An Energy-efficient Computing Offloading Framework for Blockchain-enabled Video Streaming Systems

Abstract

Blockchain and edge computing have been widely applied in video streaming systems. However, previous works lack a joint consideration of video redundancy and full utilization of edge resources (bandwidth resources, CPU frequency), resulting in suboptimal performance of video streaming systems. In this paper, we propose a computing offloading framework for blockchain-enabled video streaming systems to fully exploit edge resources and reduce energy consumption. Specifically, we formulate computing offloading, resource allocation, and adaptive compression as a joint optimization problem. We transform and decompose the original non-convex problem and propose an algorithm based on the alternating direction method of multipliers (ADMM) to solve the decomposed problem in a distributed manner. Simulation results demonstrate that our scheme can effectively reduce energy consumption and fully utilize the bandwidth and computational resources.