8697404
Audio streaming over Bluetooth: an adaptive ARQ timeout approach
Streaming audio has become a popular form of media on the Internet. As wireless personal area network architectures (e.g. Bluetooth) are now targeted to support multimedia traffic, streaming audio over these technologies give rise to interesting applications. But, the variable nature of the wireless medium will not lend itself easily to supporting audio streaming. We focus on Bluetooth and propose, an enhancement to the Bluetooth link layer ARQ mechanism to compensate for channel degradation and to better support audio streaming. Specifically, our scheme adoptively sets the ARQ timeout value based on current channel measurements. We show through testbed experiments that the adaptive ARQ improves the streaming quality significantly compared to the "vanilla" link layer of Bluetooth, especially in noisy environments. Our proposed approach is simple to implement and can actually be extended to the link layer of any wireless technology.
10353520
Finding Self-Similarities in Opportunistic People Networks
Opportunistic network is a type of delay tolerant networks (DTN) where network communication opportunities appear opportunistic. In this study, we investigate opportunistic network scenarios based on public network traces, and our contributions are the following: First, we identify the censorship issue in network traces that usually leads to strongly skewed distribution of the measurements. Based on this knowledge, we then apply the Kaplan-Meier Estimator to calculate the survivorship of network measurements, which is used in designing our proposed censorship removal algorithm (CRA) that is used to recover censored data. Second, we perform a rich set of analysis illustrating that UCSD and Dartmouth network traces show strong self-similarity, and can be modeled as such. Third, we pointed out the importance of these newly revealed characteristics in future development and evaluation of opportunistic networks.
12012725
An intelligent control system with a multi-objective self-exploration process
Abstract This paper proposes a novel approach based on artificial intelligence technologies (multi-objective Self-Exploration process based Intelligent Control System—mSEICS) for intelligent control systems. Not only can this system adapt to various environments, but it can also continually improve its performance. The mSEICS consists of four basic functions, controller, receptor, m-adaptor and advancer. A five-layer fuzzy neural network is applied to implement the controller. The receptor is used to evaluate the performance of system. The m-adaptor (multi-objective based adaptor) that comprises two elements, action explorer and rule generator, can generate a variety of new action sets in order to adapt to various environments. The Pareto optimality based multi-objective genetic algorithm is proposed to implement the action explorer to discover multiple action sets, and the rule generator is employed to transform the action set to fuzzy rules. In addition, the advancer consisting of action discoverer and rule generator is constructed to produce the novel action set to enhance the system efficiency. The parallel-simulated annealing approach is presented to realize the action discoverer. An application of the robotic path planning is applied to demonstrate the proposed model. The simulation results show that the mobile robot can reach the target successfully in various environments, and the proposed model is more efficient than the similar model.
9822806
Wavelet-based optical flow estimation
In this paper, a new algorithm for accurate optical flow estimation using discrete wavelet approximation is proposed. The proposed method takes advantages of the nature of wavelet theory, which can efficiently and accurately represent "things", to model optical flow vectors and image related functions. Each flow vector and image function are represented by linear combinations of wavelet basis functions. From such wavelet-based approximation, the leading coefficients of these basis functions carry the global information of the approximated "things". The proposed method can successfully convert the problem of minimizing a constraint function into that of solving a linear system of a quadratic and convex function of wavelet coefficients. Once all the corresponding coefficients are decided, the flow vectors can be determined accordingly. Experiments conducted on both synthetic and real image sequences show that our approach outperformed the existing methods in terms of accuracy.
33456865
Enterprise Information Integration - A Semantic Approach
Nowadays, we witness the advent of a new era in information technology as an enabler for an often proclaimed “knowledged society”. Many academicians – computer scientists, computational linguists and others – but also researchers in corporate settings investigate the use of “knowledge” as a means for intelligent information access in enterprises. Ontologies are commonly considered a formal means for modelling and instantiating conceptual structures upon which implicit knowledge can be inferred. In an industrial context, however, domain-specific conceptual information is only one corporate information resource. Relevant business information comprises facts on goods, projects, experts, customers, competitors and many other information bits as they are stored in enterprise information systems. A great wish of many executives is, however, to gain an integrated view on these assets and their relationships, thus deriving new insights relevant for their business. To achieve this goal, ontologies can help with respect to semantic data integration. A problem is, however, that the construction and maintenance of ontologies is expensive. Another problem is that the business data are usually stored redundantly in different heterogeneous data repositories and the connectivity – a prerequisite for intelligence – is not explicit. The approach discussed in the remainder will show how a mix of information extraction and classification methods can be used to automatically set-up and update a network of business objects serving as a corporate memory index. The latter represents a rich semantic access structure for filtering and individualizing the retrieval of relevant business information.
6229211
Resource allocation in a middleware for streaming data
Increasingly, a number of applications rely on, or can potentially benefit from, analysis and monitoring of <i>data streams.</i> To support processing of streaming data in a grid environment, we have been developing a middleware system called GATES (Grid-based AdapTive Execution on Streams). Our target applications are those involving high volume data streams and requiring distributed processing of data arising from a distributed set of sources.
 This paper addresses the problem of resource allocation in the GATES system. Though resource discovery and resource allocation have been active topics in grid community, the pipelined processing and real-time constraint required by distributed streaming applications pose new challenges. We present a resource allocation algorithm that is based on minimal spanning trees. We evaluate the algorithm experimentally and demonstrate that it results in configurations that are very close to optimal, and significantly better than most other possible configurations.
21848565
Discrete signal matching using coarse-to-fine wavelet basis functions
In this paper, we propose a matching algorithm to estimate accurate and dense displacements between two signals. The displacements are characterized by a coarse-to-fine wavelet representation, which is a linear combination of hierarchical basis functions developed by Cai and Wang (SIAM Numer. Anal. 33(3) (1996) 937). The coarser-scale basis function has larger support while the finer-scale basis function has smaller support. During the iterative minimization process, the basis functions are utilized as large-to-small windows in selecting global-to-local regions for signal matching. The estimated wavelet coefficients are then used to reconstruct the signal in a coarse-to-fine manner. Two sets of synthetic examples, one with small displacement and the other with large displacements, have been employed to illustrate the advantages of the wavelet-based method. This method has been applied to estimate the dense disparity between stereo images in several real examples and the results demonstrate its effectiveness.