Intelligent Scheduling Method Supporting Stadium Sharing
At present, the fast-paced work and life make people under great pressure, and people’s enthusiasm for fitness is getting higher and higher, which is in contradiction with the shortage of existing stadiums. So it is considerably significant to open shared stadiums near where citizens live for bookin...
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| Format: | Article |
| Language: | English |
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Wiley
2021-01-01
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| Series: | Discrete Dynamics in Nature and Society |
| Online Access: | http://dx.doi.org/10.1155/2021/3143434 |
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| author | Lei Fang |
| author_facet | Lei Fang |
| author_sort | Lei Fang |
| collection | DOAJ |
| description | At present, the fast-paced work and life make people under great pressure, and people’s enthusiasm for fitness is getting higher and higher, which is in contradiction with the shortage of existing stadiums. So it is considerably significant to open shared stadiums near where citizens live for booking. Therefore, how to allow citizens to book a suitable stadium according to their own needs through mobile phones or computers is an urgent problem to be solved. The booking of the shared stadium can be regarded as a mobile edge computing (MEC) scenario, and the problem can be transformed into task scheduling research under MEC through intelligent scheduling method. When using edge computing (EC) technology for service calculation, the mobile terminal needs to offload the service to the edge computing server. After the server completes the calculation, the calculation results will be sent back to the mobile terminal. Therefore, the calculation time and system energy consumption in the calculation process can be further reduced through task scheduling to improve user satisfaction. In this study, joint scheduling of service caching and task algorithm is proposed to reduce the latency of booking shared stadium request and improve user experience. The simulation results show that the proposed algorithm with edge cooperation idea can achieve lower average system latency at lower load level and can significantly reduce the cloud offloading ratio under low and middle pressure. In addition, the proposed algorithm uses the secondary transfer of more tasks to reduce the pressure of local task running. Finally, the quality of experience (QoE) satisfaction rate under low pressure is guaranteed. |
| format | Article |
| id | doaj-art-b76b552722c94b38b2d143e6b386713c |
| institution | Kabale University |
| issn | 1607-887X |
| language | English |
| publishDate | 2021-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Discrete Dynamics in Nature and Society |
| spelling | doaj-art-b76b552722c94b38b2d143e6b386713c2025-02-03T07:24:09ZengWileyDiscrete Dynamics in Nature and Society1607-887X2021-01-01202110.1155/2021/3143434Intelligent Scheduling Method Supporting Stadium SharingLei Fang0Jilin Agricultural Science and Technology UniversityAt present, the fast-paced work and life make people under great pressure, and people’s enthusiasm for fitness is getting higher and higher, which is in contradiction with the shortage of existing stadiums. So it is considerably significant to open shared stadiums near where citizens live for booking. Therefore, how to allow citizens to book a suitable stadium according to their own needs through mobile phones or computers is an urgent problem to be solved. The booking of the shared stadium can be regarded as a mobile edge computing (MEC) scenario, and the problem can be transformed into task scheduling research under MEC through intelligent scheduling method. When using edge computing (EC) technology for service calculation, the mobile terminal needs to offload the service to the edge computing server. After the server completes the calculation, the calculation results will be sent back to the mobile terminal. Therefore, the calculation time and system energy consumption in the calculation process can be further reduced through task scheduling to improve user satisfaction. In this study, joint scheduling of service caching and task algorithm is proposed to reduce the latency of booking shared stadium request and improve user experience. The simulation results show that the proposed algorithm with edge cooperation idea can achieve lower average system latency at lower load level and can significantly reduce the cloud offloading ratio under low and middle pressure. In addition, the proposed algorithm uses the secondary transfer of more tasks to reduce the pressure of local task running. Finally, the quality of experience (QoE) satisfaction rate under low pressure is guaranteed.http://dx.doi.org/10.1155/2021/3143434 |
| spellingShingle | Lei Fang Intelligent Scheduling Method Supporting Stadium Sharing Discrete Dynamics in Nature and Society |
| title | Intelligent Scheduling Method Supporting Stadium Sharing |
| title_full | Intelligent Scheduling Method Supporting Stadium Sharing |
| title_fullStr | Intelligent Scheduling Method Supporting Stadium Sharing |
| title_full_unstemmed | Intelligent Scheduling Method Supporting Stadium Sharing |
| title_short | Intelligent Scheduling Method Supporting Stadium Sharing |
| title_sort | intelligent scheduling method supporting stadium sharing |
| url | http://dx.doi.org/10.1155/2021/3143434 |
| work_keys_str_mv | AT leifang intelligentschedulingmethodsupportingstadiumsharing |