Reliability-Aware Offloading and Allocation in Multilevel Edge Computing System

Dong, Luobing; Wu, Weili; Guo, Qiumin; Satpute, Meghana N.; Znati, Taieb; Du, Dajun

doi:10.1109/tr.2019.2909279

Cited by 74 publications

(52 citation statements)

References 29 publications

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“…For example, Haritaoglu uses the minimum and maximum gray values and the largest time difference value for image sequence scenes. All the pixels in the statistics are used to create a background model that can adapt to changes in climate and light [18,19].…”

Section: Figure 1 Background Difference Methods Schematicmentioning

confidence: 99%

Simulation of tennis serve behavior based on video image processing and wireless sensor technology

Huang

2020

Preprint

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Abstract Video-based human motion analysis is an important research direction in the field of computer vision. It detects moving objects from video sequences, extracts key parts of the human body, and obtains useful information for human movements. Further analysis and identification. In this paper, the joints of the teeing arm are first color-coded. The tennis teeing video is collected by a high-speed camera. The coordinates of the tacking points in each frame are used instead of the knuckles to study the trajectory of the teeing arm. In the process of video processing, after constructing a dictionary for a series of noise maps, the sparse representation idea was used to reconstruct an interference-free service diagram, and a mixture of Gaussian background modeling was used to extract the foreground of the motion. After obtaining the motion foreground, the marker points are extracted through the color features, and binarization operations are performed on the marker points. Next, the outline of the marker points is searched, the outline is surrounded by the minimum circle, and the returned circle center coordinates are used as the joint point coordinates. Taking the trajectory of the shoulder marking point as a research object, a tennis serving model based on an improved support vector machine was established.

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Section: Figure 1 Background Difference Methods Schematicmentioning

confidence: 99%

Simulation of tennis serve behavior based on video image processing and wireless sensor technology

Huang

2020

Preprint

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“…In this paper, the author has completed the task of joint task allocation and resource allocation with the goal of minimizing the energy consumption of the mobile terminal under a certain delay requirement, and demonstrated the effectiveness of its algorithm in the simulation. Chan H [26] and others proposed a reference architecture for edge cloud, which extended the computing power of the central cloud to end users in homes or enterprises by using edge nodes provided by edge users and operators to support the operation of edge applications. The above research has done some research on the multi-terminal optimization of edge computing, but has not yet involved in-depth research on the direction of library auxiliary reading.…”

Section: Figure 2 Reference Example Framework Of Edge Computingmentioning

confidence: 99%

Research on Aided Reading System of Digital Library Based on Text Image Features and Edge Computing

Shi

Zhu

2020

IEEE Access

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“…However, with the decline in computing costs, the rapid development of sensor nodes, and the reduction of the size of microprocessors, many wireless sensor network applications have begun to be used. At present, the applications of wireless sensor networks are mainly concentrated in agriculture and biological environmental protection, industrial monitoring, home and office automation, medical treatment and nursing [32,33].…”

Section: Figure 2 Wireless Sensor Network System Structurementioning

confidence: 99%

Research on Resource Optimization of Music Multi-Terminal Based on Edge Computing

Wang

2020

IEEE Access

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The development of mobile cloud computing has increased the number of smart terminals and the computing power of processors. More and more music-type applications are loaded into the cloud, which puts a huge load on the core network. In order to solve the problem of insufficient computing resource optimization of existing music terminals, this paper proposes a resource optimization scheme based on edge computing. First, we propose a music multi-terminal architecture through a wireless sensor network to perform wireless transmission of related data and information. Secondly, we propose a music multi-terminal resource optimization model based on edge computing, which can perform fast computing and storage tasks at the edge of the music wireless network. Finally, this paper verifies the feasibility and effectiveness of the scheme by analyzing the test results of music multi-terminal cases. This technology can effectively improve the efficiency level of existing music multi-terminal resource optimization, and provide a certain reference for the development of music terminals.

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Reliability-Aware Offloading and Allocation in Multilevel Edge Computing System

Cited by 74 publications

References 29 publications

Simulation of tennis serve behavior based on video image processing and wireless sensor technology

Simulation of tennis serve behavior based on video image processing and wireless sensor technology

Research on Aided Reading System of Digital Library Based on Text Image Features and Edge Computing

Research on Resource Optimization of Music Multi-Terminal Based on Edge Computing

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