Yun Yao Chen

CLB: A novel load balancing architecture and algorithm for cloud services ☆

Abstract Cloud services are widely used in manufacturing, logistics, digital applications, and document processing. Cloud services must be able to handle tens of thousands of concurrent requests and to enable servers to seamlessly provide the amount of load balancing capacity required to respond to incoming application traffic in addition to allowing users to obtain information quickly and accurately. In the past, researchers have proposed the use of static load balancing or server response times to evaluate load balancing capacity, a lack of which may cause a server to load unevenly. In this study, a dynamic annexed balance method is used to solve this problem. Cloud load balancing (CLB) takes into consideration both server processing power and computer loading, thus making it less likely that a server will be unable to handle excessive computational requirements. Finally, two algorithms in CLB are also addressed with experiments to prove the proposed approach is innovative.

A New Approach to Integrate Internet-of-Things and Software-as-a-Service Model for Logistic Systems: A Case Study

Cloud computing is changing the ways software is developed and managed in enterprises, which is changing the way of doing business in that dynamically scalable and virtualized resources are regarded as services over the Internet. Traditional manufacturing systems such as supply chain management (SCM), customer relationship management (CRM), and enterprise resource planning (ERP) are often developed case by case. However, effective collaboration between different systems, platforms, programming languages, and interfaces has been suggested by researchers. In cloud-computing-based systems, distributed resources are encapsulated into cloud services and centrally managed, which allows high automation, flexibility, fast provision, and ease of integration at low cost. The integration between physical resources and cloud services can be improved by combining Internet of things (IoT) technology and Software-as-a-Service (SaaS) technology. This study proposes a new approach for developing cloud-based manufacturing systems based on a four-layer SaaS model. There are three main contributions of this paper: (1) enterprises can develop their own cloud-based logistic management information systems based on the approach proposed in this paper; (2) a case study based on literature reviews with experimental results is proposed to verify that the system performance is remarkable; (3) challenges encountered and feedback collected from T Company in the case study are discussed in this paper for the purpose of enterprise deployment.

Development of a multisensor embedded intelligent home environment monitoring system based on digital signal processor and Wi-Fi

Wi-Fi has been widely adopted by families in Taiwan, for it has the advantage of designing family monitoring systems with its wide usage. Therefore, there are many advantages for designing family monitoring systems. Based on our previous research architecture, we implemented a monitoring system for family environments based on Wi-Fi and sensor technologies. Humidity, gas, smoke, and temperature sensors are applied for designing and developing the intelligent home environment monitoring system in this paper. A system prototype is proposed in this research, and the experimental results are discussed. The results showed that the system is workable and remarkable for environment monitoring. The contribution of this is to propose a framework for future home environment monitoring system developers to refer to.

Design of Cloud Load Balance Architecture for Web Servers

Cloud services are widely used in manufacturing, logistics, digital applications, and document processing. Cloud services must be able to handle tens of thousands of concurrent requests and to enable servers to seamlessly provide the amount of load balance capacity needed in response to incoming application traffic in addition to allowing users to obtain information quickly and accurately. In the past, scholars proposed using static load balance or server response times to evaluate load balance capacity, both of which cause the server to load unevenly, and in this study, a dynamic annexed balance method is used to solve this problem.

Development of Software-as-a-Service Cloud Computing Architecture for Manufacturing Management Systems Based on Virtual COM Port Driver Technology

This study proposes an innovative technology of Virtual COM Port Driver applied to the SaaS cloud manufacturing system, so that user can only via a web browser to complete all operations of system. Flexibility of the system extensions, and support manufacturing enterprise use other communications equipment at work, for example RFID products, GPS receiver. Information integration, solve each computer to be fitted Middleware to read native components and retrieve information for the inconvenience. This study proposes five-layer model of cloud manufacturing system, and through the virtualization web server to achieve cloud infrastructure layer. In particular, the Virtual Com Port Driver is deployed in the cloud infrastructure layer and middleware layer, and the signal device layer can communicate directly to the cloud infrastructure layer via the web browser. Through a case study, to implement the Virtual COM Port Driver technology to verify the cloud server can capture the local COM port successfully only via the web browser and integrate the information further.

A Novel Framework for Agent-Based Production Remote Monitoring System Design: A Case Study of Injection Machines

Currently, many injection machine controllers in the market involve PC-based architecture, so engineers can conduct simple and quick operation on the controller via a human-machine interface. However, when there are too many machines in a factory, mining algorithms for multimachines and development of rear-end applications are often trivial and complicated. The operation systems of the machines in factories are different, and different machine models need different transfer protocols for data mining. Therefore, we need to develop different information platforms and machine production information mining systems for cross platform controllers. This research proposed an agent based remote monitoring system for injection machines to solve this problem. The agent-based production remote monitor system framework in this research has the following advantages. (1) It can transmit machine information cross platforms regard of constraints of different operating systems. Controlling frameworks can process data mining and transmission. (2) It can send back machine information actively to the manager without operation of machine operators, mine specific information effectively, and screen unnecessary machine information. (3) It can categorize the required information, filter extra information, and elicit data the user needs.

Design of a novel cloud-based metalworking supplier matching system

Traditionally, machine equipment manufacturers match new metalworking suppliers through yellow pages and websites, which is inefficient and not timely for supplier information transfer. In this article, a cloud-based supplier matching system is proposed to offer machine equipment manufacturers an efficient way to match suitable metalworking suppliers. A cloud architecture to enhance utilization of servers and simplified device management is designed. Two cloud services are designed in this system, including order-bidding service and order-cooperation service. A comparison result shows that the system can provide a flexible matching system for both metalworking suppliers and machine equipment manufacturers.

A Cloud Multi-Tenant Architecture for Developing Machine Remote Monitoring Systems

This study proposes innovative multi-tenant remote monitoring platform architecture based on cloud with an injection machine manufacturer as cloud data center. This study was designed to develop machine connection mechanism and monitoring module, etc. with machine manufacturers. Under the architecture of this study, machine manufacturers can provide virtualization technology based remote monitoring systems for manufacturing buyers to rapidly develop custom monitoring software. All data storage devices such as servers are provided by the machine manufacturer, and the client side can effectively manage injection machine data by simply renting virtual machine space.

A Novel Wireless Data Acquisition Infrastructure for Manufacturing Equipment Based on Wi-Fi

Production information collection is an important issue for manufacturing. Therefore, the data transmission techniques for manufacturing equipment are hot spots for researchers nowadays. Traditional equipment data transmissions are based on Ethernet, which encountered issues such as high maintenance cost and unreal-time data transmission. A wireless data acquisition infrastructure for manufacturing equipment based on Wi-Fi is designed for ensuring the data transmission quality in factories.

Design of Agent-Based Production Information Retrieval System Architecture for Injection Machines

A socket information retrieval mechanism and information retrieving agent services on the basis of injection machines is proposed in this research. The proposed agent adapted customized packet format for client-server connection communication, and sent process parameters back to production process database constructed by this Institute. The production process data of injection machines can be accessed by the agent services pro-posed in any networking environment through standard services to construct a variety of systems for machine monitoring and information analysis. If an error occurs, remote machine diagnosis can be executed at once.