Wei-Jen Wang

Adaptive scheduling for parallel tasks with QoS satisfaction for hybrid cloud environments

A hybrid cloud integrates private clouds and public clouds into one unified environment. For the economy and the efficiency reasons, the hybrid cloud environment should be able to automatically maximize the utilization rate of the private cloud and minimize the cost of the public cloud when users submit their computing jobs to the environment. In this paper, we propose the Adaptive-Scheduling-with-QoS-Satisfaction algorithm, namely AsQ, for the hybrid cloud environment to raise the resource utilization rate of the private cloud and to diminish task response time as much as possible. We exploit runtime estimation and several fast scheduling strategies for near-optimal resource allocation, which results in high resource utilization rate and low execution time in the private cloud. Moreover, the near-optimal allocation in the private cloud can reduce the amount of tasks that need to be executed on the public cloud to satisfy their deadline. For the tasks that have to be dispatched to the public cloud, we choose the minimal cost strategy to reduce the cost of using public clouds based on the characteristics of tasks such as workload size and data size. Therefore, the AsQ can achieve a total optimization regarding cost and deadline constraints. Many experiments have been conducted to evaluate the performance of the proposed AsQ. The results show that the performance of the proposed AsQ is superior to recent similar algorithms in terms of task waiting time, task execution time and task finish time. The results also show that the proposed algorithm achieves a better QoS satisfaction rate than other similar studies.

Reversible steganography based on side match and hit pattern for VQ-compressed images

Data hiding is a technique which embeds secret data into cover media. It is important to the multimedia security and has been widely studied. Recently, some researchers paid attention to reversible data hiding methods. These methods can reconstruct the original image from the stego-image when embedded data are extracted. In this paper, we propose a new reversible steganographic method for vector quantization (VQ) compressed images. The new method uses the hit pattern to achieve reversibility, and the hit pattern strategy successfully reduces the overhead. The codebook is partitioned by the extension method which makes the stego-image have good visual features. Also, a look-up table is used to speed up the partitioning operation. Compared to Chang et al.’s method, the experimental results show that the proposed method has higher capacity, better visual quality, and lower running time.

VQ Applications in Steganographic Data Hiding Upon Multimedia Images

Data hiding is one of the most important techniques to achieve better data and communication protection by hiding information into a media carrier. It provides a secure method to distribute data through a public and open channel. Data hiding for vector quantization (VQ)-based images focuses on the problem of embedding secret data into a cover VQ-based image to achieve secret communication and data protection. This paper provides a state-of-the-art review and comparison of the different existing data-hiding methods for VQ-based images. In this paper, we classify VQ-based data-hiding methods into four nonoverlapping groups according to their reversibility and output formats, introduce the details of the representative methods, summarize the features of the representative methods, and compare the performance of the representative methods using peak signal-to-noise ratio, capacity of secret data, and bit rate. Our paper shows that an irreversible method is very likely a VQ-based data-hiding method that produces a stego-image as its output, and it can embed more secret data than a reversible method. Nonstandard encoding methods (e.g., joint neighboring coding) are becoming popular in reversible data hiding since they can increase the capacity for embedding the secret data. Some methods with high compression rate, such as the search order coding-based methods, may reduce the compression rate in return for the capacity for the secret data.

Data embedding for vector quantization image processing on the basis of adjoining state-codebook mapping

Information hiding for images is an important research issue in digital multimedia. It provides a way to certify copyrights of image files, as well as a means of secret communication for people. In this paper, we propose a reversible image information hiding scheme based on vector quantization (VQ). The proposed scheme uses a new technique called Adjoining State-Codebook Mapping (ASCM) to map the content of an image block to an index in the corresponding state-codebooks. The ASCM technique uses two adjacent image blocks of an encoding image block to create two state-codebooks, which can represent the encoding image block more accurately. Therefore, it can reduce the size of the output code-stream and yet still provide large embedding capacity for secret data. Experimental results indicate that the proposed scheme has better compression bit rate and larger embedding capacity when we compare the proposed scheme with recent similar studies, proposed by Chang et al. in 2009 and Yang et al. in 2011 respectively.

A dynamic causal model for evoked and induced responses

Neuronal responses exhibit two stimulus or task-related components: evoked and induced. The functional role of induced responses has been ascribed to ‘top-down’ modulation through backward connections and lateral interactions; as opposed to the bottom-up driving processes that may predominate in evoked components. The implication is that evoked and induced components may reflect different neuronal processes. The conventional way of separating evoked and induced responses assumes that they can be decomposed linearly; in that induced responses are the average of the power minus the power of the average (the evoked component). However, this decomposition may not hold if both components are generated by nonlinear processes. In this work, we propose a Dynamic Causal Model that models evoked and induced responses at the same time. This allows us to explain both components in terms of shared mechanisms (coupling) and changes in coupling that are necessary to explain any induced components. To establish the face validity of our approach, we used Bayesian Model Selection to show that the scheme can disambiguate between models of synthetic data that did and did not contain induced components. We then repeated the analysis using MEG data during a hand grip task to ask whether induced responses in motor control circuits are mediated by ‘top-down’ or backward connections. Our result provides empirical evidence that induced responses are more likely to reflect backward message passing in the brain, while evoked and induced components share certain characteristics and mechanisms.

iPhone social networking for evidence investigations using iTunes forensics

The smart phone, like a small computer, providing not only the functions of normal phones and wireless Internet access, but also all kinds of application tools, serves as a platform of the sources of real-time information, information sharing and information exchange in our daily lives. As a result, the extract the crucial digital evidence in the smart phone, it has now become a challenge in the technology time. In particular, it is for when the smart phone applications are committed as the illegal contacts. In this paper, we discuss the most five popular mobile social networking applications in iPhone usages. The backup files of social networking applications could offer us the crucial evidence in this paper study. The relative information of social networking applications operated in iPhone is able to be accessed if necessary, even though iPhone has been destructed or encrypted by the suspect. It could help the investigators to exactly reconstruct the crime venue and find the truth.

Agent-Based Service Migration Framework in Hybrid Cloud

With the advance of cloud computing, hybrid cloud that integrate private and public cloud is increasingly becoming an important research issue. Migrating cloud applications from a busy host to an idle host needs an efficient way to guarantee the performance in the geographical heterogeneous cloud environment. This paper we propose an automatic, intelligent service migration framework on a hybrid cloud based on agent technology. We build a prototype that integrated our private cloud with public cloud. In the prototype, mobile agent technique is exploited to manage all resources, monitor system behaviour, and negotiate all actions in the hybrid cloud, in order to achieve automatic, intelligent service migration between the clouds. We demonstrate the service migration mechanism on Hadoop platform between our platform and ITRI¡¦s public cloud.

BrowserGuard: A Behavior-Based Solution to Drive-by-Download Attacks

Along with an increasing user population of various web applications, browser-based drive-by-download attacks soon become one of the most common security threats to the cyber community. A user using a vulnerable browser or browser plug-ins may become a victim of a drive-by-download attack right after visiting a vicious web site. The end result of such attacks is that an attacker can download and execute any code on the victims host. This paper proposes a runtime, behavior-based solution, BrowserGuard, to protect a browser against drive-by-download attacks. BrowserGuard records the download scenario of every file that is loaded into a host through a browser. Then based on the download scenario, BrowserGuard blocks the execution of any file that is loaded into a host without the consent of a browser user. Due to its behavior-based detection nature, BrowserGuard does not need to analyze the source file of any web page or the run-time states of any script code, such as Javascript. BrowserGuard also does not need to maintain any exploit code samples and does not need to query the reputation value of any web site. We utilize the standard BHO mechanism of Windows to implement BrowserGuard on IE 7.0. Experimental results show that BrowserGuard has low performance overhead (less than 2.5%) and no false positives and false negatives for the web pages used in our experiments.

Distributed garbage collection for mobile actor systems: the pseudo root approach

Automatic distributed garbage collection (GC) gives abstraction to grid application development, promoting code quality and improving resource management. Unreachability of active objects or actors from the root set is not a sufficient condition to collect actor garbage, making passive object GC algorithms unsafe when directly used on actor systems. In practical actor languages, all actors have references to the root set since they can interact with users, e.g., through standard input or output streams. Based on this observation, we introduce pseudo roots: a dynamic set of actors that can be viewed as the root set. Pseudo roots use protected (undeletable) references to ensure that no actors are erroneously collected even with messages in transit. Following this idea, we introduce a new direction of actor GC, and demonstrate it by developing a distributed GC framework. The framework can thus be used for automatic life time management of mobile reactive processes with unordered asynchronous communication.

Heuristic Scheduling Strategies for Linear-Dependent and Independent Jobs on Heterogeneous Grids

Grid computing came into being an active research area because of the advances in wide-area network technologies and the low cost of computing resources. One motivation of grid computing is to aggregate the power of distributed resources and integrate the resources into a unified platform. To minimize the total completion time of the submitted computing jobs to a grid platform, people employ various scheduling algorithms to dispatch the jobs to the resources. However, it has been proved that the optimal scheduling algorithm is NP-hard. Therefore, many people turn to use heuristic approaches for grid scheduling. In this paper, we introduce ten common scheduling heuristics to schedule a combination of job-chains (linear-dependent jobs) and independent jobs on a heterogeneous environment. We implemented these methods on a grid simulator to evaluate their performance under different circumstances. The results of scheduling job-chains and independent jobs on a heterogeneous environment are quite different from previous studies, and we provide our explanations for the differences. We also propose a hybrid method based on our observation, and the simulation results show that it has good performance in terns of makespan.