An Ontology-Supported Ubiquitous Interface Agent for Cloud Computing

An Ontology-Supported Ubiquitous Interface Agent for Cloud Computing - Example on Zigbee Technique Sheng-Yuan Yang1, Dong-Liang Lee2, and Chun-Liang Hsu3 1

Department of Computer and Communication Engineering, St. John’s University, Taiwan 2 Department of Information Management, St. John’s University, Taiwan 3 Department of Electrical Engineering, St. John’s University, Taiwan {ysy,lianglee,liang}@mail.sju.edu.tw

Abstract. An ontology-supported ubiquitous interface agent and its interaction diagram with the backend information agent system, i.e., OntoIAS, in cloud computing environments were proposed. The agent employs the CURRL to transform user commands into internal canonical format to conveniently process those commands by OntoIAS, which can avoid numerous, jumbled, and incorrect information torrents that results in misunderstanding of the information intention of users. In this paper, we preliminarily proposed the agent with the Zigbee techniques and related interaction diagrams with OntoIAS in cloud computing environments. The system prototype and experimental outcomes can also reveal the feasibility of the system architecture. Keywords: Ubiquitous Interface Agent, Ontology, Zigbee, Cloud Computing.

1 Introduction With increasing popularity of computers, network techniques, and WWW, information shows the multiple appearances and huge amount explosion. Therefore, the way of helping the user to quickly, precisely, and effectively get profoundly, relevantly, and up-to-dated useful information has quickly become the critical topic that the industrial, official government, and academic groups strived for in last ten years. A variety of information retrieval tools has been thus created by information providers, including information portals, search engines, etc., which could help users to filter, search for, organize, and represent related query information. Information agents are software products for assisting and guiding users to reach the goal of information retrieval. Not only can the agent possess the four main functions: information searching, information extracting, information classifying, and information representing/ranking, but also it can really and effectively up-rise the performance of information query to the user and collocate the factors in user interfaces, network speed, amount of the backend databases, and usage scenarios. Up to now, however, most of Web information agent systems are closely related to the traditional information equipments that can not directly apply to the modern mobile equipments resulting from the core part of information agent in ubiquitous environments. This study exactly focused on how to construct a ubiquitous interface agent with mobile equipments in ubiquitous environments. J.-S. Pan, S.-M. Chen, and N.T. Nguyen (Eds.): ICCCI 2010, Part III, LNAI 6423, pp. 142–153, 2010. © Springer-Verlag Berlin Heidelberg 2010

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Cloud computing is a technique of Internet- ("cloud-") based development and use of computer technology. In other words, it will set up the necessary operating resources and related data into the Internet and then users can directly use them whenever they can access the Internet. Ubiquitous computing is a post-desktop model of human-computer interaction in which information processing has been thoroughly integrated into everyday objects and activities. Computers will exist in our lives in hidden, popularized, and ubiquitous ways. Even though many people already know we have entered a ubiquitous environment, this kind of natural interaction mode has not appeared yet. Nevertheless, there is lots of traditional equipment that is suitable for these natural interaction modes, for example, mobile phones, RFID (Radio Frequency Identification), Bluetooth, Zigbee, etc. Such devices operate through wireless sensor techniques to recognize related users and let users naturally interact with relevant network services, thus, reaching the goal of ubiquitous computing. Furthermore, how to construct an interaction diagram of cloud computing for extensively and seamlessly entering related web information agent systems through modern mobile equipments in ubiquitous environments is our major investigation. To sum up, this study focused on designing a ubiquitous interface agent based on the ontology technology and interaction diagram with the backend information agent system, i.e., OntoIAS (Ontology-supported Information Agent Shell), in cloud computing environments. The agent employs the CURRL (Canonical User Request Representation Language) to transform user commands into internal canonical format to conveniently process those commands by OntoIAS, which can avoid numerous, jumbled, and incorrect information torrents that result in misunderstanding of the information intention of users. The system creates an interaction diagram that both solves the congenital defect problems of mobile equipments and adequately elaborates the powerful functions of backend information systems. In this paper, we preliminarily proposed a ubiquitous interface agent with the Zigbee techniques and related interaction diagrams with OntoIAS in cloud computing environments. The system prototype and experimental outcomes can also reveal the feasibility of the system architecture.

2 Background Knowledge and Techniques 2.1 Ontology Ontology was one theory in philosophy and primarily to explore knowledge features of life and real objects, which can provide complete semantic models with sharing and reusing substances. To use the concept of ontology can accomplish the knowledge core in a specified domain and automatically learn related information, communication, accessing and even induce new knowledge; hence, ontology is a powerful tool to construct and maintain an information system [15]. Fig. 1 illustrates the ontology structure of Scholars, which defines related basic knowledge of scholars and its conceptual hierarchy relationship and relevant features.

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Fig. 1. The ontology structure of Scholars

2.2 Ubiquitous Computing Mark Weiser created the phrase “ubiquitous computing” around 1988, during his tenure as Chief Technologist of the Xerox Palo Alto Research Centre. This concept pointed out that the third-wave revolution of computers had already come. Computers will exist in our lives in hidden, popularized, and ubiquitous ways. The humanmachine interaction modes, which operate regardless of Command-Line, MenuDriven, or even GUI-based ones, are improper and unsuitable for ubiquitous environments. This is a clear suggestion of the necessity of more natural humanmachine interaction modes to support ubiquitous computing. There are many examples of applications in previous studies [2,7,8,9,11]. In summary, the scopes of discussion related to ubiquitous computing include Pervasive Computing, Sentient Computing, Simulated Reality, Wearable Computers, Context-Aware Pervasive Systems, Ambient Intelligence, Virtual Reality, Human-Centred Computing, etc. Relevant research contents include ubiquitous software and hardware infrastructures, protocols, components, access security, etc. There is a lack of ubiquitous research in software system applications in Taiwan, especially. The only study of its kind involving ubiquitous research on agent systems was the 2008 project that explored a ubiquitous service system with an embedded intelligent interface by Director Dr. C.C. Hsu, dept. of computer science and information engineering, Fu Jen Catholic University, Taiwan. This was an influential and significant study related to web information systems. 2.3 Cloud Computing In concept, cloud computing is an information technology that makes users utilize the information services when they can only access the Internet, and even cannot completely understand the complex information service structure and possess any professional knowledge. Cloud computing earlier borrowed from the techniques of Grid Computing and Utility Computing in the early 1990s. In the 21st century, the related network services vigorously develop based on the improvement of network techniques. In 2007, Google proposed the concept of cloud computing that also start the huge business opportunity of cloud computing, including IaaS (Infrastructure as a Service), PaaS (Platform as a Service), and SaaS (Software as a Service). It still more achieves the concept of new 3C, i.e., Cloud Computing, Connecting, and Client Devices [4].

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In this paper, we exactly investigated a ubiquitous interface agent with the Zigbee technique and related interaction diagrams with OntoIAS in cloud computing environments. That means, in cloud computing environment, the ubiquitous interface agent is responsible for the role of client device; the Zigbee technique is responsible for communication mechanism; finally, the backend information agent system, OntoIAS is responsible for the role of the provider of cloud computing. Furthermore, this study can reach the investigation goal of constructing an interaction diagram of cloud computing for extensively and seamlessly entering related web information agent systems through modern mobile equipments. 2.4 Zigbee Technique with C/C++ Zigbee explored related techniques of disorderly and unsystematic information transmission that is similar to the behavior of honey bees after return to the beehive. The Zigbee specifications of hardware and software were announced and completed by the Zigbee Alliance and the IEEE 802.15.4 standard, its protocol stack as shown in Fig. 2. It was planned to become a low-speed (250kbps), short-distance, low-power, and simple-architecture wireless mesh networking technology. Currently, ZigBee operates in the industrial, scientific and medical (ISM) radio bands; 868 MHz in Europe, 915 MHz in the USA and Australia, and 2.4 GHz in most worldwide. In the 2.4 GHz band there are 16 ZigBee channels, while the channel quantities are 10 and 1 in the 915MHz and 868MHz band, respectively. Zigbee supports the client-server and point-to-point modes and has the higher extensibility, which can simultaneously have over 65,000 device connections in a network. The main applications focus on the information transmission of home appliances automation, environment security and control, individually medical treatment, etc. [6].

Fig. 2. Zigbee protocol stack

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C/C++ is a general-purpose computer language. It is usually and popularly used to develop application software and system exploitation, which possesses characteristics of high efficiency, high flexibility, abundant functions, strong expression, high transplantation and compatibility, etc. Currently, the compiler of C/C++ universally exists in variously different operating systems, such as Microsoft Windows, Linux, UNIX, etc. [12]. In this paper, we employ the JN5121 Zigbee module of Jennic Ltd., which uses the C/C++ to develop its applications of ROM in the module and Jennic names the program Codeblocks [1]. Its main function is the code editing and compiling, and then employs the Flash Programmer to burn the compiled codes into the JN5121 module. Owing to the Codeblocks and Flash Programmer are developed by Jennic Ltd. according to the JN5121 module. The system developers must install their official drivers for application development. 2.5 Developing Techniques This system adapted MS SQL Server as backend knowledge-database sharing platform based on ontology. MS SQL Server is one broadly used relational database management system [14]. SQL (stands for Structured Query Language) is one query language to get the data in the relational database. The agent system itself was developed with Java SE and ME, and the Zigbee technology with C/C++ mentioned above. The ontology construction tool, Protégé, was an ontology freeware developed by SMI (Stanford Medical Informatics). Protégé not only was one of the most important platforms to construct ontology but also the most frequently adapted one [3]. Its most special feature is that it used multi components to edit and make ontology and led knowledge workers to construct knowledge management system based on ontology; furthermore, users could transfer to different formats of ontology such as RDF(S), OWL, XML or directly inherit into database just like MySQL and MS SQL Server, which have better supported function than other tools [16].

3 Architecture of the Ubiquitous Interface Agent and Interaction Diagram with OntoIAS To reach ubiquitous research goals of this study, users can employ the Ubiquitous Interface Agent to use the backend information agent system: OntoIAS via related mobile equipments, such as mobile phones, PDA-related equipments, lap-top computers, related equipments with Zigbee interfaces, or another related information systems that fit in with communication protocols. Therefore, the agent has to provide the communication bridge between the mobile and wireless equipments and related web information systems, as shown in Fig. 3. This must be done to satisfy the basic requirements of seamless information services in ubiquitous computing, whose related interaction diagrams contain the following actions: users key in specific information requirements to trigger OntoIAS to return query information, users directly query OntoIAS to provide commonly used hot information, etc.

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Fig. 3. System architecture of the Ubiquitous Interface Agent

In general, mobile equipments possess small screens, small keyboards, and poor system efficiency. Therefore, the system employs simple codes or hot keys to describe common or important information requirements for dealing with complex user commands. Through the techniques of packet decoding and recognizing, the Ubiquitous Interface Agent employs CURRL to transform user commands into internal canonical format to conveniently process those commands by OntoIAS, which can avoid numerous, jumbled, and incorrect information torrents that result in misunderstanding of the information intention of users. When users key in specific information queries, the agent divides the user queries into three types of commands for fast processing. The three types include Query, Simple Command, and Conditional Command. We modified FURRL (Formalized User Request Representation Language) [5] to design a CURRL to represent the above user commands. The CURRL is a frame-based command representation that makes it easy to map users’ command intentions, objects, and goals into corresponding frame slots. Table 1 illustrates some examples of user commands. Table 1. Examples of user commands with CURRL User command Query

User command What is Ubiquitous Computing?

Simple Command

Anything else?

Conditional Command

Retrieving Fuzzy webpages with the exception of AI

CURRL Query [ Theme = + Computing, aTheme = Ubiquitous, tSpace = At (WWW) ] Command [ Theme = +Anymore, tTime = Now, object = Related, oSpace = At (Last-one) ConditionalCommand [ Condition [ Theme = -Fuzzy, tTime = Now, tSpace = At (WWW) ], Command [ Theme = +AI, tTime = Now, tSPace = At (WWW) ] ]

In short, we simplify the design of the agent into a data decoding controller of related communication equipment; and then employ CURRL to transform them into an internal canonical format; finally, we trigger OntoIAS to provide information solutions. The interaction diagram can not only solve the congenital defects of the

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mobile equipment mentioned above, but can also adequately elaborate the powerful functions of the backend system, OntoIAS. The application environment of the system uses related mobile equipment and constructs them with the architecture of the World Wide Web. The operating mode adopts a three-tier architecture, including the user end, the ubiquitous interface Agent end, and the OntoIAS end. The interaction system prototype that includes the three-tier multi-agent architecture can solve the congenital defect problems of mobile equipment encounter in satisfying users’ basic information requirements in ubiquitous environments. Detailed explanations of the interaction diagrams are provided as follows: (1) The user keys in specific information queries to trigger OntoIAS to return information solutions: after the user enters his/her account, the Ubiquitous Interface Agent provides the interface for entering the information query, and then employs CURRL to transform the query into the internal query format, finally, triggering OntoIAS to process the query and return its solutions. After the user finishes browsing, the Ubiquitous Interface Agent returns relevant feedback to OntoRecommander to act as the calculation base of hot information and records them in the user’s profile; (2) The user directly queries OntoIAS to provide commonly used hot information: after the user enters his/her account, Ubiquitous Interface Agent directly triggers the OntoRecommander of OntoIAS, according to the user’s account, and returns commonly used hot information to the user. That is, the user directly uses the information but has to do nothing.

Fig. 4. Conceptualized architecture of the backend information agent system: OntoIAS

Fig. 4 illustrates the OntoIAS architecture diagram [17]. It contains the four main modules of information agents, including information searching, information extracting, information classifying, and information presenting/ranking, corresponding to OntoCrawler, OntoExtractor, OntoClassifier, and OntoRecommander, respectively. An Ontological Database (OD) is a stored structure designed according to the ontology structure, serving as an ontology-directed canonical format for storing webpage information processed by OntoIAS. Users can employ the ubiquitous interface agent to use the OntoIAS via related mobile equipments, or other related information systems fitted with communication protocols. Therefore, the proposed method can reach the

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goals of ubiquitous research. User profile databases are responsible for recording relevant user models. The system can trigger OntoRecommander to provide relatively personal information services.

4 System Display and Evaluations 4.1 System Prototype Our system is developed using C++Builder on Windows XP® Service Pack 3 of Professional Version with Intel® Core 2 Duo CPU at 2.53GHz and 2GB memory, and the Zigbee device with JN5121 (Jennic Ltd.) chip. To use Zigbee devices with other chips such as TI-CC2431 (Texas Instruments), etc., the system must install their official drivers for normal action. The system employed Java ME and SE to develop the Ubiquitous Interface to simulate the communication between cellular phones and the computer end. Because of the communication of Zigbee JN5121 module has to use the C/C++ language. For this reason, we need to develop related middle-wares; that is to go through the serial port transferred circuit via the RS232 port for connecting to Zigbee JN5121 module, as shown in Fig. 5.

Fig. 5. Front-end of the ubiquitous interface agent

By way of the front-end Zigbee JN5121 module to deliver data, the system prototype employs the back-end Zigbee JN5121 module to receive data, and then goes through the reversed operation mentioned above to connect to the back-end server system for carrying out related processes, as shown in Fig. 6. After back-end system processing, the system prototype orderly returns and presents the results into the cellphone simulator.

Fig. 6. Back-end system of the ubiquitous interface agent

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Fig. 7. Screen of client device end

The execution steps of the ubiquitous interface agent system prototype with the Zigbee technique and related interaction diagrams in cloud computing environments are explained with the ASUS cell phone P552w and detailed follows: (1) Client device end: enters the query keywords in the cell phone and assigns related search engines, the testing screen as shown in Fig. 7; (2) Connecting technology: starts the Zigbee transmitted program as shown in Table 2 and sends related query information from step 1 to the cloud computing provider OntoIAS; (3) Cloud computing end: OntoIAS starts the received program as shown in Table 3, then executes related query processes, and finally communicate the query results to the cell phone of the client through a series of Request-Response manner in the Client-Server mode, as shown in Fig. 8. Table 2. Processing procedure and related function description of the transmitted end Action Description

Related Functions

Local Device Devices Discovered Services Discovered Client Session

JZS_vStartStack JZS_vStartNetwork JZS_vJoinNetwork JZA_vStackEvent

Table 3. Processing procedure and related function descriptions of the received end Action Description

Related Functions

Local Device Devices Discovered Server Connection Server Request Handler

JZS_vStartStack JZS_DiscoverNetworks JZS_vPollParaent JZA_u8AfMsgObject

Fig. 8. Received screen

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4.2 Performance Evaluation The information recommendation means that the optimal recommendation is chosen from a group of related information sets, just like the concept of sampling. In the sampling survey domain, the reliability was generally employed to measure the degree of precision of the sampling system itself, while the validity emphasized whether it could correctly reflect the properties of the appearance of things or not. In this study, we employed the aid of a mathematic model, provided by J.P. Peter [10] in 1979, and cited by numerous other studies to represent the definitions of reliability and validity [17]. Table 5. Results of the 3 recommendations No

1

2

3

Information Recommendation Course Information Academic Activities Website Recommendation Average Course Information Academic Activities Website Recommendation Average Course Information Academic Activities Website Recommendation Average

Fuzzy Theory rtt Val 0.93 0.92 0.94 0.93 0.91 0.83 0.93 0.89 0.94 0.9 0.92 0.78 0.92 0.88 0.93 0.85 0.78 0.63 0.94 0.88 0.96 0.93 0.89 0.81

Artificial Neural Network rtt Val 0.88 0.86 0.81 0.76 0.93 0.78 0.87 0.8 0.86 0.65 0.78 0.58 0.91 0.89 0.85 0.71 0.88 0.68 0.79 0.72 0.88 0.78 0.85 0.73

Artificial Intelligence rtt Val 0.96 0.75 0.98 0.93 0.97 0.88 0.97 0.85 0.83 0.85 0.94 0.88 0.98 0.96 0.92 0.9 0.99 0.89 0.96 0.92 0.97 0.9 0.97 0.9

Table 5 illustrates the reliabilities and validities of information recommendation in different professional domains, while the total average results are shown in Table 6. The average values of reliability and validity were 0.91 and 0.83, respectively. In this experiment, we randomly chose 100 data from the personal webpages of the members of the Taiwanese Association for Artificial Intelligence to carry out different 3 separate recommending experiments. The significant information recommendation of these experiments were asserted by the domain experts, including observed values, true values, error values, and related variances. From previous technical studies [13], we know that the regular-level values of reliability and validity are 0.7 and 0.5, respectively, which verifies and validates that our experiment results have high-level outcomes of information recommendation of the proposed system. Table 6. Total average results Performance Average Reliability Average Validity

Fuzzy Theory 0.92 0.85

Artificial Neural Network 0.86 0.75

Artificial Intelligence 0.95 0.88

Total Average 0.91 0.83

5 Conclusions In this paper, an ontology-supported ubiquitous interface agent and interaction diagram with the backend information agent system in cloud computing environments were proposed. The agent adopts the CURRL to fast and precisely deal with user query commands for conveniently processing those commands by OntoIAS. The

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system also creates an interaction diagram that both solves the congenital defect problems of mobile equipments and adequately elaborates the powerful functions of backend information systems. In this paper, we preliminarily proposed a ubiquitous interface agent with the Zigbee technique and related interaction diagrams with OntoIAS in cloud computing environments. The system prototype and experiment outcomes can not only reveal the feasibility of the system architecture, but also have high-level outcomes of information recommendation. Continuously improving the performance efficiency, expanding database of ontology and its related linking interface, and developing the middle programs, for example, RFID, Bluetooth, etc., with backend systems for truly completing the wireless communication functions of the ubiquitous interface agent would be the everlasting research in the future.

Acknowledgement The authors would like to thank Ssu-Hsien Lu, Ting-An Chen, Chi-Feng Wu, and Zhe-Min Ni for their assistance in system implementation and experiments. This partial work was supported by the National Science Council, R.O.C., under Grants NSC-99-2221-E-129-012 and NSC-99-2623-E-129-002-ET, and the Ministry of Education, Taiwan, R.O.C., under Grant Skill of Taiwan (1) Word No. 0990045921s.

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