scholarly journals Application of Internet of Things and Edge Computing Technology in Sports Tourism Services

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Benxia Zheng ◽  
Zheng Mei ◽  
Liangyu Hou ◽  
Shuoli Qiu
Keyword(s):  
Energy Consumption ◽  
Internet Of Things ◽  
Edge Computing ◽  
Computing Technology ◽  
Retrieval Time ◽  
Sports Tourism ◽  
Tourism Resources ◽  
Tourism Service ◽  
Service Application ◽  
Tourism Services

Aiming at the problems of long retrieval time of sports tourism data, high integration error of sports tourism data, and high energy consumption of sports tourism service management in traditional methods, the application of Internet of Things and edge computing technology in sports tourism services is proposed. We established a sports tourism service application model based on Internet technology to realize the functions of sports tourism service internal management control, external collaboration, and information release. We calculated the similarity of sports tourism resources from the two levels of feature words and the environment where the sports tourism resources are located. According to the calculation results, the edge computing method is used to realize the integration of sports tourism service resources to improve the application effect of sports tourism service application models. The experimental results show that the minimum data retrieval time of the proposed method is only 2.35s. The sports tourism data fusion error is low. The management energy consumption is small, which significantly improves the existing problems and fully verifies the practical application value of the method.

A Research on Smart Tourism Service Mechanism Based on Context Awareness

2014 ◽  
Vol 519-520 ◽  
pp. 752-758 ◽  
Author(s):  
Wen Long Feng ◽  
Yu Cong Duan ◽  
Meng Xin Huang ◽  
Lin Feng Dong ◽  
Xiao Yi Zhou ◽  
...  
Keyword(s):  
Context Awareness ◽  
Contextual Information ◽  
Distributed Processing ◽  
Individual Characteristics ◽  
Storage And Retrieval ◽  
Context Data ◽  
Tourism Resources ◽  
Tourism Service ◽  
The Individual ◽  
Tourism Services

The traditional tourism services tend to use tourism resources as the center. They ignore individual characteristics and contextual information of the user side. The provided service is static, and doesnt meet the real needs of the users. A service mechanism based on context awareness is presented which consists of data, platform and services. It sets up data center based on users and gets context data according to rules .It uses the cloud computing technology to provide distributed processing, storage and retrieval capability for big data. It also establishes tourism service confirming to requirements of the users and dynamic adjusts service mode according to the user context information. Simulation results show that the mechanism can realize the demand for tourism services in conjunction with the individual characteristics of user.

scholarly journals Research on Intelligent Scheduling Mechanism in Edge Network for Industrial Internet of Things

2022 ◽  
Vol 2022 ◽  
pp. 1-14
Author(s):  
Zhenzhong Zhang ◽  
Wei Sun ◽  
Yanliang Yu
Keyword(s):  
Resource Allocation ◽  
Cloud Computing ◽  
Internet Of Things ◽  
Task Scheduling ◽  
Edge Computing ◽  
The Internet ◽  
Computing Technology ◽  
Industrial Internet Of Things ◽  
Industrial Internet ◽  
Internet Of Things Technology

With the vigorous development of the Internet of Things, the Internet, cloud computing, and mobile terminals, edge computing has emerged as a new type of Internet of Things technology, which is one of the important components of the Industrial Internet of Things. In the face of large-scale data processing and calculations, traditional cloud computing is facing tremendous pressure, and the demand for new low-latency computing technologies is imminent. As a supplementary expansion of cloud computing technology, mobile edge computing will sink the computing power from the previous cloud to a network edge node. Through the mutual cooperation between computing nodes, the number of nodes that can be calculated is more, the types are more comprehensive, and the computing range is even greater. Broadly, it makes up for the shortcomings of cloud computing technology. Although edge computing technology has many advantages and has certain research and application results, how to allocate a large number of computing tasks and computing resources to computing nodes and how to schedule computing tasks at edge nodes are still challenges for edge computing. In view of the problems encountered by edge computing technology in resource allocation and task scheduling, this paper designs a dynamic task scheduling strategy for edge computing with delay-aware characteristics, which realizes the reasonable utilization of computing resources and is required for edge computing systems. This paper proposes a resource allocation scheme combined with the simulated annealing algorithm, which minimizes the overall performance loss of the system while keeping the system low delay. Finally, it is verified through experiments that the task scheduling and resource allocation methods proposed in this paper can significantly reduce the response delay of the application.

An Algorithm of Mobile Edge Computing Offloading Based on Improved SPEA2 Algorithm

2021 ◽  
Author(s):  
Dan Ye ◽  
Xiaogang Wang ◽  
Jin Hou
Keyword(s):  
Energy Consumption ◽  
Internet Of Things ◽  
Cost Estimation ◽  
Edge Computing ◽  
Task Execution ◽  
Pareto Solution ◽  
Strength Pareto Evolutionary Algorithm ◽  
The Cost ◽  
Execution Delay ◽  
The Internet Of Things

Abstract Internet of things devices can offload some tasks to the edge servers through the wireless network, thus the computing pressure and energy consumption are reduced. But this will increase the cost of communication. Therefore, it is necessary to maintain the balance between task execution energy and experiment when designing the offloading strategy for the edge computing scenario of the Internet of things. This paper proposes an offloading strategy which can optimize the energy consumption and time delay of task execution at the same time. This strategy satisfies different preferences of users. First, the above task is modeled as a multi-objective optimization problem, and the Pareto solution set is found by improving the strength Pareto evolutionary algorithm (SPEA2). Based on the Pareto set, the offloading strategy satisfying the requires of users with different preferences by offloading cost estimation. Second, a simulation experiment is carried out to verify the robustness of the improved SPEA2 algorithm under the influence of different main parameters. By comparing with other algorithms. It is proved that the improved SPEA2 algorithm can minimize the balance between task execution delay and energy consumption.

scholarly journals Computing Unloading Strategy of Massive Internet of Things Devices Based on Game Theory in Mobile Edge Computing

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Xinhui Ding ◽  
Wenjuan Zhang
Keyword(s):  
Game Theory ◽  
Energy Consumption ◽  
Internet Of Things ◽  
Transmission Rate ◽  
Mobile User ◽  
Edge Computing ◽  
Communication Model ◽  
Mobile Edge Computing ◽  
Computing Model ◽  
The Game Theory

Due to the limited computing resources of the mobile edge computing (MEC) server, a massive Internet of things device computing unloading strategy using game theory in mobile edge computing is proposed. First of all, in order to make full use of the massive local Internet of things equipment resources, a new MEC system computing an unloading system model based on device-to-device (D2D) communication is designed and modeled, including communication model, task model, and computing model. Then, by using the utility function, the parameters are substituted into it, and the optimization problem with the goal of maximizing the number of CPU cycles and minimizing the energy consumption is constructed with the unloading strategy and power as constraints. Finally, the game theory is used to solve the problem of computing offload. Based on the proposed beneficial task offload theory, combined with the mobile user device computing offload task amount, transmission rate, idle device performance, and other factors, the computing offload scheme suitable for their own situation is selected. The simulation results show that the proposed scheme has better convergence characteristics, and, compared with other schemes, the proposed scheme significantly improves the amount of data transmission and reduces the energy consumption of the task.

Joint Optimization of Energy Consumption and Latency in Mobile Edge Computing for Internet of Things

2019 ◽  
Vol 6 (3) ◽  
pp. 4791-4803 ◽  
Author(s):  
Laizhong Cui ◽  
Chong Xu ◽  
Shu Yang ◽  
Joshua Zhexue Huang ◽  
Jianqiang Li ◽  
...  
Keyword(s):  
Energy Consumption ◽  
Internet Of Things ◽  
Edge Computing ◽  
Joint Optimization ◽  
Mobile Edge Computing

The Appraisal and Countermeasure Analysis of the International Competitiveness of Tourism Service Trade in Henan Province

2021 ◽  
pp. 45-47
Author(s):  
Lin Zhu ◽  
Yuqing Geng ◽  
Heshun Zhang
Keyword(s):  
Henan Province ◽  
Service Trade ◽  
Central Plains ◽  
Factors Influencing ◽  
Diamond Model ◽  
Export Competitiveness ◽  
The Status ◽  
Tourism Resources ◽  
Tourism Service ◽  
Tourism Services

With the continuous development of the macro-economy and the Internet of transportation and trade worldwide, the status of trade in tourism services is getting higher and higher. Henan has a long history and rich and colorful culture. As the birthplace of Central Plains Civilization, Henan has rich tourism resources. This paper analyzes the export status of the tourism service trade in Henan Province by using relevant data and analyzes the factors influencing the competitiveness of the tourism service trade in Henan Province by using the diamond model; this paper puts forward some suggestions to improve the export competitiveness of tourism service trade in Henan Province.

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