866017
Contour map matching for event detection in sensor networks
Many sensor network applications, such as object tracking and disaster monitoring, require effective techniques for event detection. In this paper, we propose a novel event detection mechanism based on matching the contour maps of in-network sensory data distribution. Our key observation is that events in sensor networks can be abstracted into spatio-temporal patterns of sensory data and that pattern matching can be done efficiently through contour map matching. Therefore, we propose simple SQL extensions to allow users to specify common types of events as patterns in contour maps and study energy-efficient techniques of contour map construction and maintenance for our pattern-based event detection. Our experiments with synthetic workloads derived from a real-world coal mine surveillance application validate the effectiveness and efficiency of our approach.
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.
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.
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.
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.
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.
15287686
Performance comparisons of power allocation mechanisms for downlink handoff in the WCDMA system with microcellular environments
This paper investigates different power allocation algorithms for downlink handoff in the wideband code division multiple access system from both outage performance and power efficiency perspectives. Traditionally, the site selection diversity transmission (SSDT) scheme has been viewed as the optimal solution for downlink handoff from the standpoint of power efficiency, which selects the best base station to transmit downlink signals to the user. However, from the outage performance perspective, the user at the cell boundary may have poor quality if there is only one serving base station. Thus, we are motivated to develop an improved SSDT scheme that can take both power efficiency and outage performances in account. In this paper, we propose a joint link proportional power allocation (LPPA) and SSDT scheme. Through analysis and simulation, we demonstrate that the proposed joint LPPA and SSDT scheme is the optimal power allocation solution for downlink handoff in the WCDMA system, which not only can improve the outage performance over the SSDT scheme when the traffic intensity is low, but can be very power efficient as the SSDT scheme in the heavy traffic situation.
10134892
Parameterized Freeform Shape Design and Deformation
Deformation is the most widely used in product design. Interactive free-form deformation (FFD), however, is often difficult to generate a desired result by designers. And it can not explicitly specify the degree of deformations such as angle of bend. Therefore, in order to solve these problems, a parametric deformation method driven by nature product definition parameters is presented in the paper. It consists of two phases. Firstly, based on mesh segmentation using feature point and core extraction, the proposed method extracts some product definition parameters automatically. Secondly, regarding these parameters as hard constraints, the deformation process is stably and precisely performed by the constraint optimization. Comparing to previous FFD methods, the proposed method has several distinctive benefits: designers can get the expected deformation efficiently, and then form the product family easily. Finally, shoe industry application of the method in product design is demonstrated. The dimension and style of shoe-last can be changed rapidly to achieve new product design by editing parameters.
18409692
An Interference Free Data Aggregation Protocol for Clustered Wireless Sensor Networks
An interference free cluster-based TDMA protocol (IFCT) for wireless sensor networks was proposed in previous study. IFCT uses a distributed frame assignment algorithm (FA) to assign different frames for neighboring clusters. In this paper, we propose a interference-free data aggregation protocol (IFDA) for clustered based TDMA wireless sensor networks based on IFCT. IFDA alters the FA algorithm of IFCT and uses a channel expansion algorithm CE to increase average per cluster channel usage ratio. The expected message cost for both FA and CE algorithms of IFDA is O(1). The expected running time complexity for both FA and CE is bound to polynomial of D, where D is the maximum neighboring cluster count of a cluster. Simulation results show that FA algorithm of IFDA requires less message cost than that of IFCT. Besides, IFDA improves the average per cluster channel usage ratio by about 80%compared with IFCT.
14979419
QoS-aware routing based on bandwidth estimation for mobile ad hoc networks
Routing protocols for mobile ad hoc networks (MANETs) have been explored extensively in recent years. Much of this work is targeted at finding a feasible route from a source to a destination without considering current network traffic or application requirements. Therefore, the network may easily become overloaded with too much traffic and the application has no way to improve its performance under a given network traffic condition. While this may be acceptable for data transfer, many real-time applications require quality-of-service (QoS) support from the network. We believe that such QoS support can be achieved by either finding a route to satisfy the application requirements or offering network feedback to the application when the requirements cannot be met. We propose a QoS-aware routing protocol that incorporates an admission control scheme and a feedback scheme to meet the QoS requirements of real-time applications. The novel part of this QoS-aware routing protocol is the use of the approximate bandwidth estimation to react to network traffic. Our approach implements these schemes by using two bandwidth estimation methods to find the residual bandwidth available at each node to support new streams. We simulate our QoS-aware routing protocol for nodes running the IEEE 802.11 medium access control. Results of our experiments show that the packet delivery ratio increases greatly, and packet delay and energy dissipation decrease significantly, while the overall end-to-end throughput is not impacted, compared with routing protocols that do not provide QoS support.
38425379
Noninvasive Temperature Monitoring in a Wide Range Based on Textures of Ultrasound Images
The B-mode ultrasound is widely used in thermal therapies as an invasive technique for temperature measurement and monitoring the effectiveness of the treatment. In traditional technique the B-mode ultrasound can only measure a small range of temperature changes using the gray scale of images. We obtained a series of real-time B-mode ultrasound images with a wide range of temperature variation from 28°C to 85°C. In this paper, we investigate image texture characteristics with respect to changes of tissue temperature. Results from water bath and radiofrequency ablation experiments show that there is a strong correlation between several texture features and temperature in a wide range of 28-85°C.