利用区块链托管匹配机制为最后一英里配送应用提供众包车辆和无人机

IF 5.8 2区 计算机科学 Q1 TELECOMMUNICATIONS Vehicular Communications Pub Date : 2024-03-15 DOI:10.1016/j.vehcom.2024.100761
Maha Kadadha , Rabeb Mizouni , Shakti Singh , Hadi Otrok , Azzam Mourad
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引用次数: 0

摘要

众包模式已被用于最后一英里配送应用,通过众包车辆提供具有成本效益的配送服务。由于用户对快速送货的需求日益增长,无人驾驶飞行器(UAV)因其速度快、成本低而被采用,例如在高峰时段。然而,现有的框架并没有提供一个全面的解决方案,利用车辆和无人机实现透明、及时和具有成本效益的交付。本文提出了一种基于联合体区块链的新型供应链管理框架,通过众包车辆和无人机实现最后一英里配送。基于区块链的框架旨在以透明、经济高效的方式为时间紧迫的任务提供最后一英里配送。设计了一种区块链托管的 Gale-Shapley 匹配机制,用于将交付任务分配给无人机和车辆,使其能够及时、经济高效地执行任务。该分配机制被纳入了拟议的管理框架,该框架由智能合约组成,可自主响应成员的互动。此外,该框架还以透明和不变的方式存储供应链流程数据。所进行的实验探索了拟议解决方案的可行性,结果表明,与所考虑的基准相比,任务分配百分比(至少 6%)和奖励(至少 50%)均有所提高,同时交付时间也缩短了(至少 23%)。
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Crowdsourced vehicles and UAVs for last-mile delivery application using blockchain-hosted matching mechanism

The crowdsourcing paradigm has been used for last-mile delivery applications to offer cost-efficient delivery through crowdsourced vehicles. The increasing demand from users for fast delivery led to the adoption of Unmanned Aerial Vehicles (UAVs) due to their speed and cost, for instance, in peak hours. However, existing frameworks do not offer a comprehensive solution that utilizes vehicles and UAVs for transparent, timely, and cost-efficient delivery. This paper proposes a novel supply chain management framework on a consortium blockchain with last-mile delivery through crowdsourced vehicles and UAVs. The blockchain-based framework aims to provide last-mile delivery for time-critical tasks in a transparent and cost-efficient manner. A blockchain-hosted Gale-Shapley Matching mechanism is designed for allocating delivery tasks to UAVs and vehicles that will perform them timely and cost-efficiently. The allocation mechanism is incorporated in the proposed management framework consisting of smart contracts that autonomously respond to members' interactions. In addition, the framework stores the supply chain process data transparently and immutably. The performed experiments explore the feasibility of the proposed solution showing the increase in task allocation percentage (at least 6%) and reward (at least 50%) while reducing the delivery time (at least 23%) compared to the considered benchmarks.

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来源期刊
Vehicular Communications
Vehicular Communications Engineering-Electrical and Electronic Engineering
CiteScore
12.70
自引率
10.40%
发文量
88
审稿时长
62 days
期刊介绍: Vehicular communications is a growing area of communications between vehicles and including roadside communication infrastructure. Advances in wireless communications are making possible sharing of information through real time communications between vehicles and infrastructure. This has led to applications to increase safety of vehicles and communication between passengers and the Internet. Standardization efforts on vehicular communication are also underway to make vehicular transportation safer, greener and easier. The aim of the journal is to publish high quality peer–reviewed papers in the area of vehicular communications. The scope encompasses all types of communications involving vehicles, including vehicle–to–vehicle and vehicle–to–infrastructure. The scope includes (but not limited to) the following topics related to vehicular communications: Vehicle to vehicle and vehicle to infrastructure communications Channel modelling, modulating and coding Congestion Control and scalability issues Protocol design, testing and verification Routing in vehicular networks Security issues and countermeasures Deployment and field testing Reducing energy consumption and enhancing safety of vehicles Wireless in–car networks Data collection and dissemination methods Mobility and handover issues Safety and driver assistance applications UAV Underwater communications Autonomous cooperative driving Social networks Internet of vehicles Standardization of protocols.
期刊最新文献
Decentralized multi-hop data processing in UAV networks using MARL Prediction-based data collection of UAV-assisted Maritime Internet of Things Hybrid mutual authentication for vehicle-to-infrastructure communication without the coverage of roadside units Hierarchical federated deep reinforcement learning based joint communication and computation for UAV situation awareness Volunteer vehicle assisted dependent task offloading based on ant colony optimization algorithm in vehicular edge computing
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