17294449
Efficient Similarity Search in Nonmetric Spaces with Local Constant Embedding
Similarity-based search has been a key factor for many applications such as multimedia retrieval, data mining, Web search and retrieval, and so on. There are two important issues related to the similarity search, namely, the design of a distance function to measure the similarity and improving the search efficiency. Many distance functions have been proposed, which attempt to closely mimic human recognition. Unfortunately, some of these well-designed distance functions do not follow the triangle inequality and are therefore nonmetric. As a consequence, efficient retrieval by using these nonmetric distance functions becomes more challenging, since most existing index structures assume that the indexed distance functions are metric. In this paper, we address this challenging problem by proposing an efficient method, that is, local constant embedding (LCE), which divides the data set into disjoint groups so that the triangle inequality holds within each group by constant shifting. Furthermore, we design a pivot selection approach for the converted metric distance and create an index structure to speed up the retrieval efficiency. Moreover, we also propose a novel method to answer approximate similarity search in the nonmetric space with a guaranteed query accuracy. Extensive experiments show that our method works well on various nonmetric distance functions and improves the retrieval efficiency by an order of magnitude compared to the linear scan and existing retrieval approaches with no false dismissals.
8931794
Speed up semantic search in p2p networks
Peer-to-peer architectures become popular in modern massively distributed systems, which are often in very large scale and contain a huge volume of heterogeneous data. To facilitate the information retrieval process in P2P networks, we consider semantic search approach, where syntax-based queries are shipped to peers based on semantic correlations. Motivated by an interesting experience in Web information retrieval, we propose a novel ontology-based scheme to measure similarity of peer interests accurately and consistently in a decentralized way, and group peers under a scalable hierarchical overlay network. Given queries, our approach either floods them within local peer groups or guides them towards remote groups based on the similarity of interests. Our work overcomes the limitations of the existing P2P hybrid-search approaches by avoiding costly data popularity measurement. Performance evaluation and comparison against baseline algorithms show that our approach provides a better solution for information retrieval in large-scale P2P networks.
262231
Monochromatic and bichromatic reverse skyline search over uncertain databases
Reverse skyline queries over uncertain databases have many important applications such as sensor data monitoring and business planning. Due to the existence of uncertainty in many real-world data, answering reverse skyline queries accurately and efficiently over uncertain data has become increasingly important. In this paper, we model the probabilistic reverse skyline query on uncertain data, in both monochromatic and bichromatic cases, and propose effective pruning methods to reduce the search space of query processing. Moreover, efficient query procedures have been presented seamlessly integrating the proposed pruning methods. Extensive experiments have demonstrated the efficiency and effectiveness of our proposed approach with various experimental settings.
9576587
Non-Threshold based Event Detection for 3D Environment Monitoring in Sensor Networks
Event detection is a crucial task for wireless sensor network applications, especially environment monitoring. Existing approaches for event detection are mainly based on some predefined threshold values, and thus are often inaccurate and incapable of capturing complex events. For example, in coal mine monitoring scenarios, gas leakage or water osmosis can hardly be described by the overrun of specified attribute thresholds, but some complex pattern in the full-scale view of the environmental data. To address this issue, we propose a non-threshold based approach for the real 3D sensor monitoring environment. We employ energy-efficient methods to collect a time series of data maps from the sensor network and detect complex events through matching the gathered data to spatio-temporal data patterns. Finally, we conduct trace driven simulations to prove the efficacy and efficiency of this approach on detecting events of complex phenomena from real-life records.
7517195
Spotting Significant Changing Subgraphs in Evolving Graphs
Graphs are popularly used to model structural relationships between objects. In many application domains such as social networks, sensor networks and telecommunication, graphs evolve over time. In this paper, we study a new problem of discovering the subgraphs that exhibit significant changes in evolving graphs. This problem is challenging since it is hard to define changing regions that are closely related to the actual changes (i.e., additions/deletions of edges/nodes) in graphs. We formalize the problem, and design an efficient algorithm that is able to identify the changing subgraphs incrementally. Our experimental results on real datasets show that our solution is very efficient and the resultant subgraphs are of high quality.
8704395
Summarization Graph Indexing: Beyond Frequent Structure-Based Approach
Graph is an important data structure to model complex structural data, such as chemical compounds, proteins, and XML documents. Among many graph data-based applications, sub-graph search is a key problem, which is defined as given a query Q, retrieving all graphs containing Q as a sub-graph in the graph database. Most existing sub-graph search methods try to filter out false positives (graphs that are not possible in the results) as many as possible by indexing some frequent sub-structures in graph database, such as [20, 22, 4, 23]. However, due to ignoring the relationships between sub-structures, these methods still admit a high percentage of false positives. In this paper, we propose a novel concept, Summarization Graph, which is a complete graph and captures most topology information of the original graph, such as sub-structures and their relationships. Based on Summarization Graphs, we convert the filtering problem into retrieving objects with set-valued attributes. Moreover, we build an efficient signature file-based index to improve the filtering process. We prove theoretically that the pruning power of our method is larger than existing structure-based approaches. Finally, we show by extensive experimental study on real and synthetic data sets that the size of candidate set generated by Summarization Graph-based approach is only about 50% of that left by existing graph indexing methods, and the total response time of our method is reduced 2-10 times.
17397024
Multi-level secure video streaming over SRTP
In this paper, we propose a set of solutions to four different levels on data selection for encrypting Motion JPEG video frames over SRTP. These solutions are based on our intensive analysis of the JPEG image compression procedure. We select the most important data which contains most information of an image for encryption; in consequence provide a set of balances between security and computation for different hardware environments. Extensive experiments are conducted and performance data has been analyzed to evaluate the proposed solutions. Results show that these solutions are well suited in different scenarios with various computation power and security requirements.
38456559
Testing Technology of Torsional Vibration Spring Static Stiffness
The principle and method of testing static stiffness of torsional vibration spring are put forward based on the structure of dual-mass flywheel with torsional vibration spring, and the test bench is designed for these. The testing data is collected by using the PXI-6259 data collection card of National instrument and the data is processed by the LabVIEW software system. The elastic characteristic of the torsional vibration spring is obtained by analyzing the data.
18643817
A Survey of Routing Protocols that Support QoS in Mobile Ad Hoc Networks
The explosive growth in the use of mobile devices coupled with users' desires for real-time applications has provided new challenges in the design of protocols for mobile ad hoc networks. Chief among these challenges to enabling real-time applications for mobile ad hoc networks is incorporating support for quality of service (QoS), such as meeting bandwidth or delay constraints. In particular, it is important that routing protocols incorporate QoS metrics in route finding and maintenance to support end-to-end QoS. This article extensively and exclusively studies the issues involved with QoS-aware routing and presents an overview and comparison of existing QoS-aware routing protocols. In addition, the open issues that must be addressed to fully support QoS-aware routing are discussed.
18449881
Tracking Articulated Hand Underlying Graphical Model with Depth Cue
Visual tracking of articulated objects in real 3D space is challenging with applications in advanced human–computer interfaces and gesture semantic understanding. In this paper, graphical model, constructing articulated human hand, and NBP algorithm embedded with CAMSHIFT, inferencing hand configuration in 3D space, are applied for visual hand tracking. We also introduce image depth cue captured by two calibrated cameras together with color and edge as observation model. Depth cue allows our method to track human hand incomparatively accurate distance from cameras, especially in cluttered scenes with objects of similar color or edge. All those image cues are converted necessarily to probability distribution applied for the graphical model frame. The proposed method promotes the tracking efficiency and robustness proved by experiments and theory analysis.
40545913
Algebraic Constructions of Quasi-cyclic LDPC Codes - Part I: For AWGN and Binary Random Erasure Channels
This paper is the first part of a sequence of two papers that present algebraic constructions of quasi-cyclic LDPC codes for AWGN, binary random and burst erasure channels. In this paper, a class of quasi-cyclic LDPC codes for both AWGN and binary random erasure channels is constructed based on finite fields and special vector representations of finite field elements.