7321726
A gateway-assisted approach toward QoS adaptations
We present a gateway-assisted QoS adaptation framework which satisfies high-level QoS application guarantees. We validate this framework via a distributed tracking system and show provisioning of critical QoS guarantees despite the best effort underlying resource management.
2274256
Overlay Networks with Linear Capacity Constraints
Overlay networks are virtual networks residing over the IP network; consequently, overlay links may share hidden lower level bottlenecks. Previous work has assumed an independent overlay model: a graph with independent link capacities. We introduce a model of overlays that incorporates correlated link capacities and linear capacity constraints (LCC) to formulate hidden shared bottlenecks; we refer to these as LCC-overlays. We define metrics to qualitatively measure overlay quality in terms of its accuracy (in representing the true network topology) and efficiency (that is, performance). Through analysis and simulations, we show that LCC-overlay is perfectly accurate and, hence, enjoys much higher efficiency than the inaccurate independent overlay. We discover that even a highly restricted LCC class-node-based LCC-yields near-optimal accuracy and significantly higher efficiency. We study two network flow problems in the context of LCC-graphs: widest path and maximum flow. We prove that Widest Path with LCC is NP-complete. We formulate Maximum Flow with LCC as a linear program and propose an efficient distributed algorithm to solve it. Based on the LCC model, we further study the problem of optimizing delay while still maintaining optimal or near-optimal bandwidth. We also outline a distributed algorithm to efficiently construct an overlay with node-based LCC.
5921080
Dynamic reconfiguration for complex multimedia applications
Current state-of-the-art distributed multimedia applications require an environment that provides stable quality of service (QoS). However, these applications typically run on best-effort heterogeneous platforms, and compete with other applications or connections for end system and network resources, hence suffer from instability and dynamic variations with regards to QoS. We present a dynamically reconfigurable middleware control architecture to enhance adaptation awareness of these applications. Our middleware architecture allows for detecting QoS fluctuations in the surrounding environment and signaling optimal control actions to the application. Furthermore, we discuss the design of a core component, the Configurator, that adopts a fuzzy control approach to compute optimal control actions. Preliminary experimental results with a distributed visual tracking application show that our approach is viable and effective in controlling adaptive applications.
8043231
QoS-Aware Adaptive Services in Mobile Ad-Hoc Networks
Ad-hoc wireless networks consist of mobile nodes interconnected by multi-hop wireless paths. Unlike conventional wireless networks, ad-hoc networks have no fixed network infrastructure or administrative support. Because of the dynamic nature of the network topology and limited bandwidth of wireless channels, Quality-of-Service (QoS) provisioning is an inherently complex and difficult issue. In this paper, we propose a fully distributed and adaptive algorithm to provide statistical QoS guarantees with respect to accessibility of services in an ad-hoc network. In this algorithm, we focus on the optimization of a new QoS parameter of interest, service efficiency, while keeping protocol overheads to the minimum. To achieve this goal, we first theoretically derive the lower and upper bounds of service efficiency based on a novel model for group mobility, followed by extensive simulation results to verify the effectiveness of our algorithm.
3208295
Price-based resource allocation in wireless ad hoc networks
The shared-medium multi-hop nature of wireless ad hoc networks poses fundamental challenges to the design of an effective resource allocation algorithm to maximize the aggregated utility of flows, while maintaining basic fairness among multiple flows. When previously proposed scheduling algorithms have been shown to perform well in providing fair shares of bandwidth among single-hop wireless flows, they did not consider multi-hop flows with an end-to-end perspective. Moreover, the resource allocation strategies employed in the wireline network can not be applied directly in the context of ad hoc networks due to the unique characteristic of location dependent contention and spatial reuse of the shared wireless channel. In this paper, we propose a price-based resource allocation model to achieve maximized aggregated utility (i.e., social welfare) of flows. Our original contributions are: First, we propose to use maximal clique-associated shadow prices for wireless channel access coordination, rather than link-associated price for wireline link access arbitration. Second, we present a new pricing policy for end-to-end multi-hop flow. Using this model, different fairness goals can be realized in ad hoc networks for end-to-end flows. With a two-tier distributed and iterative algorithm, scarce channel capacity is allocated fairly among multi-hop flows from an end-to-end perspective, using shadow prices as the mechanism to arbitrate channel access. Through extensive analysis and simulation results, we show that our proposed algorithm is able to fairly distribute resources among multi-hop flows, while simultaneously maximizing the aggregated utility of flows globally.
1974741
Strategyproof Mechanisms towards Dynamic Topology Formation in Autonomous Networks
In autonomous networks, cooperations among nodes cannot be assumed, since each node is capable of making independent decisions based on their personal preferences. In particular, when a node needs the help of intermediate nodes to relay messages to other nodes, these intermediaries may be reluctant to contribute their network resource for the benefit of others. Ideally, the right amount of incentives should be provided to motivate cooperations among autonomous nodes so that a mutually beneficial network results. In this paper, we leverage the power of mechanism design in microeconomics to design a distributed incentive mechanism that motivates each node towards a more desirable network topology. Since network parameters and constraints change dynamically in reality, the desirable topology can vary over time. Our solution presented in this paper has successfully encompassed such a dynamic nature of the network topology. In addition, we have transformed our solution to an easy-to-implement distributed algorithm, that converges towards the globally optimal topology.
14227223
Bridging the semantic gap in sports video retrieval and summarization
One of the major challenges facing current media management systems and related applications is the so-called ''semantic gap'' between the rich meaning that a user desires and the shallowness of the content descriptions that are automatically extracted from the media. In this paper, we address the problem of bridging this gap in the sports domain. We propose a general framework for indexing and summarizing sports broadcast programs, with a high-level model of sports broadcast video using the concept of an event, defined according to domain-specific knowledge for different types of sports. Within this general framework, we develop automatic event detection algorithms that are based on automatic analysis of the visual and aural signals in the media. We have successfully applied the event detection algorithms to different types of sports including American football, baseball, Japanese sumo wrestling, and soccer. Event modeling and detection contribute to the reduction of the semantic gap by providing rudimentary semantic information obtained through media analysis. We further propose a novel approach, which makes use of independently generated rich textual metadata, to fill the gap completely through synchronization of the information-laden textual data with the basic event segments. We implemented an MPEG-7 compliant browsing system for semantic retrieval and summarization of sports video using the proposed algorithms.
17742402
A Unicode-based Adaptive Segmenter
This paper presents a Unicode based Chinese word segmentor. It can handle Chinese text in Simplified, Traditional, or mixed mode. The system uses the strategy of divide-and-conquer to handle the recognition of personal names, numbers, time and numerical values, etc in the preprocessing stage. The segmentor further uses tagging information to work on disambiguation. Adopting a modular design approach, different functional parts are separately implemented using different modules and each module tackles one problem at a time providing more flexibility and extensibility. Results show that with added pre-processing modules and accessorial modules, the accuracy of the segmentor is increased and the system is easily adaptive to different applications.
1260337
An Improved k-Nearest Neighbor Algorithm for Text Categorization
k is the most important parameter in a text categorization system based on k-Nearest Neighbor algorithm (kNN).In the classification process, k nearest documents to the test one in the training set are determined firstly. Then, the predication can be made according to the category distribution among these k nearest neighbors. Generally speaking, the class distribution in the training set is uneven. Some classes may have more samples than others. Therefore, the system performance is very sensitive to the choice of the parameter k. And it is very likely that a fixed k value will result in a bias on large categories. To deal with these problems, we propose an improved kNN algorithm, which uses different numbers of nearest neighbors for different categories, rather than a fixed number across all categories. More samples (nearest neighbors) will be used for deciding whether a test document should be classified to a category, which has more samples in the training set. Preliminary experiments on Chinese text categorization show that our method is less sensitive to the parameter k than the traditional one, and it can properly classify documents belonging to smaller classes with a large k. The method is promising for some cases, where estimating the parameter k via cross-validation is not allowed.
11775748
Schema Mapping for Interoperability in XML-based multidatabase
The main aim of a multidatabase system (MDBS) is to achieve data integration and interoperability among distributed and heterogeneous database systems. But data model heterogeneity and schema make this a challenging task. Multidatabase users can only view the global schemas whose real data come from local database systems. Thus, mappings from global schemas to local schemas should be established. At the same time, the recent emergence of XML has shown great intractability as a new standard for data representation and exchange on the Web. A data model based on XML becomes more suitable for integrating different types of systems. This paper firstly introduces a multidatabase common data model based on XML, named XML-based Integration Model (XIDM). Then, an approach of schema mappings based on XIDM in MDBSs has been presented. Finally, the illustration and implementation of schema mappings in a multidatabase prototype - Panorama are also discussed.
10521248
A generic approach to simultaneous tracking and verification in video
In this paper, a generic approach to simultaneous tracking and verification in video data is presented. The approach is based on posterior density estimation using sequential Monte Carlo methods. Visual tracking, which is in essence a temporal correspondence problem, is solved through probability density propagation, with the density being defined over a proper state space characterizing the object configuration. Verification is realized through hypothesis testing using the estimated posterior density. In its most basic form, verification can be performed as follows. Given a measurement vector Z and two hypotheses H1 and H0, we first estimate posterior probabilities P(H0/Z) and P(H1/Z), and then choose the one with the larger posterior probability as the true hypothesis. Several applications of the approach are illustrated by experiments devised to evaluate its performance. The idea is first tested on synthetic data, and then experiments with real video sequences are presented, illustrating vehicle tracking and verification, human (face) tracking and verification, facial feature tracking, and image sequence stabilization.