郭荣佐 冯朝胜 秦志光

摘 要：针对物流领域的服务组合存在容错性差和服务不可靠等问题，提出一种基于π网的物联网智能物流系统物流服务容错组合模型。首先，在简单介绍物联网智能物流系统后，给出了物联网智能物流系统的容错服务组合框架;然后，基于π网建立了物联网智能物流系统物流服务容错组合模型，并对模型进行了容错正确性和拟合性分析;最后，对提出的模型进行了服务可靠性、服务故障容错可靠性实验，并与Petri网、QoS动态预测算法、模糊卡诺模型和改进粒子群优化的服务组合方法针对服务组合的执行时间、用户满意度、可靠性和最优度进行对比实验。实验结果表明，所提模型具有更高的服务可靠性和服务故障容错可靠性，同时在服务组合的执行时间、用户满意度、可靠性和最优度等方面也具有一定的优越性。

关键词：物联网;智能物流;容错服务组合;π网;建模与分析

中图分类号： TP311.5; TP301.2

文献标志码：A

Abstract： In order to solve the problem that the service composition in the logistics field has poor tolerance and unreliable service， a model of logistics service fault-tolerant composition for intelligent logistics system of Internet of Things （IoT） based on π-net was built. Firstly， after a brief introdution of IoT intelligent logistics system， a fault-tolerant service composition framework for the system was provided. Then， a model of logistics service fault-tolerant composition for the system based on π-net was built， and the correctness of fault tolerance and fitting degree of the model were analyzed. Finally， the service reliability and the fault-tolerant reliability of the model were tested， and the comparison with Petri-net， QoS （Quality of Service） dynamic prediction， fuzzy Kano model and modified particle swarm optimization methods in the service composition execution time， user satisfaction， reliability and optimal degree were carried out. The results show that the proposed model has high service reliability and fault-tolerant reliability， and has certain advantages in terms of service composition execution time， user satisfaction， reliability and optimal degree.

Key words： Internet of Things （IoT）; intelligent logistics; fault tolerant service composition; π-net; modeling and analysis

0 引言

电子商务的迅速发展，使得物流业务得到跨越式发展。物流快速发展后，其服务不得不依赖于现代信息技术，以使物流发展为智能物流。如Amazon公司利用现代信息技术，为各大运转中心、配送、订单与客服、库管、智能拣货、智能调拨和定位与跟踪等提供全面智能化服务[1]。基于物联网技术的智能物流系统能够提高对订单的实时掌控和科学调配能力，从而提高对配送人员的监控与管理能力，并有助于提高物流效率和客户满意度等。……