Service Encapsulation Research Articles

Phoenix: A Live Upgradable Blockchain Client

Blockchain is an important supporting technology for various sustainable systems. It relies on a number of distributed nodes running blockchain client software, which is responsible for some critical tasks, such as communicating with other nodes and generating new blocks. However, the quick evolution of blockchain technology brings crucial challenges to blockchain client design. After carefully examining existing blockchain client software, we have identified a critical weakness: Blockchain clients are weak in supporting live upgrades, resulting in a blockchain fork that incurs security concerns and risks. In this paper, we propose Phoenix, a novel blockchain client design that is live upgradable. Phoenix uses blockchain service encapsulation to decouple blockchain services. Based on service encapsulation, we propose a live upgrade scheme that packs upgrade codes into blockchain transactions and uses a Just-In-Time engine to avoid service interruption. A parallel execution engine is developed to increase service efficiency. We evaluated Phoenix on a 51-node blockchain, and experimental results show that Phoenix outperforms existing solutions in overhead and upgrade latency.

Monitoring Land Cover Change by Leveraging a Dynamic Service-Oriented Computing Model

Land cover change (LCC) is increasingly affecting global climate change, energy cycle, carbon cycle, and water cycle, with far-reaching consequences to human well-being. Web service-based online change detection applications have bloomed over the past decade for monitoring land cover change. Currently, massive processing services and data services have been published and used over the internet. However, few studies consider both service integration and resource sharing in land cover domain, making end-users rarely able to acquire the LCC information timely. The behavior interaction between services is also growing more complex due to the increasing use of web service composition technology, making it challenging for static web services to provide collaboration and matching between diverse web services. To address the above challenges, a Dynamic Service Computing Model (DSCM) was proposed for monitoring LCC. Three dynamic computation strategies were proposed according to different users’ requirements of change detection. WMS-LCC was first developed by extending the existing WMS for ready-use LCC data access. Spatial relation-based LCC data integration was then proposed for extracting LCC information based on multi-temporal land cover data. Processing service encapsulation and service composition methods were also developed for chaining various land cover services to a complex service chain. Finally, a prototype system was implemented to evaluate the validity and feasibility of the proposed DSCM. Two walk-through examples were performed with GlobeLand30 datasets and muti-temporal Landsat imagery, respectively. The experimental results indicate that the proposed DSCM approach was more effective and applicable to a wider range of issues in land cover change detection.

A service encapsulation method of NC machine tool resources in cloud manufacturing

NC machine tool resources are important manufacturing resources in cloud manufacturing. How to carry out semantic description and service encapsulation of heterogeneous, decentralized and autonomous NC machine tool resources is one of the key technologies to realize the cloud manufacturing mode to the workshop level. In order to solve the problems such as encapsulation complexity and lack of specification in the process of service encapsulation of NC machine tool resources in cloud manufacturing, this paper first analyzes the basic attributes, functional attributes and other attributes of NC machine tool resources in cloud manufacturing. Then, a semantic description method of NC machine tool resources based on XML language is proposed. Finally, a service encapsulation method of NC machine tool resources based on JAX-WS is put forward.

State prediction and servitisation of manufacturing processing equipment resources in smart cloud manufacturing

For enabling the manufacturing processing equipment resources to intelligently perceive their own operating state, this paper proposes an integrated prediction method, in which by combining the clustering ability of SOM and the classification ability of BP together, an integrated intelligent prediction model with the ability of both qualitative and quantitative analysis is defined and used to realise the accurate prediction of operating state. Next, the service encapsulation specification for the various algorithms and model in this method are given. They are encapsulated as a set of cloud services and then published to the smart cloud manufacturing service platform, so as to enable the virtualised resources combine their own processing ability and the intelligent perception ability of these cloud services together by carrying out service composition. The above process realised the networking, servitisation, and intellectualisation of manufacturing processing equipment resources. Finally, the experimental results demonstrate the effectiveness of the proposed method.

State prediction and servitisation of manufacturing processing equipment resources in smart cloud manufacturing

For enabling the manufacturing processing equipment resources to intelligently perceive their own operating state, this paper proposes an integrated prediction method, in which by combining the clustering ability of SOM and the classification ability of BP together, an integrated intelligent prediction model with the ability of both qualitative and quantitative analysis is defined and used to realise the accurate prediction of operating state. Next, the service encapsulation specification for the various algorithms and model in this method are given. They are encapsulated as a set of cloud services and then published to the smart cloud manufacturing service platform, so as to enable the virtualised resources combine their own processing ability and the intelligent perception ability of these cloud services together by carrying out service composition. The above process realised the networking, servitisation, and intellectualisation of manufacturing processing equipment resources. Finally, the experimental results demonstrate the effectiveness of the proposed method.

A cloud service platform integrating additive and subtractive manufacturing with high resource efficiency

Abstract Cloud manufacturing has been studied for years, yet commercial implementations are still limited. The recent advances in information technology have stimulated the free sharing of additive and subtractive manufacturing (A/SM) resources through cloud services. Currently, due to the lack of a general method to model manufacturing capabilities, as well as the absence of an open platform to integrate business and manufacturing processes, it is difficult to integrate A/SM resources within one platform efficiently and seamlessly. In this research, a service encapsulation model for A/SM resources was described using ontology modeling technique. A collaborative cloud platform integrating A/SM was designed that can provide optimal production plans considering time, cost, quality, and energy waste during manufacturing. The proposed platform and models were demonstrated by a prototype system and tested in a case study, which showed the integrated platform can increase the utilization rate of resources while reducing energy consumption. This research has provided a practical tool for virtualization, integration, and configuration of A/SM resource with high efficiency.

A Web Service-Oriented Geoprocessing System for Supporting Intelligent Land Cover Change Detection

Remotely sensed imagery-based change detection is an effective approach for identifying land cover change information. A large number of change detection algorithms have been developed that satisfy different requirements. However, most change detection algorithms have been developed using desktop-based software in offline environments; thus, it is increasingly difficult for common end-users, who have limited remote sensing experience and geographic information system (GIS) skills, to perform appropriate change detection tasks. To address this challenge, this paper proposes an online geoprocessing system for supporting intelligent land cover change detection (OGS-LCCD). This system leverages web service encapsulation technology and an automatic service composition approach to dynamically generate a change detection service chain. First, a service encapsulation strategy is proposed with an execution body encapsulation and service semantics description. Then, a constraint rule-based service composition method is proposed to chain several web services into a flexible change detection workflow. Finally, the design and implementation of the OGS-LCCD are elaborated. A step-by-step walk-through example for a web-based change detection task is presented using this system. The experimental results demonstrate the effectiveness and applicability of the prototype system.

A Configurable WoT Application Platform Based on Spatiotemporal Semantic Scenarios

With the transformation of Internet of Things to Web of Things (WoT), a variety of applications are required to deal with huge volumes of real-time and heterogeneous data. However, in most applications, due to the weak semantics of data itself and the loose combination with specific scenarios, it is sometimes difficult to depict the spatiotemporal feature of the scenario in an application only through the data. In this paper, a spatiotemporal semantic scenario meta-model-based configurable platform is proposed for the development of WoT applications to address this issue, based on the data configuration, event stream configuration, and service encapsulation, the entire WoT scenario can be depicted with an abstract data model and related rules, and the business process can be changed by redefining corresponding rules when requirements change. A case study is given to verify the feasibility of our platform. The result shows that the platform can provide background support for WoT applications in a promising way.

Collaboration impact on social well-being for business sustainability: a case study of a Malaysian water treatment SME company

This study demonstrated how collaboration advances the manufacturing-based industry to transform its business structure as a social service-oriented and well-being solution, thereby being able to sustain its business vis-a-vis market competition. Thus, this paper presents an approach for industry analysis from the corporate collaboration rationality perspective. The study was performed in the Malaysian water management service industry and examined the operations of a small and medium-sized enterprise (SME) water treatment company as a case example. Data were gathered by conducting an explorative questionnaire survey with the SME water service provider in Kedah, Malaysia. Potential scenarios were identified for establishing viable future directions of SMEs, which include the needs of mutual corporate collaboration for service encapsulation, and ecosystem oriented approach for social welfare value creation. This research can help overcome the managerial challenges of a company, thus enable it to succeed in the commercial market by ensuring service-oriented social well-being solutions.

IIHub: An Industrial Internet-of-Things Hub Toward Smart Manufacturing Based on Cyber-Physical System

Smart manufacturing is increasingly becoming the common goal of various national strategies. Smart interconnection is one of the most important issues for implementing smart manufacturing. However, current solutions are not tended to realize smart interconnection in dealing with heterogeneous equipment, quick configuration and implementation, and online service generation. To solve the issues, industrial Internet-of-Things hub (IIHub) is proposed, which consists of customized access module (CA-Module), access hub (A-Hub), and local service pool (LSP). A set of flexible CA-Modules can be configured or programed to connect heterogeneous physical manufacturing resources. Besides, the IIHub supports manufacturing services online generation based on the service encapsulation templates and also supports quick configuration and implementation for smart interconnection. Furthermore, related smart analysis and precise management have the potential to be achieved. Finally, a prototype is given to illustrate the functions of the proposed IIHub, and to show how IIHub realizes smart interconnection.

Cloud manufacturing based service encapsulation and optimal configuration method for injection molding machine

This paper aims to introduce the concept of cloud manufacturing (CMfg) in the injection molding industry. The CMfg platform for injection molding enterprises is built to improve the sharing, circulation and integration of the injection molding resources. With the implementation of the Internet of Things technologies in the traditional injection molding shop, the real-time manufacturing information of resources can be accurately captured and the entire molding process becomes more visible and traceable. The virtual machining service of the injection molding machine is encapsulated as a cloud service that published into the platform for on-demand use. When task orders are published, through the presented task-driven proactive service discovery method, competent services can be quickly found. The custom-oriented evaluation method based on technique for order preference by similarity to ideal solution is designed to help the demanders to find satisfying services according to their customized criteria. Since the task orders arrive dynamically, after these orders are assigned to the specified machine, a real-time order dispatching mechanism is developed to provide an optimal scheduling plan for the cloud service. Finally, the proposed framework and methods are illustrated by a numerical simulation.

Research on Task-focused Massive Multi-source Heterogeneous Information Sharing & Utilizing Method

Nowadays the famous search engine companies are all providing the keyword web search capabilities. No one provides the high accurate & efficient user-requirements-oriented information Services. The task-focused massive multi-source heterogeneous information sharing & utilizing method and system is introduced in this paper. This paper presents the general metadata description model of heterogeneous information resource, the metadata extraction method of information resource, the service encapsulation method and registration publication mechanism of information resource, in order to standard the sharing process of large amounts of heterogeneous information resource. And then, the implement mechanism of information collection and index construction for huge amounts of information resource is given in the paper, by designing the optimized algorithm based on the map-reduce mechanism. Finally, the task-focused massive multi-source heterogeneous information precision searching mechanism is given in the paper in order to realize the information sharing and effective user of resources.

A method of demand-driven and data-centric Web service configuration for flexible business process implementation

ABSTRACTFacing the rapidly changing business environments, implementation of flexible business process is crucial, but difficult especially in data-intensive application areas. This study aims to provide scalable and easily accessible information resources to leverage business process management. In this article, with a resource-oriented approach, enterprise data resources are represented as data-centric Web services, grouped on-demand of business requirement and configured dynamically to adapt to changing business processes. First, a configurable architecture CIRPA involving information resource pool is proposed to act as a scalable and dynamic platform to virtualise enterprise information resources as data-centric Web services. By exposing data-centric resources as REST services in larger granularities, tenant-isolated information resources could be accessed in business process execution. Second, dynamic information resource pool is designed to fulfil configurable and on-demand data accessing in business process execution. CIRPA also isolates transaction data from business process while supporting diverse business processes composition. Finally, a case study of using our method in logistics application shows that CIRPA provides an enhanced performance both in static service encapsulation and dynamic service execution in cloud computing environment.

A Cloud Manufacturing Architecture for Complex Parts Machining

Service provider (SP) know-hows are essential in machining service (MS) encapsulation in the cloud. However, since the acquisition of the know-hows for complex parts machining requires investing considerable manpower and resources in R&D, this kind of machining know-hows is usually considered as one of the core competences of the SP who makes them unshareable. Targeting the problem, this paper presents a new cloud manufacturing (CM) architecture in which MSs are encapsulated within each SP with standardized machining task description strategies (SMTDS). Only the capability information about what the SP can do is provided to the cloud. During service matching, SMTDS is also applied for user request formulation to improve the matching efficiency and quality. For complex parts in large size, high machining requirements, high value, short delivery cycle, and complex structures, e.g., aircraft structural parts, unacceptable machining quality or delivery delay may cause a much greater loss not only in economy. In the proposed CM architecture, to guarantee the feasibility of the MSs for complex structural parts, machining operations for the user preferred services could be generated by mapping the corresponding typical machining plans (TMP) to the part based on the dynamic feature concept to support accurate evaluations of the MSs. The machining of an aircraft structural part is then applied as a test user request to demonstrate how the proposed method works for finding MS for complex parts.

Cloud-Based Global Supply Chain: A Conceptual Model and Multilayer Architecture

The cloud manufacturing (C-Manufacturing) paradigm, as an advanced form of networked manufacturing, has recently been proposed based on a combination of existing manufacturing systems and emerging technologies, such as cloud computing, virtual manufacturing, agile manufacturing, manufacturing grid, Internet-of-things (IOT), and service-oriented technologies. In this study, through investigating the main goals of C-Manufacturing and today's hypercompetitive global marketplace circumstances, a prospective conceptual model called cloud-based global supply chain (CBGSC) has been developed which can overcome or mitigate the issues and risks associated with supply chain processes on a global scale. CBGSC extends the conventional three-tier customer–manufacturer–supplier supply chain model into a new five-tier customer–cloud provider of manufacturing applications (CPMA)–manufacturer–cloud provider of supplying applications (CPSA)–supplier model, in which the CPMA and CPSA tiers act as intermediators in order to enhance the diversity and intensity of the markets and businesses of conventional supply chain parties while securing their own profits. On the other hand, CBGSC enriches the notion of C-Manufacturing by incorporating CPSAs to safeguard smooth and continuous supply of raw materials and goods to manufacturers (physical resource providers), thus prevailing the “share to gain” philosophy within the whole network. Also, aiming to facilitate practicalizing the CBGSC, we have proposed a multilayer architecture for the CBGSC with seven layers of user, interface, application, service, resource virtualization and service encapsulation, perception, and resource, which are blended together via four basic aspects of security, optimality, resilience, and information technology (IT) and information and communications technology (ICT) infrastructure.

Research on services encapsulation and virtualization access model of machine for cloud manufacturing

Considering the new requirements of the services encapsulation and virtualization access of manufacturing resources for cloud manufacturing (CMfg), this paper presents a services encapsulation and ...

Granulation-based resource classification in Cloud Manufacturing

Cloud Manufacturing, a new manufacturing mode, has the characteristics of service-oriented, knowledge-based, high efficiency and low consumption. Resource virtualization is critical for Cloud Manufacturing, which describes physical resources as cloud services. In this article, a resource virtualization method is proposed for sharing manufacturing resources. By analyzing features of Cloud Manufacturing resources, a multilevel resource virtualization framework is constructed. A multi-granularity resource classification algorithm is presented for cloud services encapsulation, based on which physical resources are flexibly composed to respond business opportunities. Ontology, the fundamental of the proposed method, is implemented by Web Ontology Language and Semantic Web Rule Language, along with a case study validating the proposed method.

Research of the Emergence of Virtual Organizations Based on Cloud Computing Environment

In the cloud computing environment, resources of services encapsulation extend from initial computing resources to all other encapsulated social resources, such as manufacturing resources, financial resources, etc. Increasingly, services are reflecting the agent characteristics. This paper proposes that the cloud computing environment is a complex adaptive system of which the service is the service agent. With the emergence of its core, the model of interactions between service agents has been established by synthesizing theories and technologies of various disciplines like System Science, Economics, Management and Computer Science. By using the CAS theory as the technical route of cloud computing environment and its service agents, we can draw the conclusion that virtual organizations will spring up because of the combination of service agents.

SOA-Cloud Computing Based Fast and Scalable Simulation Architecture for Advanced Flight Management System

This paper presents a SOA and cloud computing based architecture for the distributed simulation of advanced flight management system (FMS). The architecture is designed to facilitate the fast simulation, validation and evaluation of different FMS system designs and functionalities with customized system configurations and widely varying aircraft equipage levels under various operation conditions. It is also intended to accommodate the potential evolutionary extensions of new avionics concepts and functionalities such as the future CNS/ATM and 4-D trajectory based technologies. To address the requirements of flexibility, scalability and reusability, the design of the simulation architecture takes advantage of the cloud computing and service oriented architecture (SOA) and the key enabling technologies are developed: simulation unit service encapsulation, simulation agent technology and simulation orchestration. Based on the proposed architecture associated technologies, the simulation components are encapsulated as services or accessed through agents, and the configuration of different FMS system frameworks and simulation tasks can be achieved through simulation orchestration. A prototype avionic simulation system that implements the SOA/cloud computing architecture is developed and illustrated with application cases. The applications demonstrate that the proposed architecture enables fast and scalable simulation of both existing and new FMS design and technologies.

Rehabilitation Management System Oriented Cloud Services Integration Technology

As the informationization of the medicare sector in China grows up and the sources of the rehabilitation data are distributed and multi-leveled from different centers, it is urgently needed to integrate the resources of various application systems, implement unified data exchange of the distributed and heterogeneous multiple data sources and encapsulate the data resources into various kinds of services. For this purpose, this paper puts forward the idea of SOA-based cloud services encapsulation and integrated architecture. At first, the multi-source and heterogeneity of data and the integration of information in the rehabilitation management are analyzed. Then, the cloud services encapsulation and integration technology is study to find out how to encapsulate data resources into various kinds of services, build a SOA-based cloud services platform, find a solution for the integration of multi-sourced and heterogeneous data, and meet the function extension, encapsulation and release of cloud services arising out of changing demands. At last, A case of the cloud platform system is presented to show the feasibility and effectiveness of the architecture platform.