Rick C.S. Chen

Applying DNA computation to intractable problems in social network analysis.

From ancient times to the present day, social networks have played an important role in the formation of various organizations for a range of social behaviors. As such, social networks inherently describe the complicated relationships between elements around the world. Based on mathematical graph theory, social network analysis (SNA) has been developed in and applied to various fields such as Web 2.0 for Web applications and product developments in industries, etc. However, some definitions of SNA, such as finding a clique, N-clique, N-clan, N-club and K-plex, are NP-complete problems, which are not easily solved via traditional computer architecture. These challenges have restricted the uses of SNA. This paper provides DNA-computing-based approaches with inherently high information density and massive parallelism. Using these approaches, we aim to solve the three primary problems of social networks: N-clique, N-clan, and N-club. Their accuracy and feasible time complexities discussed in the paper will demonstrate that DNA computing can be used to facilitate the development of SNA.

Enhancing the precision of content analysis in content adaptation using entropy-based fuzzy reasoning

Content adaptation is a well-known technique to help portable devices present Web pages as smoothly as desktops do. Because of limited I/O and weak transmission capability, adaptations are usually performed by either transcoding or resizing multimedia components. In this paper, we propose a novel semantic coherence-retained content adaptation approach, namely functionality sense-based content adaptation (FSCA). Our goal is to avoid semantic distortions when rearranging a Web page on different screen sizes. Simulating entropy-based fuzzy reasoning in human cognition, we introduce Relevance of Functionality (RoF) to quantitatively represent the similarity intensity between two presentation objects (groups) based on their functionalities. We present an algorithm of calculating RoF and a procedure that uses RoF to decide content adaptation degree. Our experiments verify the feasibility and effectiveness of FSCA.

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.

A Service Supporting Universal Access to Mobile Internet with Unit of Information-Based Intelligent Content Adaptation

In the mobile Internet, users mostly work with handheld devices with limited computing power and small screens. Their access conditions also change more frequently. In this paper, we present a novel service supporting intelligent content adaptation to better suit handheld devices. The underlying technique is a unit of information (UOI)-based content adaptation method, which automatically detects semantic relationships among comprising components in Web contents, and then reorganizes page layout to fit handheld devices based on identified Ious. Experimental results demonstrate that our method enables more exquisite content adaptation.

Efficient Usage of Network Bandwidth in the Cloud Architecture

The cloud computing emphasizes that any resources can be services provided to users. For IaaS, virtualization technologies leverage the use of hardware to serve users without complicated applying procedures. As we know, any physical resources, such as CPU, memory or bandwidth, are precious in general so that they should be used as well as possible. Many researches hence are booming aiming at performance enhancement, especially for cloud networking. The paper presents hardware and software-based concepts to let virtual machines use bandwidth of physical machines under best-effort provisioning. The result can benefit IaaS architecture running from less waste of bandwidth.