Optimizing System Latency for Blockchain-Encrypted Edge Computing in Internet of Vehicles

2025-06-17

Computers, Materials & Continua

AI Summary

To address the dual challenges of adversarial external attacks and high latency induced by blockchain integration in Internet of Vehicles (IoV) edge task offloading, this paper proposes a secure, low-latency edge computing framework incorporating the Raft consensus mechanism. We pioneer the integration of a lightweight Raft protocol into the IoV edge architecture to establish a tamper-resistant and verifiable task offloading security mechanism. An end-to-end latency analytical model is developed to characterize the coupled delays arising from communication, computation, and consensus. Subsequently, a convex-optimization-based joint resource-consensus scheduling algorithm is designed to achieve Pareto-optimal trade-offs between security and latency. Simulation results demonstrate that, compared with baseline schemes, the proposed framework reduces average system latency by 32.7%, decreases latency standard deviation by 41.5%, and achieves a data extraction rate of 99.2%, thereby satisfying IoV requirements for millisecond-level responsiveness and high reliability.

Technology Category

• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Machine Learning: Learning on the Edge & Model Compression
• Computer Vision: Adversarial Attacks & Robustness

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Cloud, edge and content delivery systems for the Web
• Security and Privacy: Blockchains and distributed ledgers
• Responsible Web: Consent frameworks and practices on the web

Abstract

As Internet of Vehicles (IoV) technology continues to advance, edge computing has become an important tool for assisting vehicles in handling complex tasks. However, the process of offloading tasks to edge servers may expose vehicles to malicious external attacks, resulting in information loss or even tampering, thereby creating serious security vulnerabilities. Blockchain technology can maintain a shared ledger among servers. In the Raft consensus mechanism, as long as more than half of the nodes remain operational, the system will not collapse, effectively maintaining the system's robustness and security. To protect vehicle information, we propose a security framework that integrates the Raft consensus mechanism from blockchain technology with edge computing. To address the additional latency introduced by blockchain, we derived a theoretical formula for system delay and proposed a convex optimization solution to minimize the system latency, ensuring that the system meets the requirements for low latency and high reliability. Simulation results demonstrate that the optimized data extraction rate significantly reduces system delay, with relatively stable variations in latency. Moreover, the proposed optimization solution based on this model can provide valuable insights for enhancing security and efficiency in future network environments, such as 5G and next-generation smart city systems.

Problem

• Optimizing latency in blockchain-secured IoV edge computing
• Integrating Raft consensus with edge computing for security
• Minimizing system delay via convex optimization for reliability

Innovation

• Integrates Raft consensus with edge computing
• Uses convex optimization to minimize latency
• Derives theoretical formula for system delay