Research Of Cloud Logistics Scheduling System Based On Hadoop

With the rapid development of social networking and e-commerce, online shopping volume ofbusiness grows sharply. Whether for electricity enterprises, consumers or logistics company, a seriesof logistics scheduling problems caused by mass data are increasingly prominent. Dueto lack of unified management, the traditional logistics management mode has been unable to meetthe increasingly complex supply chain system. How to ensure the speed of delivery, thesustainability and stability of supply chain and the instantaneity of logistics information, havebecome a huge problem for the logistics company.Combined with the traditional logistics management model and the most popular cloudcomputing technology, it can help build a cloud logistics management platform that will help breakthrough the bottleneck of the development of the logistics industry. By collecting the logisticdistribution demand and adding all of the logistics enterprises to the cloud logistics system, we cangather huge amounts of invoice as the cloud computing platform is established. The massiveinvoice data are analyzed and processed together according to the geography, time, category anddegree of emergency. Finally, the system will set out the optimal distribution scheme by usingdistribution nodes all over the country.Hadoop is a software framework for distributed processing of large data, which includes theintegration of cloud computing management, data warehousing and some other architectures. It hasbecome a standard platform for cloud computing applications in academia and the industry.Foreigncompany like Yahoo!, FaceBook, etc. and domestic firm as Ali, China Mobile, Huawei, etc., havedeployed their own cloud computing platform by Hadoop. Research on this topic is just based onthe in-depth analysis of Hadoop technology architecture, make the traditional logistics schedulingmodel combined with cloud computing. According to the cloud logistics scheduling system demand,the system is based on distributed storage capabilities of HDFS and HBase to store massive waybillinformation, based on MapReduce programming framework to achieve the unified logisticsscheduling algorithm. Finally, we successfully design and implement the cloud logistics schedulingsystem based on Hadoop.