Directional antennas provide numerous benefits, such as higher gains, increased transmission range, and lower interferences. In this paper, we propose a reliable broadcast protocol for directional antenna referred to as beam table-based reliable broadcast for directional antennas (BTRB). The BTRB employs (1) ACK-based scheme to provide full reliability; (2) spatio-temporal ACK combination to resolve the problems of ACK implosion and transmission delay; and (3) beam table caching to represent spatial relationship among destination nodes in the broadcast group. Performance evaluation has shown that the proposed BTRB shows full reliability and outperforms existing reliable broadcast schemes with respect to transmission delay by about 55%.

We introduce the interval timing correlation, which can establish timing correlation conditions to handle interval timing timestamps. Interval timestamps are adopted to handle the temporal uncertainties in the timestamps of stream data. A probabilistic querying approach is taken in order to support timing predicates such as deadline, delay, and within over interval timestamps. A timing correlation condition entails a desired confidence threshold (minimum satisfaction probability). We define the interval timing correlation and discuss how to implement the algorithm. We present an analysis result which can effectively identify only tuples that need to be considered in determining the correlation. The performance of the proposed algorithm is shown.

The patching technique has been used for reducing initial waiting time in VOD services. Traditionally the technique has been applied to fixed segment NVOD scheduling. However, variable segment NVOD scheduling is known to have a better server bandwidth and less initial waiting time. In this paper, we propose a new scheduling algorithm for a true VOD service by incorporating the patching technique into variable segment NVOD scheduling. Our algorithm provides jitter-free playback while minimizing the use of the patching bandwidth. We present the proof of the correctness of our algorithm.

The reputation-based majority-voting approach is a promising solution for detecting malicious workers in a cloud system. However, this approach has a drawback in that it can detect malicious workers only when the number of colluders make up no more than half of all workers. In this paper, we simulate the behavior of a reputation-based method and mathematically analyze its accuracy. Through the analysis, we observe that, regardless of the number of colluders and their collusion probability, if the reputation value of a group is significantly different from those of other groups, it is a completely honest group. Based on the analysis result, we propose a new method for distinguishing honest workers from colluders even when the colluders make up the majority group. The proposed method constructs groups based on their reputations. A group with the significantly highest or lowest reputation value is considered a completely honest group. Otherwise, honest workers are mixed together with colluders in a group. The proposed method accurately identifies honest workers even in a mixed group by comparing each voting result one by one. The results of a security analysis and an experiment show that our method can identify honest workers much more accurately than a traditional reputation-based approach with little additional computational overhead.

Modularity is an effective evaluation approach for understanding the structural quality of evolutionary software. However, there are many diverse ways to measure it. In this paper, we analyze and compare various modularity metrics that have been studied in different domains to assess their applicability to evolutionary software analysis. Through extensive experiments with artificial DSMs and open-source software, we find that the correlations of those metrics are generally high despite their differences. However, our experiments show that a certain metric can be more sensitive to particular modular factors, hence applying of comprehensive modularity metrics must be taken into consideration.

A new exemplar-based inpainting method which effectively preserves global structures and textures in the restored region driven by feature vectors is presented. Exemplars that belong to the source region are segmented based on their features. To express characteristics of exemplars such as shapes of structures and smoothness of textures, the Harris corner response and the variance of pixel values are employed as a feature vector. Enhancements on restoration plausibility and processing speedup are achieved as shown in the experiments.

Packages are re-usable components for faster and effective software maintenance. To promote the re-use in object-oriented systems and maintenance tasks easier, packages should be organized to depict compact design. Therefore, understanding and assessing package organization is primordial for maintenance tasks like Re-usability and Changeability. We believe that additional investigations of prevalent basic design principles such as defined by R.C. Martin are required to explore different aspects of package organization. In this study, we propose package-organization framework based on reachable components that measures re-usability index. Package re-usability index measures common effect of change taking place over dependent elements of a package in an object-oriented design paradigm. A detailed quality assessment on different versions of open source software systems is presented which evaluates capability of the proposed package re-usability index and other traditional package-level metrics to predict fault-proneness in software. The experimental study shows that proposed index captures different aspects of package-design which can be practically integrated with best practices of software development. Furthermore, the results provide insights on organization of feasible software design to counter potential faults appearing due to complex package dependencies.

Software architecture recovery techniques are often adopted to derive a module view of software from its source code in case software architecture documents are unavailable or outdated. The module view is one of the most important perspectives of software architecture. In this paper, we propose a novel approach to derive a module view by adaptively integrating structural dependency and textual similarity. Our approach utilizes Newman modularity and Shannon information entropy to determine the appropriate weights of the dependencies during the integration. We apply our approach to various open-source projects and show the experimental results validating the effectiveness of the approach.

We propose an energy-efficient real-time scheduling algorithm based on T-L Plane abstraction. The algorithm is designed to exploit Dynamic Power Management and generates a new event called event-s to render longer idle intervals, which increases the chances of switching a processor to the sleep mode. We compare the proposed algorithm with previous work and show that it is effective for energy management.

Most previous approaches on comparing the results for software architecture recovery are designed to handle only flat decompositions. In this paper, we propose a novel distance called Split-Jaccard Distance of Hierarchical Decompositions. It extends the Jaccard coefficient and incorporates the concept of the splits of leaves in a hierarchical decomposition. We analyze the proposed distance and derive its properties, including the lower-bound and the metric space.