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Task Offloading for Vehicular Edge Computing Based on Improved Hotstuff under Parking Assistance

Guoling Liang, Chunhai Li, Feng Zhao, Chuan Zhang, Liehuang Zhu

TL;DR

A blockchain-based PVEC (BPVEC) offloading framework to enhance the security and reliability of the task offloading and transaction and a consensus node selection algorithm based on the connected dominating set (CDS) is designed to improve the Hotstuff consensus according to parking duration, computing capability and communication quality.

Abstract

Parked-assisted vehicular edge computing (PVEC) fully leverages communication and computing resources of parking vehicles, thereby significantly alleviating the pressure on edge servers. However, resource sharing and trading for vehicular task offloading in the PVEC environment usually occur between untrustworthy entities, which compromises the security of data sharing and transactions by vehicles and edge devices. To address these concerns, blockchain is introduced to provide a secure and trustworthy environment for offloading and transactions in PVEC. Nevertheless, due to the mobility of the vehicles, the processes of computing offloading and blockchain transactions are interrupted, which greatly reduces the reliability of the blockchain in edge computing process. In this paper, we propose a blockchain-based PVEC (BPVEC) offloading framework to enhance the security and reliability of the task offloading and transaction. Specifically, a consensus node selection algorithm based on the connected dominating set (CDS) is designed to improve the Hotstuff consensus according to parking time, computing capability and communication quality, which enhances blockchain reliability in computing offloading and transactions. Meanwhile, a Stackelberg game model, establishing the roadside units (RSUs) and parking vehicles (PVs) as leaders and the requesting vehicles (RVs) as follower, is utilized to optimize the offloading strategy and pricing. Subsequently, a BPVEC offloading strategy algorithm with gradient descent method is designed to maximize system revenue. Simulation results show that the proposed BPVEC offloading scheme is secure and reliable while ensuring maximum benefits.

Task Offloading for Vehicular Edge Computing Based on Improved Hotstuff under Parking Assistance

TL;DR

A blockchain-based PVEC (BPVEC) offloading framework to enhance the security and reliability of the task offloading and transaction and a consensus node selection algorithm based on the connected dominating set (CDS) is designed to improve the Hotstuff consensus according to parking duration, computing capability and communication quality.

Abstract

Parked-assisted vehicular edge computing (PVEC) fully leverages communication and computing resources of parking vehicles, thereby significantly alleviating the pressure on edge servers. However, resource sharing and trading for vehicular task offloading in the PVEC environment usually occur between untrustworthy entities, which compromises the security of data sharing and transactions by vehicles and edge devices. To address these concerns, blockchain is introduced to provide a secure and trustworthy environment for offloading and transactions in PVEC. Nevertheless, due to the mobility of the vehicles, the processes of computing offloading and blockchain transactions are interrupted, which greatly reduces the reliability of the blockchain in edge computing process. In this paper, we propose a blockchain-based PVEC (BPVEC) offloading framework to enhance the security and reliability of the task offloading and transaction. Specifically, a consensus node selection algorithm based on the connected dominating set (CDS) is designed to improve the Hotstuff consensus according to parking time, computing capability and communication quality, which enhances blockchain reliability in computing offloading and transactions. Meanwhile, a Stackelberg game model, establishing the roadside units (RSUs) and parking vehicles (PVs) as leaders and the requesting vehicles (RVs) as follower, is utilized to optimize the offloading strategy and pricing. Subsequently, a BPVEC offloading strategy algorithm with gradient descent method is designed to maximize system revenue. Simulation results show that the proposed BPVEC offloading scheme is secure and reliable while ensuring maximum benefits.

Paper Structure

This paper contains 21 sections, 38 equations, 7 figures, 2 tables, 2 algorithms.

Figures (7)

  • Figure 1: The Hotstuff consensus process
  • Figure 2: BPVEC offloading system framework
  • Figure 3: Variation of the average $\varepsilon _{RSUi}$ with the transmission rate. (a) PV transmission rate $R_{pa}$. (b) RSU transmission rate $R_{RSU}$.
  • Figure 4: Variation of RV utility function with RV number in different offloading schemes. (a) Average RV utility. (b) Total RV utility.
  • Figure 5: Effect of different RVs, PVs and RSUs on utility function. (a) RVs. (b) PVs. (c) RSUs.
  • ...and 2 more figures