Task Scheduling Based on Grey Wolf Optimizer Algorithm for Smart Meter Embedded Operating System
In recent years, with the rapid development of electric power informatization, smart meters are gradually developing towards intelligent IOT. Smart meters can not only measure user status, but also interconnect and communicate with cell phones, smart homes and other cloud devices, and these core fun...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Faculty of Mechanical Engineering in Slavonski Brod, Faculty of Electrical Engineering in Osijek, Faculty of Civil Engineering in Osijek
2022-01-01
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| Series: | Tehnički Vjesnik |
| Subjects: | |
| Online Access: | https://hrcak.srce.hr/file/408391 |
| _version_ | 1827281968546447360 |
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| author | Wang Shuang Duan Xiaomeng Zhao Ting Wang Xiaodong |
| author_facet | Wang Shuang Duan Xiaomeng Zhao Ting Wang Xiaodong |
| author_sort | Wang Shuang |
| collection | DOAJ |
| description | In recent years, with the rapid development of electric power informatization, smart meters are gradually developing towards intelligent IOT. Smart meters can not only measure user status, but also interconnect and communicate with cell phones, smart homes and other cloud devices, and these core functions are completed by the smart meter embedded operating system. Due to the dynamic heterogeneity of the user program side and the system processing side of the embedded system, resource allocation and task scheduling is a challenging problem for embedded operating systems of smart meters. Smart meters need to achieve fast response and shortest completion time for user program side requests, and also need to take into account the load balancing of each processing node to ensure the reliability of smart meter embedded systems. In this paper, based on the advanced Grey Wolf Optimizer, we study the scheduling principle of the service program nodes in the smart meter operating system, and analyze the problems of the traditional scheduling algorithm to find the optimal solution. Compared with traditional algorithms and classical swarm intelligence algorithms, the algorithm proposed in this paper avoids the dilemma of local optimization, can quickly allocate operating system tasks, effectively shorten the time consumption of task scheduling, ensure the real-time performance of multi task scheduling, and achieve the system tuning balance. Finally, the effectiveness of the algorithm is verified by simulation experiments. |
| first_indexed | 2024-04-24T09:10:10Z |
| format | Article |
| id | doaj.art-1fa1e5f0a94944c7ac5ee591c331d7fb |
| institution | Directory Open Access Journal |
| issn | 1330-3651 1848-6339 |
| language | English |
| last_indexed | 2024-04-24T09:10:10Z |
| publishDate | 2022-01-01 |
| publisher | Faculty of Mechanical Engineering in Slavonski Brod, Faculty of Electrical Engineering in Osijek, Faculty of Civil Engineering in Osijek |
| record_format | Article |
| series | Tehnički Vjesnik |
| spelling | doaj.art-1fa1e5f0a94944c7ac5ee591c331d7fb2024-04-15T17:56:52ZengFaculty of Mechanical Engineering in Slavonski Brod, Faculty of Electrical Engineering in Osijek, Faculty of Civil Engineering in OsijekTehnički Vjesnik1330-36511848-63392022-01-012951629163610.17559/TV-20220518055833Task Scheduling Based on Grey Wolf Optimizer Algorithm for Smart Meter Embedded Operating SystemWang Shuang0Duan Xiaomeng1Zhao Ting2Wang Xiaodong3Institute of Metrology, Chinese Academy of Electricity Power, Beijing 100192, ChinaInstitute of Metrology, Chinese Academy of Electricity Power, Beijing 100192, ChinaInstitute of Metrology, Chinese Academy of Electricity Power, Beijing 100192, ChinaInstitute of Metrology, Chinese Academy of Electricity Power, Beijing 100192, ChinaIn recent years, with the rapid development of electric power informatization, smart meters are gradually developing towards intelligent IOT. Smart meters can not only measure user status, but also interconnect and communicate with cell phones, smart homes and other cloud devices, and these core functions are completed by the smart meter embedded operating system. Due to the dynamic heterogeneity of the user program side and the system processing side of the embedded system, resource allocation and task scheduling is a challenging problem for embedded operating systems of smart meters. Smart meters need to achieve fast response and shortest completion time for user program side requests, and also need to take into account the load balancing of each processing node to ensure the reliability of smart meter embedded systems. In this paper, based on the advanced Grey Wolf Optimizer, we study the scheduling principle of the service program nodes in the smart meter operating system, and analyze the problems of the traditional scheduling algorithm to find the optimal solution. Compared with traditional algorithms and classical swarm intelligence algorithms, the algorithm proposed in this paper avoids the dilemma of local optimization, can quickly allocate operating system tasks, effectively shorten the time consumption of task scheduling, ensure the real-time performance of multi task scheduling, and achieve the system tuning balance. Finally, the effectiveness of the algorithm is verified by simulation experiments.https://hrcak.srce.hr/file/408391gray wolf algorithmheterogeneous multicoreload balancingreal time |
| spellingShingle | Wang Shuang Duan Xiaomeng Zhao Ting Wang Xiaodong Task Scheduling Based on Grey Wolf Optimizer Algorithm for Smart Meter Embedded Operating System Tehnički Vjesnik gray wolf algorithm heterogeneous multicore load balancing real time |
| title | Task Scheduling Based on Grey Wolf Optimizer Algorithm for Smart Meter Embedded Operating System |
| title_full | Task Scheduling Based on Grey Wolf Optimizer Algorithm for Smart Meter Embedded Operating System |
| title_fullStr | Task Scheduling Based on Grey Wolf Optimizer Algorithm for Smart Meter Embedded Operating System |
| title_full_unstemmed | Task Scheduling Based on Grey Wolf Optimizer Algorithm for Smart Meter Embedded Operating System |
| title_short | Task Scheduling Based on Grey Wolf Optimizer Algorithm for Smart Meter Embedded Operating System |
| title_sort | task scheduling based on grey wolf optimizer algorithm for smart meter embedded operating system |
| topic | gray wolf algorithm heterogeneous multicore load balancing real time |
| url | https://hrcak.srce.hr/file/408391 |
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