Energy and Latency Control for Edge Computing in Dense V2X Networks

TL;DR

This paper proposes a dynamic control algorithm for dense V2X networks that optimizes energy consumption and latency by managing offloaded tasks and transmit power without needing global channel information.

Contribution

It introduces a novel, interference-aware control algorithm for energy and latency management in dense V2X edge computing networks.

Findings

Effective energy and latency tradeoff achieved

Interference coordination without global channel info

Algorithm outperforms baseline methods

Abstract

This study focuses on edge computing in dense millimeter wave vehicle-to-everything (V2X) networks. A control problem is formulated to minimize the energy consumption under delay constraint resulting from vehicle mobility. A tractable algorithm is proposed to solve this problem by optimizing the offloaded computing tasks and transmit power of vehicles and road side units. The proposed dynamic solution can well coordinate the interference without requiring global channel state information, and makes a tradeoff between energy consumption and task computing latency.