A long video caption generation algorithm for big video data retrieval

In mobile crowd-sensing (MCS) network, it is necessary to reduce the cost of sensing data transformation from mobile devices to the MCS platform in the core of the network. With the widespread deployment of access point (AP), explosive data traffic of the mobile devices is offloaded from cellular base stations to Wi-Fi networks. The congestion of the 2.4 GHz band in dual-band wireless area network makes the lower quality of experience (QoE) of users. To ease the load of 2.4 GHz band, the band-steering technology has been widely used by equipment manufacturers. However, the fixed threshold configuration strategy in band steering technology makes it easy to be exploited by setting up a great number of connection requirements in a short time, which may prevent a normal connection requirement of a user, making it difficult to satisfy the dynamic resource requirements of different services. Moreover, if the threshold is configured too high, it may result in QoE imbalance in dual bands. Besides, when the band (such as 2.4 GHz) resources cannot meet the terminal requirement, the terminal cannot autonomously switch to another band (such as 5 GHz), and this may result in a very poor QoE of users. In this paper, a secure QoE-oriented wireless network optimization framework is proposed to improve the QoE of users in dual-band network. Firstly, to ensure the overall QoE of network and balancing the QoE between 2.4 GHz and 5 GHz bands, the framework dynamically adjusts the load threshold of the frequency band based on QoE information during the association of a terminal. Secondly, to meet the basic QoE requirement of each user, the framework preferentially switches the terminals with poor QoE to the idle band after users join the network. The experimental results show that the proposed framework can improve the QoE both before and after the terminal accesses the network. Additionally, it enables the better QoE balance in dual bands.

Section: Related Workmentioning

confidence: 99%

Band Steering Technology Based on QoE-Oriented Optimization in Wireless Network

Han

Liao

et al. 2020

“…In other aspects, many methods for the big data have been proposed to ensure the effectiveness of the data [10][11][12]. In [13], Ding et al proposed a long video caption generation algorithm for big video data retrieval.…”

Section: Related Workmentioning

confidence: 99%

An efficient storage and service method for multi-source merging meteorological big data in cloud environment

He¹,

Zhang²,

Xu³

et al. 2019

With the development of the meteorological IoT (Internet of Things) and meteorological sensing network, the collected multi-source meteorological data have the characteristics of large amount of information, multidimensional and high accuracy. Cloud computing technology has been applied to the storage and service of meteorological big data. Although the constant evolution of big data storage technology is improving the storage and access of meteorological data, storage and service efficiency is still far from meeting multi-source big data requirements. Traditional methods have been used for the storage and service of meteorological data, and a number of problems still persist, such as a lack of unified storage structure, poor scalability, and poor service performance. In this study, an efficient storage and service method for multidimensional meteorological data is designed based on NoSQL big data storage technology and the multidimensional characteristics of meteorological data. In the process of data storage, multidimensional block compression technology and data structures are applied to store and transmit meteorological data. In service, heterogeneous NoSQL common components are designed to improve the heterogeneity of the NoSQL database. The results show that the proposed method has good storage transmission efficiency and versatility, and can effectively improve the efficiency of meteorological data storage and service in meteorological applications.

“…LOD technology is based on a series of evaluation criteria to select different precision to achieve the object of multiresolution display [26]. Generally, the LOD technology in the traditional geometric modeling means that the number of vertices in a geometric model is determined by the distance from the object to the viewpoint [27][28][29]. For the particle system, when the viewpoint is close, more particles are generated; on the contrary, fewer particles.…”

Section: Display With the Distancementioning

confidence: 99%

A simulation method of three-dimensional cloud over WRF big data

Xie

Kou

2019

Nowadays, due to the expansion of people's living ranges and the impact of human life on the natural environment, climate changes fiercely than before. In order to observe the changing climate environment accurately, multi-modal sensors are used to collect the various data around us, and we could analyze and predict the weather based on these collected data. One of the applications is 3D visualization simulation, and the 3D visualization simulation of cloud data has always been the research hotspot in the field of computer graphics and meteorology. Currently, it is a key challenge to resolve the problems of 3D cloud simulation, such as reducing complexity of modeling and computation and improving the real-time performance. Technically, a method for data modeling and optimizing based on Weather Research and Forecasting (WRF) is proposed in this paper, aiming to solve the problems of the existing 3D cloud simulation and realize 3D virtual simulation of real-world cloud data. According to the characteristics (e.g., color, size, shape) of the cloud, the spherical particle system is designed to model, and the initial color, size, shape, and other attributes are given to these spherical particles to realize the modeling of WRF cloud data. From the perspective of new particles' generation, the level of detail (LOD) technique, based on the relationship between the quantity of new generated spherical particles and the distance of the viewpoint, is used to change the quantity of new particles generated in real time according to the distance of the simulated scene distance. Finally, illumination model is introduced to render and simulate the modeling particles. Experimental simulation results verify the effectiveness of this method in improving the modeling and rendering speed of cloud data as well as the fidelity of the 3D virtualization model.