also the block size and block interval. Ding et al [118] introduced edge server into IoT networks, where IoT devices are able to purchase computational power from edge servers.…”