14906808
Dynamic data broadcasting with traffic awareness
Data dissemination has significantly served as a scalable data delivery mechanism in wireless networks. However, even though the broadcast traffic has the nature of dynamic changes, most previous research efforts were elaborated upon the premise of static workloads and access patterns without having proper traffic awareness. In this paper, we address the existence of client impatience and accordingly devise an online traffic awareness mechanism based on a novel selective deferment and reflection (SDR) technique to estimate the dynamic workloads and access patterns in a granularity of a broadcast cycle. In comparison with prior probing and feedback approaches, our design is of practical usefulness in that it has low complexity and is light-weight without performance degradation. With various dynamic traffic scenarios, the experimental results show that with an increasing/decreasing workload, the real access frequency distribution is bounded by two specific estimated distributions. This fact in turn suggests us to employ a trigonometric tuning method to further enhance the estimation. In addition, we examine that the mean difference between the estimated access frequency distribution and the real one is very small, consequently indicating the feasibility and reliability of our proposed data broadcast mechanism with traffic awareness.
146722
Adaptive dissemination of dynamic information services in an extended data broadcast environment
Considering that most information broadcast services generate data dynamically in practice, we devise in this paper an extended data broadcast mechanism which supports not only the original data broadcast scenario but also the dissemination of dynamic inforamtion services. Furthermore, we design an on-line loan-based slot allocation and feedback technique to tolerate the dynamic changes of broadcast traffic and accordingly perform the adaptation of service classification, bandwidth allocation and broadcast schedule so as to enhance the performance. Our experimental studies show that the extended data broadcast mechanism associated with the loan-based feedback technique is able to achieve a substantial saving in message traffic for dynamic information dissemination in wireless networks.
20310851
A mobile agent-based active network architecture for intelligent network control
The innovation and evolution of network technologies and services to enhance network functionality have traditionally encountered the problems of backward-compatibility and standardization. To resolve the related issues, active networks have been introduced to enable specific customization of network functionality without the lengthy standard-mediated committee processes. In this paper, we exploit the capability of mobile agent technology to construct an active network architecture. We argue that the mobile agent can be a building block for specific network customizations, and introduction of new network functionality. Both integrated and discrete operational models of network customizations can be supported in our prototype implementation. For the service development and deployment, an abstract service structure and a service loading mechanism are presented. Furthermore, we provide an agent management/control mechanism and devise a service management/control mechanism, which is either not available or incomplete in the other related work. The proposed architecture allows new service introduction, and as a result, achieves improved network functionality.
8145594
Effects of global interconnect optimizations on performance estimation of deep submicron design
In this paper, we quantify the impact of global interconnect optimization techniques that address such design objectives as delay, peak noise, delay uncertainty due to noise, power, and cost. In doing so, we develop a new system-performance simulation model as a set of studies within the MARCO GSRC Technology Extrapolation (GTX) system. We model a typical point-to-point global interconnect and focus on accurate assessment of both circuit and design technology with respect to such issues as inductance, signal line shielding, dynamic delay, buffer placement uncertainty and repeater staggering. We demonstrate, for example, that optimal wire sizing models need to consider inductive effects-and that use of more accurate (-1,3) worst-case capacitive coupling noise switch factors substantially increases peak noise estimates compared to traditional (0,2) bounds. We also find that optimal repeater sizes are significantly smaller than conventional models would suggest, especially when considering energy-delay issues.
3771585
Icon-based visualization of large high-dimensional datasets
High dimensional data visualization is critical to data analysts since it gives a direct view of original data. We present a method to visualize large amount of high dimensional data. We divide dimensions of data into several groups. Then, we use one icon to represent each group, and associate visual properties of each icon with dimensions in each group. A high dimensional data record will be represented by multiple different types of icons located in the same position. Furthermore, we use summary icons to display local details of viewer's interests and the whole data set at meantime. We show its effectiveness and efficiency through a case study on a real large data set.
14850039
Provisioning Quality Controlled Medium Access in UltraWideBand-Operated WPANs
Quality of service (QoS) provisioning is one of the most important criteria in newly emerging UWB-operated WPANs, as they are expected to support a wide variety of applica- tions from time-constrained, multimedia streaming to throughput- hungry, content transfer applications. As such, the Enhanced Distributed Coordinated Access (EDCA) mechanism has been adopted by MultiBand OFDM Alliance in its UWB MAC proposal. In this paper, we conduct a rigorous, comprehensive, theoretical analysis and show that with the currently recommended parame- ter setting, EDCA cannot provide adequate QoS. In particular, without responding to the system dynamics (e.g., taking into account of the number of active class-i stations), EDCA cannot allocate bandwidth in a deterministic proportional manner and the system bandwidth is under-utilized. After identifying the deficiency of EDCA, we propose, in compliance with the EDCA-incorporated UWB MAC protocol proposed in (15) (20), a framework, along with a set of theoretically grounded methods for controlling medium access with determin- istic QoS for UWB networks. We show that in this framework, 1) real-time traffic is guaranteed of deterministic bandwidth via a contention-based reservation access method; 2) best-effort traffic is provided with deterministic proportional QoS; and moreover, 3) the bandwidth utilization is maximized. We have also validated and evaluated the QoS provisioning capability and practicality of the proposed MAC framework both via simulation and empirically by leveraging the MADWifi (Multiband Atheros Driver for WiFi) Linux driver for Wireless LAN devices with the Atheros chipset.
1952111
Manifold Based Analysis of Facial Expression
We propose a novel approach for modeling, tracking and recognizing facial expressions. Our method works on a low dimensional expression manifold, which is obtained by Isomap embedding. In this space, facial contour features are first clustered, using a mixture model. Then, expression dynamics are learned for tracking and classification. We use ICondensation to track facial features in the embedded space, while recognizing facial expressions in a cooperative manner, within a common probabilistic framework. The image observation likelihood is derived from a variation of the Active Shape Model (ASM) algorithm. For each cluster in the low-dimensional space, a specific ASM model is learned, thus avoiding incorrect matching due to non-linear image variations. Preliminary experimental results show that our probabilistic facial expression model on manifold significantly improves facial deformation tracking and expression recognition.
123451361
Probabilistic expression analysis on manifolds
In this paper, we propose a probabilistic video-based facial expression recognition method on manifolds. The concept of the manifold of facial expression is based on the observation that the images of all possible facial deformations of an individual make a smooth manifold embedded in a high dimensional image space. An enhanced Lipschitz embedding is developed to embed the aligned face appearance in a low dimensional space while keeping the main structure of the manifold. In the embedded space, a complete expression sequence becomes a path on the expression manifold, emanating from a center that corresponds to the neutral expression. Each path consists of several clusters. A probabilistic model of transition between the clusters and paths is learned through training videos in the embedded space. The likelihood of one kind of facial expression is modeled as a mixture density with the clusters as mixture centers. The transition between different expressions is represented as the evolution of the posterior probability of the six basic paths. The experimental results demonstrate that the probabilistic approach can recognize expression transitions effectively. We also synthesize image sequences of changing expressions through the manifold model.