15626216
SenCast: Scalable multicast in wireless sensor networks
Multicast is essential for wireless sensor network (WSN) applications. Existing multicast protocols in WSNs are often designed in a P2P pattern, assuming small number of destination nodes and frequent changes on network topologies. In order to truly adopt multicast in WSNs, we propose a base-station model- based multicast, SenCast, to meet the general requirements of applications. SenCast is scalable and energy-efficient for large group communications in WSNs. Theoretical analysis shows that SenCast is able to approximate the Minimum Nonleaf Nodes (MNN) problem to a ratio of ln\R\ (R is the set of all destinations), best known lowest bound. We evaluate our design through comprehensive simulations. Experimental results demonstrate that SenCast outperforms previous multicast protocols including the most recent work uCast.
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.
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.
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.
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.
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.
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.
36282948
Extremal problems on consecutive L(2, 1)-labelling
For a given graph G of order n, a k-L(2,1)-labelling is defined as a function f:V(G)->{0,1,2,...,k} such that |f(u)-f(v)|>=2 when d"G(u,v)=1 and |f(u)-f(v)|>=1 when d"G(u,v)=2. The L(2,1)-labelling number of G, denoted by @l(G), is the smallest number k such that G has a k-L(2,1)-labelling. The consecutive L(2,1)-labelling is a variation of L(2,1)-labelling under the condition that the labelling f is an onto function. The consecutive L(2,1)-labelling number of G is denoted by @[email protected]?(G). Obviously, @l(G)=<@[email protected]?(G)=<|V(G)|-1 if G admits a consecutive L(2,1)-labelling. In this paper, we investigate the graphs with @[email protected]?(G)=|V(G)|-1 and the graphs with @[email protected]?(G)[email protected](G), in terms of their sizes, diameters and the number of components.
36015741
Feedforward Neural Networks without Orthonormalization
A blood pressure measurement system comprises a determination means for determining whether a cuff pressure is increasing for preparation purposes or decreasing for measurement purposes. The determination means includes a comparator for comparing the current cuff pressure with the last cuff pressure, and detection means for detecting whether a difference between the current cuff pressure and the last cuff pressure is smaller than a predetermined value. Another determination means is provided for detecting whether the cuff pressure is first increased to a desired level higher than systolic pressure of a person to be measured. A reset means is provided for automatically resetting the system when the cuff pressure is decreased to a predetermined level after completion of measurement.
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.
8353452
OPHMR: An Optimized Polymorphic Hybrid Multicast Routing Protocol for MANET
We propose in this paper an optimized, polymorphic, hybrid multicast routing protocol for MANET. This new polymorphic protocol attempts to benefit from the high efficiency of proactive behavior (in terms of quicker response to transmission requests) and the limited network traffic overhead of the reactive behavior, while being power, mobility, and vicinity-density (in terms of number of neighbor nodes per specified area around a mobile node) aware. The proposed protocol is based on the principle of adaptability and multibehavioral modes of operations. It is able to change behavior in different situations in order to improve certain metrics like maximizing battery life, reducing communication delays, improving deliverability, etc. The protocol is augmented by an optimization scheme, adapted from the one proposed for the optimized link state routing protocol (OLSR) in which only selected neighbor nodes propagate control packets to reduce the amount of control overhead. Extensive simulations and comparison to peer protocols demonstrated the effectiveness of the proposed protocol in improving performance and in extending battery power longevity