Design and Implementation of Cloud Platform for Intelligent Logistics in the Trend of Intellectualization

Mengke Yang＊, Movahedipour Mahmood＊, Xiaoguang Zhou Salam Shafaq, Latif Zahid4 School of Automation, Beijing University of Posts and Telecommunications, Beijing00876, China

2 Academic Center for Education, Culture and Research, (ACECR), 14155-4364, Tehran, Iran

2,3,4 School of Economics & Management, Beijing University of Posts and Telecommunications, Beijing100876, China

* The Correspondence author, email: yangmengke@139.com, mahmood.movahedipour@yahoo.com

Editor: Xudong Gao

I. INTRODUCTION

Intellectualization is a very important term from Chinese government work report in March 2017, which is not only a clear policy or strategy from government, but also a new developing direction for ICT industry. Intellectualization has become a new trend for ICT operators, which is driven by the new technology including cloud computing, big data and Internet of things because of the development of mobile Internet [1]. The intelligent application services based on intelligent terminals provided by the internet enterprises bring unprecedented impact and challenge into this field. It is urgent to take actions for the ICT operators in reformation and transformation towards the comprehensively intelligent service operators [2]. The intelligent service consists of more than intelligent connection, intelligence platform and intelligent applications,but the business ecosystem of the convergence can also be involved. And then it becomes an issue on how to develop the intelligent service platform in the trend of intellectualization in ICT industry [3].

Since 1920s, the theory about information has been widely interested and made contributions such as Nyguist.H published the classic paper named “Certain topics in telegraph transmission theory” in 1928[4]. In the 1970s,human society entered the microelectronics technology term which provided means for the digital expression and construction of information that information began to emerge as an independent information platform and triggering an information revolution. Since then,more scholars begun to do research on information platform, such as Parsons GL (1983)[5] and Porter ME, Millar VE (1995)[6], both of them pointed out that the development of information technology will bring great impact to enterprises.

From the 21th century, how to apply the new ICT technology such as cloud computing for information platform is paid attention,Eric Schmidt(2006) put forward his concept of computing cloud. Hassan (2011) and Peter Mell (2011) pointed out it is a model for enabling ubiquitous, on-demand access to a shared pool of configurable computing resources [7,8]. Boloni L and Turgut D (2016)[9] considered applications where the output quality increases with the deployed computational power, and proposed the value of information based scheduling of cloud computing resources that considers both the financial cost of the computation and the predicted financial benefit of the output.

As for logistics information platform,Mats Abrahamsson, Niklas Aldin Fredrik Stahre(2003)[10] defined the logistics information platform and pointed out that logistics information platform is a very important part in the logistics information system, logistics information center is the management and control of the operation of logistics information platform can effectively enhance the enterprise flexibility good. Choy KL, So SCK,Lau HCW and some other scholars (2006)[11] put forward Integrated Logistics Information Management System (ILIMS) to solve inefficient problem in the small and medium-sized 3PL facilitators. Marinagi C, Trivellas P, Sakas DP(2014)[12] explored the impact of Information Technology (IT) practices on building competitive advantage throughout the supply chain. Bae HS(2016)[13] verified the moderating effect of logistics information systems (LIS) on inter-organizational collaboration (IOC) and performance. However, these researches are merely theoretical analysis how the logistics information platform impact on logistics rather than actually the construction of the logistics information platform.

In order to satisfy the service demand of intelligent logistics,this paper designed an intelligent logistics platform containing the main applications such as e-commerce,self-service transceiver,big data analysis, path location and distribution optimization.

Based on the literature review and research projects, this study takes intelligent logistics for example to design and do implementation of cloud platform with the development of ICT and the trend of intellectualization [14,15,16].The intelligent logistics platform is a collaborative platform which comprehensively utilizes integrated information technology and intelligent technology to provide integrated logistics services, and to solve problems in logistics efficiently [17,18]. The construction of intelligent logistics information platform can be conducive to solve the long-standing logistics business independent operation of each other and the lack of integration in this industry, and also can avoid the repeat construction of self-built logistics business subject information platform [19].

With the technology development, it can be believed that the operational benefits and potential savings from clouds are too great to ignore [20]. Cloud-based platforms are inherently collaborative and accessible, creating major benefits for companies that deal routinely with thousands of suppliers [21].Meanwhile, cloud-based collaboration offers a collaborative framework with centralized storage and contact points, fewer visibility barriers, and the opportunity to enact simplified, standardized processes [22]. Thus, the intelligent logistics information platform should be built by the integration of cloud computing,big data and Internet of thing [23,24,25,26],and not only the service model, the framework of logistics information platform, but also how to construct and implement it by the core technology facing the intelligent service will be innovatively put forward in application.

II. THE SERVICE MODEL OF INTELLIGENT LOGISTICS INFORMATION

2.1 The common service on cloud platform

The common service on cloud platform can be designed to collect, store and handling multisource heterogeneous mass data from mass sensors, RFID electronic tag[27], vehicle terminals, navigation, positioning terminals and mobile phone APP in logistics distribution,and provide the open-access cloud services including distribution, positioning, navigation,scheduling, resource and other data services for the logistics distribution applications based on the technology of relational database and NoSQL big data storage[28]. Based on the database service interface of common service cloud platform, the complexity and technical difficulty of the application development can be reduced, and the operational requirements can be quickly satisfi ed.

In general, the common service platform can access, store and analyze the huge amounts of heterogeneous data from different terminals. With the data sharing and interacting among the cloud platform, kinds of open applications can be provided to satisfy the different service demand in city logistics distribution, such as self-service transceiver,E-commerce system, big data analysis, delivery resource allocation and so on. Moreover,the application function of the cloud platform can be expanded according to the mode of PaaS or SaaS, to customize cloud services for different clients.

2.2 The application service for the smart city logistics

The intelligent cloud platform includes different application system, terminal App and third-party system interface to support the data interaction and intelligent information service.Take smart city logistics for example, there are four main application system facing with the demand of smart city logistics service, as is shown in figure 1.

Fig. 1 The service model of intelligent logistics information platform

2.2.1 Intelligent express self-service transceiver application system

Intelligent express self-service transceiver application system is an intelligent platform focusing on the last kilometer express industry service. By the Internet of things and cloud platform, this intelligent device can provide express generation transceiver and temporary hosting service for individuals, which can reduce the manpower cost, improve the efficiency of delivery and solve the existing problem of last kilometer completely.

2.2.2 O2O (Online to Oラine) E-commerce system

Facing with the clients gathering in the intelligent express self-service terminals, the O2O(Online to Offline) E-commerce systems can provide a whole set of O2O solution to community, school or office business circle, a full range of shopping service such as the online shopping transaction and offline logistics distribution due to the advantage of container distribution.

In addition, the intelligent cloud platform can combine with crowdsourcing model, adopt the piggyback service by the way in the last kilometer distribution to enlarge the service radius of self-service transceiver.

2.2.3 Big data analysis system based on the community service

Big data analysis system, which is used to do the data flow analysis of the enterprise marketing strategy can provide reliable precision through massive user data acquisition, and then locate user behavior precisely, to draw up intelligent and personalized service plan for the community users. It can also provide reliable data to support the property management and business circle operation through the analysis of massive data to predict the behavior of the community users in advance [29,30].

2.2.4 Path location and distribution optimization applications

According to the demand of reestablishing express logistics distribution network in smart city, the platform will include the path location and distribution optimization applications to determine number and location of the nodes of the logistics distribution network. The optimal distribution route, from city distribution center to downtown distribution sites and the self-service center, can be confirmed by mathematical model and algorithm designed using distribution resources in the logistics distribution system, large delivery car, small electric distribution, in accordance with the daily number of express parcel.

Routing selection and distribution optimization application can realize the optimal scheduling and rational utilization of e-commerce and logistics distribution resources, reduce logistics cost and improve the efficiency of logistics distribution [31].

2.2.5 The open interface and App

The standard interface could be developed to link, interact and share the data between the cloud platform system and the third party system like e-commerce, the third party company and the logistics center. These interface is open to develop new application whose development progress can be accelerated based on cloud platform.

The terminal App can be developed facing with a complete set of services including the express delivery, O2O e-commerce applications, data analysis, community shopping for the users. More accurate delivery can be finished by the smart location system based on the open platform.

III. CONSTRUCTION AND OPERATION OF CLOUD PLATFORM

3.1 The architecture of intelligent logistics cloud platform

Like other general platform, the architecture of intelligent logistics cloud platform mainly consists of software services layer (SaaS, Software as a Service), platform layer (PaaS, Platform as a Service) and infrastructure (IaaS,Infrastructure as a Service) as shown in figure 2. Software layer (SaaS) is to provide common basic service for the third party, which can encapsulate service capacity, open service applications like the big data analysis to a third party, call open interface service directly through the standardization of web services/REST. Platform layer (PaaS) is to provide customizable cloud service middleware such as data processing engine and access control for various logistics applications through the rapid development, diversification of application,and customized extensions [32]. Infrastructure layer (IaaS) is to provide the required computing and storage resources for the middle tier or the user through virtualization technology such as data storage, computing service and resource pooling, so as to realize the allocation of resources and rapid deployment[33,34,35,36].

However, different from the former research, the construction of intelligent logistics platform based on cloud computing is not just the architecture or the business model of the intelligent service. It needs to conquer the technology difficulties to realize the high concurrent processing capability of the dynamically scalable resources, the strong capability of calculation and mass data processing.

Fig. 2 The architecture of intelligent logistics cloud platform

3.2 The core technology of building intelligent logistics cloud platform

3.2.1 High concurrent processing technique

The intelligent logistics cloud platform is to provide basic data services and application services for intelligent distribution, which will support millions of registered users and concurrent terminal access. Security platform can be sustained and stable to provide large-scale concurrent terminal access, data access and the invocation ability of basic service by the cloud computing technology in order to meet big concurrent processing and continuous reliable operation of the platform.

For a variety of large data storage and access in the city logistics, the data management means of relational database, distributed database cluster, real-time database cluster will be used. As for the cloud computing technology,distributed cluster architecture is the key to solve the concurrent processing and system for reliable operation. All nodes in cloud computing cluster have the independent and assimilate service ability. When a node in the cluster fails, it will not affect the normal operation of the other nodes, but guarantee sustained and stable operation. In addition, because of the cloud cluster, any node can provide service independently external. Therefore, the cloud cluster’s ability can be increased to handle big concurrent requests, and concurrent terminal access, data access, basic service call request by expanding the scale of the cluster.

Fig. 3 The mechanism of data access on the cloud platform

3.2.2 Heterogeneous terminal data access Heterogeneous terminal data access is the channel of data interaction between cloud platform and sensor network layer, which has its specific functions that get access to collection terminals, collect terminal state, send control information to terminal, and provide unified terminal control interface both inside and outside. At the same time, data access services can provide other external information data sharing service including traffic control request from the regulators, meteorological data services, enterprise information system services, illegal data services, the third party data services and so on. If there are new information systems needing to access to cloud platform by a third party, the data access can be designed according to extension mechanism based on the technology of data access to achieve information sharing and interaction.

There are six core modules in the data access service, as is shown in the figure 3.

The kernel manager, as the hub of the whole system, is responsible for the data source runtime instance, release runtime instance, the operation of data points observer instance and event, and basic operation process.

Data monitor, as the core function of the system, is responsible for establishing communication connection with external data sources according to the specific agreement instance, gathering the external data source status information, and collecting the status of information service in the kernel manager and data analysis service subsystem.

Fig. 4 Encrypted technology

Data dissemination is responsible for releasing the data collected by data monitor to external systems or releasing rest interface for external system to access data.

Event manager is responsible for the definition of the type of event, such as system events, data source event, publishing events,timing and maintenance events. The trigger and processing of events mainly refer mail processing way, set point processing method and execute instruction approach.

configuration tool is responsible for the design management tool, the configuration model instance, including the configuration of data source model, data dissemination model, event model, report model system settings, and so on.

3.2.3 Encapsulation and open technology To reduce the complexity of the implementation, the business system and service functions can be built separately. The service functions can be encapsulated through Web Service interface by App engine, to provide call interface for kinds of terminal capacity, including the location alarm, telephone announce,vehicle control, task management, terminal management, information collection, multimedia and data processing. By the technology of encapsulation as is shown in figure 4, the business can be responded quickly and accurately through the upper-level application system.

As for the open technology, the application service engine provides a unifi ed open-access service interface to the business system. For the type of long transaction business, the application service engine interface will call distributed processing service framework to respond the request; For most types of the high concurrency and short transaction business,the process scheduling service framework will be called.

3.2.4 The technology of data storage and data mining service

On the intelligent logistics cloud platform,the express delivery system of large heterogeneous data service engine can encapsulate the underlying data storage and provide a unifi ed data query and storage interface for the application of intelligent logistics service.

Data service engine will achieve the efficient access to structured and unstructured data, and the distributed parallel computing services can ensure the feasibility and efficiency of large-scale data processing, with the pluggable mining algorithm providing a simple and feasible way for the expansion of the function of the system. To handle the massive amounts of data in the intelligent logistics service, the platform should be designed with an data service engine with the basic modules of data scheduling , data caching, data access and data mining , as is shown in figure 5.

Data scheduling module takes charge of supplying the data access interfaces to the external and to coordination with other modules to supply the business data services. When the business data request was accepted, the data scheduling module can use the overload checking interface to check the overload and refuse the overloaded request or continue to access the data. And then call data access interface of the data cache module. If the data operation results are returned by data cache module, it can return the response to the client. If the false result appears, the data access module can be called.

Data-caching module can store a lot of high frequency data in the internal storage to improve the concurrency value of data access,and clear data not frequently used from the cache on the premise of ensuring the synchronization with the data access module. When the cache space is insuffi cient, the infrequently used data has to be cleared. In addition, data-caching module can synchronize the data in data scheduling module. There are two directions to synchronize，one is from the data scheduling module to data accessing module,anther is from the data accessing module to data scheduling module. For censored data, using the former can synchronize in the configured frequency while for the query data, using the latter to synchronize the temporary data which may loss due to the restart of the process, and then the query data should be synchronized by the data accessing module. The data-caching module can satisfy the demand of the query and writing of large volumes of data. The process control subsystem can control the request of data access according to the system resource like CPU and internal storage that refuse the quest which exceed overload control valve, and return the failure response to the clients.

Fig. 5 Data service engine structure

Data accessing module is to encapsulate database and file, which can support relational data base like Informix, Oracle, MySQL and kinds of NoSQL data base like HBase. It can shield the differences between different databases to provide the unified interface. There is the interface among data access module, data scheduling module and data cache module.The interface between data access module and data scheduling module is responsible for the data access function, which can be called to operate the database or file directly when the data cache module fails to access the data.The interface between data access module and data cache module is responsible for the data synchronism. For the data writing in the database, the data access module returns the execution result after receiving and executing SQL. For the data reading from the database,the data access module returns the query result to the data caching module after receiving and executing SQL.

Data mining module is still an effective tool for handling data including big data.There are a large number of data collected on the cloud platform, which can reflect lots of important information. Simple query and statistics cannot be able to meet the needs of the business, so the data mining, a means of mining hidden knowledge of data that can explore the knowledge from database or distributed file system, is essential to support the decision making. Data mining mainly depends on the distributed parallel computing services and plug-in development mining algorithm to process huge amounts of information [37,38].Data service engine will achieve the efficient access to structured and unstructured data,the distributed parallel computing services can ensure the feasibility and efficiency of large-scale data processing, and the pluggable mining algorithm provides a simple and feasible way for the expansion of the functions of the system. Likewise, visualization analysis of multidimensional data can be used as a powerful tool of detection data in the hidden information. Through human-computer interaction, it can make full use of human strong perception and association ability, combined with domain knowledge and convert the data structure of graphics presented to useful information. Using visualization technology can not only realize data visualization, but also give people visual impression by the result of data mining visualization at the same time.So the users and business analysts can use a variety of business intelligence front rendering tools to connect to the cube for ad-hoc queries,or publish to the Web for end-users to browse by developing visual statement such as dashboards and scorecards.

IV. THE IMPLEMENTATION OF CLOUD COMPUTING SERVICE

4.1 The mode of cloud computing service

Facing with the diversification of delivery service for different third party logistics companies, the common basic services and intelligent logistics application on the cloud platform can be designed to provide service separately.

The common basic service platform can access the huge amounts of heterogeneous terminals concurrently, store and analyze the huge amounts of heterogeneous data. Furthermore, it can also provide kinds of common applications to satisfy the business demand for the collaborative distribution of city express,consisting of express delivery buffet, dynamic task allocation for delivery staff, delivery resource allocation, real-time query and trace of distribution state, and financial settlement of delivery charge.

The intelligent logistics application platform can operate synergistically with third party logistics system and e-commerce sys-tem. By building the information exchange mechanism with these system, it is in need to provide the extended interface to satisfy more demand of services because of intellectualization.

4.2 Mechanism of cloud computing service

On the one hand, the intelligent logistics service platform can use SaaS (Software as a Service) mode, to provide distribution cloud services for the third party delivery agencies,including the features of express delivery to receive, tasks dynamically allocated for delivery staff, intelligent deployment of resources distribution, real-time query and trace back of distribution status, delivery fee settlement, reverse order and so on. And all the services can be used as needed and paid according to the usage [39].

On the other hand, the intelligent logistics service platform also uses PaaS (Platform as a Service) mode, to customizable cloud services middleware. Various applications based on the cloud services middleware can be rapidly developed to realize the diversification and customized extension. The function of the platform can be expanded by the basic middleware, and the efficiency of application entering into the market can also be improved.

V. CONCLUSIONS

The rise of intelligent cloud platform is more than just another platform shift that gets geeks excited. It is not only required from Chinese government work report in March 2017, but also the development of ICT industry in need,which will change the ways to working and service operation.

In order to satisfy the current demand from the intelligent logistics, the intelligent logistics service platform based on cloud computing can be built to collect, store and handling multi-source heterogeneous mass data from sensors, RFID electronic tag, vehicle terminals, positioning terminal and APP, and also provide the open-access cloud services including distribution, positioning, navigation, scheduling and other data services for the logistics distribution applications. And intelligent logistics cloud platform containing software layer (SaaS), platform layer (PaaS)and infrastructure (IaaS) can be constructed accordance with the core technology including high concurrent processing technique, heterogeneous terminal data access, encapsulation,and data mining.

Contributions of the intelligent logistics cloud platform construction may also be made.It is available for the different services and enterprises connected through technical innovation, and the development of the third-party logistics enterprises can be promoted towards specialization through industrial linkage. In addition, it can make good use of resources through the optimization of supply chain based on the unified platform. Furthermore, it is more comprehensive, visual and customized in application that can be formed by the information service of different activities. In these ways, intelligent logistics cloud platform can be contributive to accelerate the construction of the symbiotic win-win logistics ecological system and the benign development of the ICT industry in the trend of intellectualization in China.

ACKNOWLEDGEMENTS

This research was supported in part by National Key Research and Development Program under Grant No. 2016YFC0803206 and China Postdoctoral Science Foundation under Grant No.2016M600972 .

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