Angus F. M. Huang

An optimal QoS-based Web service selection scheme

Quality-of-service (QoS) in Web services encompasses various non-functional issues such as performance, dependability and security, etc. As more and more Web services become available, QoS capability is becoming a decisive factor to distinguishing services. This study proposes an efficient service selection scheme to help service requesters select services by considering two different contexts: single QoS-based service discovery and QoS-based optimization of service composition. Based on QoS measurement metrics, this study proposes multiple criteria decision making and integer programming approaches to select the optimal service. Experimental results show that the scheme is not only efficient, but also works well for complicated scenarios.

Improving End-User Programming with Situational Mashups in Web 2.0 Environment

Mashups is an emerging technology on the Web 2.0. Users can propose favorite preferences and compose various widgets in a mashboard. The mashups selection can be performed dynamically identifying the situational set of widgets available at runtime. In this context, there are dynamic changes in user situation, defined as the configuration of accessible widgets depending on user location and schedule. The development of situational mashups requires mechanisms to interpret user context and to mash-up widgets. We propose a system including context representation, situation reasoning, workflow planning, and mashups optimization, called SituMash, capable of supporting the automatic composition of widgets in response to situation changes without user manual selection. Experimental results demonstrated that the system possess effective capabilities in composition-time, ease-of-use and usefulness.

A Context-Driven Content Adaptation Planner for Improving Mobile Internet Accessibility

This paper presents our design and development of a context-driven content adaptation planner, which dynamically transforms requested Web content into a proper format conforming to receiving contexts (e.g., access condition, network connection, and receiving device). Aiming to establish a semantic foundation for content adaptation, we apply description logics (DLs) to formally define context profiles and requirements and automate content adaptation decision. In addition, the computational overhead caused by content adaptation can be moderately decreased through the reduction of the size of adapted content.

A Multiple Objectives Optimization Approach for QoS-Based Web Services Compositions

While a lot of Web Services are available nowadays, Quality-of-Service (QoS) becomes a crucial concern to distinguish alternatives from each other. QoS-based service composition aims to determining optimal combinations among exponential candidates with consideration of overall non-functional performance. In this paper, a multiple objectives optimization approach is proposed for the decision-making process. First, we design a pattern-wise replacement method to derive composite QoS objectives of a given XML-encoded workflow process. According to the process descriptions, the composite QoS objectives will be available by synthesizing non-functional metrics of primitive patterns repeatedly. Second, we employ the ε-Pareto dominance relations to discriminate the overall QoS performance of combinations. Thus user can freely set any desirable ε values to define the precision of service composition’s QoS performance. Finally, we present a genetic algorithm to find out the optimal combinations through evolutionary computation. The experimental results have shown that the proposed approach is more efficient and effective in terms of user-defined ε values for different QoS objectives.

Information password recovery with GPU

The protective techniques of WINZIP files include compressing the original document and encrypting the AES key. If we want to decrypt the WINZIP file, we require very large computing power and techniques of reducing the password space. In this paper, we have developed a GPU-based parallelized computing system to quickly find out the correct password, and the new system can make parallel decryption, decompression and plain text recognition for encrypted WINZIP files by using OpenCL computing technology on graphics cards ATI 6990 and NVIDIA GTX 690. The experimental results have shown that the speed of the GPU-based parallelized computing system increases about 5,670 password/second (depends on the graphics card ATI 6990) compared to sequential execution on the Intel Xeon X5650.

SOA-BASED CONTENT DELIVERY MODEL FOR MOBILE INTERNET NAVIGATION

This paper presents a Service Oriented Architecture (SOA)-based content delivery model to facilitate mobile content delivery. The main contribution of this paper is the design and development of an SOA-equipped content delivery system based on a context-driven, access-controlled, profilefavored, and history-maintained (CAPH) model. We embody the generic model-view-controller (MVC) model to support a dynamic content adaptation technique based on mobile users’ contextual environments. Self-adaptable presentation objects and modules are modeled as universal Web services resources, so that their interactions are formalized into Web services operations for high interoperability. Experimental results demonstrate that our proposed SOA-based model makes it easy to configure and construct a flexible Web content delivery system on the mobile Internet.

Collaborative Search Research in College Computer Courses

The Internet has become the most important information source for students; however, most students lack adequate search processes and search abilities when solving problems using Web search. Current Web search with a single-user environment does not require students to seek assistance in solving their problem. Therefore, how to use information problem solving model to help students solve problems is an emerging issue, and integrated collaborative Web technologies with a suitable model is a key solution. We propose a novel collaborative search system, and it develops the knowledge base of an expert system by organizing the problem of the students. The experimental data were conducted with 36 students at a college school in Northern Taiwan. The results show that collaborative search benefits college student information gathering and improves search processes and search abilities.

A Privacy Reinforcement Approach against De-identified Dataset

Protection of individual privacy has been a key issue for the corresponding data dissemination. Nowadays powerful search utilities increase the re-identification risk by easier information collection as well as validation than before. Despite there usually performs certain de-identified process, attackers may recognize someone from released dataset with which attacker-owned information is matched. In this paper, we propose an approach to mitigate the identity disclosure problem by generating plurals in a given dataset. The approach leverages decision tree to help selection of quasi-identifier and several masking techniques can be employed for privacy reinforcement. In addition to different privacy metrics applicability, the approach can achieve better trade-off between data integrity and privacy protection through flexible data masking.

Model, Properties, and Applications of Context-Aware Web Services

Context-aware Web services is a seamless interaction between service requestors and services considering both contextual requirements of services and contextual conditions of the service requestors. We envision that providing context-aware Web services is the first step toward the ultimate goal of e-services by delivering right services from right partners at right time. This chapter aims for the models, properties, and applications of context-aware Web services by developing an ontology-based context model, and identifying context-aware applications as well as their properties. We have developed an ontology-based context model to enable formal description and acquisition of contextual information pertaining to service requestors and services. The context model is supported by context query and phrased acquisition techniques. We will also report three context-aware applications built on top of our context model as a proof-of-concept to demonstrate how our context model can be used to enable and facilitate in finding right services, right partners (collaborators), and right information (content presentation).