Trust-Based Distributed Resource Allocation in Edge-Enabled IIoT Networks

Abstract

Due to the emergence of computation-intensive and latency-sensitive applications, the Industrial Internet of Things (IIoT) paradigm imposes several new challenges to the Mobile Edge Computing (MEC) platform with minimal compute resources. MEC has emerged as a new paradigm that can enhance the performance of edge services through optimal service execution. As IIoT devices are mostly resource and energy-constrained, therefore it provides several challenges: 1) maximization of resource utilization; 2) minimization of average delay; 3) high throughput required to execute the edge services. To handle such issues, a trust-based distributed resource allocation (TDRA) framework is developed to offer optimal throughput and resource utilization to IIoT-enabled MEC. On the other hand, we set different priorities for edge services based on application types for optimal resource allocation. We formulate the proposed scheme mathematically and analyze the complexity of TDRA. We present extensive experimental results to illustrate the superiority of TDRA compared to existing solutions in the literature with regard to resource utilization, utility, delay, cost, and fairness.