6065142
On effective data clustering in bitemporal databases
Temporal databases provide built-in supports for efficient recording and querying of time-evolving data. In this paper, data clustering issues in temporal database environment are addressed. Data clustering is one of the most effective techniques that can improve performance of a database system. However, data clustering methods for conventional databases do not perform well in temporal databases because there exist crucial differences between their query patterns. We propose a data clustering measure, called Temporal Affinity, that can be used for the clustering of temporal data. The temporal affinity, which is based on the analysis of query patterns in temporal databases, reflects the closeness of temporal data objects in viewpoints of temporal query processing. We perform experiments to evaluate the proposed measure. The experimental results show that a data clustering method with the temporal affinity works better than other methods.
1994375
Effective Temporal Aggregation Using Point-Based Trees
Temporal databases introduce the concept of time into underlying data, and provide built-in facilities that allow users to store and retrieve time-varying data. The aggregation in temporal databases, that is, temporal aggregation is an extension of conventional aggregation on the domain and range of aggregates to include time concept. Temporal aggregation is important for various applications, but is very expensive. In this paper, we propose a new tree structure for temporal aggregation, called PA-tree, and aggregate processing method based on the PA-tree. We show that the time complexity of the proposed method is better than those of the existing methods. The time complexity of the proposed method is shown to be indeed the lower bound of the problem. We perform comparative experiments and show the performance advantage of our proposed method in practice.
1514813
Temporal Query Processing Using Spatially-Partitioned Method
In this paper, we propose a general spatiallypartitioned temporal operation model, called 3D-TOM, and partition-based join algorithms for various types of temporal join in the proposed model. The temporal operators addressed in this paper include overlap, precede, follow, and equal. Some factors which a ect the performance of the proposed method are also discussed.
26955217
On Temporal Aggregate Processing Based on Time Points
Temporal aggregation is an extension of conventional aggregate on the domain and range of aggregates to include the time concept. In this paper, we propose a new tree-based temporal aggregation processing method. The time complexity of the proposed method is better than those of the existing methods. The experimental results indicate that our proposed method ourperforms the existing methods.
1231793
An effective data clustering measure for temporal selection and projection queries
Abstract Temporal databases (TDBs) allow users to record and retrieve time-varying data objects. Since TDBs usually manage a huge amount of underlying data objects, efficient disk accesses are essential for fast response time in temporal query processing. Data clustering is one of the most effective techniques that can improve performance of TDB systems. However, clustering measures for conventional data objects are not appropriate to temporal data objects because it is important to exploit temporal properties of underlying data objects and temporal queries as data clustering criteria. In this paper, we propose a data clustering measure called temporal affinity that can be used for effective temporal data clustering. The temporal affinity, which is based on the semantics of temporal operators, reflects the closeness among temporal data objects with respect to temporal query processing. We perform experiments to show the effectiveness of the proposed temporal data clustering measure. The experimental results indicate that a data clustering method based on the temporal affinity works better than other methods.
241209
Transient behaviors of TCP-friendly congestion control protocols
We investigate the fairness, smoothness, responsiveness, and aggressiveness of TCP and three representative TCP-friendly congestion control protocols: GAIMD, TFRC, and TEAR. The properties are evaluated both analytically and via simulation by studying protocol responses to three network environment changes. The first environment change is the inherent fluctuations in a stationary network environment. Under this scenario, we consider three types of sending rate variations: smoothness, short-term fairness, and long-term fairness. For a stationary environment, we observe that smoothness and fairness are positively correlated. We derive an analytical expression for the sending rate coefficient of variation for each of the four protocols. These analytical results match well with experimental results. The other two environment changes we study are a step increase of network congestion and a step increase of available bandwidth. Protocol responses to these changes reflect their responsiveness and aggressiveness, respectively.
18865506
Watermarking of 3D Irregular Meshes Based on Wavelet Multiresolution Analysis
In this paper, we propose a robust watermarking method for 3-D triangle surface meshes. Most previous methods based on the wavelet analysis can process only semi-regular meshes. Our proposal can be applied to irregular as well as regular meshes by using recently introduced irregular wavelet analysis scheme. L2-Norm of the wavelet coefficients is modified in various multi-resolution levels to embed the watermark. We also introduced a vertex and face re-ordering process as pre-processing in both watermark embedding and extraction for the robustness against connectivity reordering attacks. In addition, our proposal employs blind watermark detection scheme, which can extract the watermark without reference of cover mesh model. Through the simulations, we prove that our approach is robust against connectivity reordering as well as various kinds of geometrical attacks such as lossy compression and affine transform.
43684392
Wavelet Analysis Based Blind Watermarking for 3-D Surface Meshes
As most previous wavelet analysis based 3-D mesh watermarking methods embed the watermark information into wavelet coefficients arranged in a certain order, they have not been used as blind schemes since the connectivity information must be exactly known in the watermark extraction process. In this paper, we propose a blind watermarking method based on wavelet analysis for 3-D mesh model. Two new techniques are introduced. One is to exploit the statistical features of scale coefficients on an approximation (low resolution) level for watermark embedding. Another is to extract the hidden watermark, not from the same resolution level as used in embedding process, but directly from the spatial domain. As the proposed watermark detection does not require the wavelet analysis, any pre-processing such as registration and re-sampling, is not needed. These techniques allow to detect the watermark without referring to the original meshes. In addition, the proposed are applicable directly to irregular meshes by using irregular wavelet analysis. Through simulations, we prove that our method is fairly robust against various attacks including topological ones.
1278835
Evolutionary Approaches To Minimizing Network Coding Resources
We wish to minimize the resources used for network coding while achieving the desired throughput in a multicast scenario. We employ evolutionary approaches, based on a genetic algorithm, that avoid the computational complexity that makes the problem NP-hard. Our experiments show great improvements over the sub-optimal solutions of prior methods. Our new algorithms improve over our previously proposed algorithm in three ways. First, whereas the previous algorithm can be applied only to acyclic networks, our new method works also with networks with cycles. Second, we enrich the set of components used in the genetic algorithm, which improves the performance. Third, we develop a novel distributed framework. Combining distributed random network coding with our distributed optimization yields a network coding protocol where the resources used for coding are optimized in the setup phase by running our evolutionary algorithm at each node of the network. We demonstrate the effectiveness of our approach by carrying out simulations on a number of different sets of network topologies.
14547237
Foundations for the Run-Time Monitoring of Reactive Systems - Fundamentals of the MaC Language
As the complexity of systems grows, the correctness of systems becomes harder to achieve. This difficulty promotes a run-time monitoring technique as a promising complementary methodology for higher system assurance. To formalize and understand the computational nature of run-time monitoring is a key to utilize this valuable technique. In this paper, we formalize the notion of run-time monitoring of reactive systems in terms of ω-languages and show that the language of Monitoring and Checking (MaC) architecture, called MEDL, is expressive enough for the run-time monitoring. 
 
First, we provide a descriptive theory for the class of monitorable languages and show that this class of languages coincides with the class Π01 of the Arithmetic hierarchy. Second, we introduce a class of automata with storage that can be used to describe the class of monitorable languages using connections to the Arithmetic hierarchy. Finally, we show that MEDL can express the class of monitorable languages via the correspondence between MEDL and the automata with storage.