There has been a surge of interest in the delivery of personalized information to users (e.g., personalized stocks or travel information), particularly as mobile users with limited terminal device capabilities increasingly desire updated and targeted information in real time. When the number of information recipients is large and there is sufficient commonality in their interests, as is often the case, IP multicast is an efficient way of delivering the information. However, IP multicast services do not consider the structure and semantics of the information in the multicast process. We propose the use of Content-Based Multicast (CBM) where extra content filtering is performed at the interior nodes of the IP multicast tree; this will reduce network bandwidth usage and delivery delay, as well as the computation required at the sources and sinks. We evaluate the situations in which CBM is advantageous. The benefits of CBM depend critically upon how well filters are placed at interior nodes of the IP multicast tree and the costs depend upon those introduced by filters themselves. Further, we consider the benefits of allowing the filters to be mobile so as to respond to user mobility or changes in user interests and the corresponding costs of filter mobility. The criterion that we consider is the total network bandwidth utilization. For this criterion, we develop an optimal filter placement algorithm, as well as a heuristic that executes faster than the optimal algorithm. We evaluate the algorithms by means of simulation experiments. Our results indicate that filters can be effective in substantially reducing bandwidth. We also find filter mobility is worthwhile if there is marked large-scale user mobility. We conclude with suggestions for further work. 相似文献
Neural Computing and Applications - In order to provide benchmark performance for Urdu text document classification, the contribution of this paper is manifold. First, it provides a publicly... 相似文献
The edge computing model offers an ultimate platform to support scientific and real-time workflow-based applications over the edge of the network. However, scientific workflow scheduling and execution still facing challenges such as response time management and latency time. This leads to deal with the acquisition delay of servers, deployed at the edge of a network and reduces the overall completion time of workflow. Previous studies show that existing scheduling methods consider the static performance of the server and ignore the impact of resource acquisition delay when scheduling workflow tasks. Our proposed method presented a meta-heuristic algorithm to schedule the scientific workflow and minimize the overall completion time by properly managing the acquisition and transmission delays. We carry out extensive experiments and evaluations based on commercial clouds and various scientific workflow templates. The proposed method has approximately 7.7% better performance than the baseline algorithms, particularly in overall deadline constraint that gives a success rate.
A generic method for floor plan analysis and interpretation is presented in this article. The method, which is mainly inspired by the way engineers draw and interpret floor plans, applies two recognition steps in a bottom-up manner. First, basic building blocks, i.e., walls, doors, and windows are detected using a statistical patch-based segmentation approach. Second, a graph is generated, and structural pattern recognition techniques are applied to further locate the main entities, i.e., rooms of the building. The proposed approach is able to analyze any type of floor plan regardless of the notation used. We have evaluated our method on different publicly available datasets of real architectural floor plans with different notations. The overall detection and recognition accuracy is about 95 %, which is significantly better than any other state-of-the-art method. Our approach is generic enough such that it could be easily adopted to the recognition and interpretation of any other printed machine-generated structured documents. 相似文献
Beyond the catalytic activity of nanocatalysts, the support with architectural design and explicit boundary could also promote the overall performance through improving the diffusion process, highlighting additional support for the morphology-dependent activity. To delineate this, herein, a novel mazelike-reactor framework, namely multi-voids mesoporous silica sphere (MVmSiO2), is carved through a top-down approach by endowing core-shell porosity premade Stöber SiO2 spheres. The precisely-engineered MVmSiO2 with peripheral one-dimensional pores in the shell and interconnecting compartmented voids in the core region is simulated to prove combined hierarchical and structural superiority over its analogous counterparts. Supported with CuZn-based alloys, mazelike MVmSiO2 nanoreactor experimentally demonstrated its expected workability in model gas-phase CO2 hydrogenation reaction where enhanced CO2 activity, good methanol yield, and more importantly, a prolonged stable performance are realized. While tuning the nanoreactor composition besides morphology optimization could further increase the catalytic performance, it is accentuated that the morphological architecture of support further boosts the reaction performance apart from comprehensive compositional optimization. In addition to the found morphological restraints and size-confinement effects imposed by MVmSiO2, active sites of catalysts are also investigated by exploring the size difference of the confined CuZn alloy nanoparticles in CO2 hydrogenation employing both in-situ experimental characterizations and density functional theory calculations. 相似文献