Quality-of-Experience-Aware Computation Offloading in MEC-Enabled Blockchain-Based IoT Networks
Mahsa Hosseinpour, Mohammad Hossein Yaghmaee
Abstract
Blockchain technology enables the Internet of Things (IoT) to build trust among various stakeholders. Offloading the computation-intensive IoT data processing and blockchain mining computations as tasks to mobile edge computing (MEC) and nearby devices in a device-to-device (D2D) network is a promising solution for resource constraint IoT devices. In this article, to decide on the offloading plan, we consider enhancing the users’ Quality of Experience (QoE) parameters reflecting the token-based cost of delay and energy consumption. For this purpose, we formulate the problem as a mixed integer nonlinear bilevel programming (MINLBP), which is NP-hard. Therefore, we propose a suboptimal solution with the help of two-sided matching theory games in two phases: 1) we decide to offload IoT data processing tasks using a many-to-one and 2) make a decision for mining tasks elaborating a many-to-many matching game. We also present algorithms based on the deferred acceptance (DA) mechanism to guarantee the stability of the matching results. The simulation results show that the proposed method can perform better in terms of delay and energy cost compared to the existing offloading approaches. Furthermore, it improves the utility of the users deciding to offload their tasks.