Energy Management in Smart Sectors Using Fog Based Environment and Meta-Heuristic Algorithms
Smart Grid (SG) plays vital role in modern electricity grid. The data is increasing with the drastic increase in number of users. An efficient technology is required to handle this dramatic growth of data. Cloud computing is then used to store the data and to provide numerous services to the consume...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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IEEE
2019-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/8884157/ |
| _version_ | 1818412580268408832 |
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| author | Zahoor Ali Khan Ayesha Anjum Butt Turki Ali Alghamdi Aisha Fatima Mariam Akbar Muhammad Ramzan Nadeem Javaid |
| author_facet | Zahoor Ali Khan Ayesha Anjum Butt Turki Ali Alghamdi Aisha Fatima Mariam Akbar Muhammad Ramzan Nadeem Javaid |
| author_sort | Zahoor Ali Khan |
| collection | DOAJ |
| description | Smart Grid (SG) plays vital role in modern electricity grid. The data is increasing with the drastic increase in number of users. An efficient technology is required to handle this dramatic growth of data. Cloud computing is then used to store the data and to provide numerous services to the consumers. There are various cloud Data Centers (DC), which deal with the requests coming from consumers. However, there is a chance of delay due to the large geographical area between cloud and consumer. So, a concept of fog computing is presented to minimize the delay and to maximize the efficiency. However, the issue of load balancing is raising; as the number of consumers and services provided by fog grow. So, an enhanced mechanism is required to balance the load of fog. In this paper, a three-layered architecture comprising of cloud, fog and consumer layers is proposed. A meta-heuristic algorithm: Improved Particle Swarm Optimization with Levy Walk (IPSOLW) is proposed to balance the load of fog. Consumers send request to the fog servers, which then provide services. Further, cloud is deployed to save the records of all consumers and to provide the services to the consumers, if fog layer is failed. The proposed algorithm is then compared with existing algorithms: genetic algorithm, particle swarm optimization, binary PSO, cuckoo with levy walk and BAT. Further, service broker policies are used for efficient selection of DC. The service broker policies used in this paper are: closest data center, optimize response time, reconfigure dynamically with load and new advance service broker policy. Moreover, response time and processing time are minimized. The IPSOLW has outperformed to its counterpart algorithms with almost 4.89% better results. |
| first_indexed | 2024-12-14T10:49:34Z |
| format | Article |
| id | doaj.art-63103139006f4a9b99918f5e662d8a44 |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-14T10:49:34Z |
| publishDate | 2019-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-63103139006f4a9b99918f5e662d8a442022-12-21T23:05:18ZengIEEEIEEE Access2169-35362019-01-01715725415726710.1109/ACCESS.2019.29498638884157Energy Management in Smart Sectors Using Fog Based Environment and Meta-Heuristic AlgorithmsZahoor Ali Khan0Ayesha Anjum Butt1Turki Ali Alghamdi2https://orcid.org/0000-0001-6706-2183Aisha Fatima3https://orcid.org/0000-0001-9620-4806Mariam Akbar4Muhammad Ramzan5Nadeem Javaid6https://orcid.org/0000-0003-3777-8249Computer Information Science Division, Higher Colleges of Technology, Fujairah, United Arab EmiratesDepartment of Computer Science, COMSATS University Islamabad, Islamabad, PakistanDepartment of Computer Science, College of Computer and Information Systems, Umm Al-Qura University, Makkah, Saudi ArabiaDepartment of Computer Science, COMSATS University Islamabad, Islamabad, PakistanDepartment of Computer Science, COMSATS University Islamabad, Islamabad, PakistanDepartment of Computer Science and IT, University of Sargodha, Sargodha, PakistanDepartment of Computer Science, COMSATS University Islamabad, Islamabad, PakistanSmart Grid (SG) plays vital role in modern electricity grid. The data is increasing with the drastic increase in number of users. An efficient technology is required to handle this dramatic growth of data. Cloud computing is then used to store the data and to provide numerous services to the consumers. There are various cloud Data Centers (DC), which deal with the requests coming from consumers. However, there is a chance of delay due to the large geographical area between cloud and consumer. So, a concept of fog computing is presented to minimize the delay and to maximize the efficiency. However, the issue of load balancing is raising; as the number of consumers and services provided by fog grow. So, an enhanced mechanism is required to balance the load of fog. In this paper, a three-layered architecture comprising of cloud, fog and consumer layers is proposed. A meta-heuristic algorithm: Improved Particle Swarm Optimization with Levy Walk (IPSOLW) is proposed to balance the load of fog. Consumers send request to the fog servers, which then provide services. Further, cloud is deployed to save the records of all consumers and to provide the services to the consumers, if fog layer is failed. The proposed algorithm is then compared with existing algorithms: genetic algorithm, particle swarm optimization, binary PSO, cuckoo with levy walk and BAT. Further, service broker policies are used for efficient selection of DC. The service broker policies used in this paper are: closest data center, optimize response time, reconfigure dynamically with load and new advance service broker policy. Moreover, response time and processing time are minimized. The IPSOLW has outperformed to its counterpart algorithms with almost 4.89% better results.https://ieeexplore.ieee.org/document/8884157/Cloud computingfog computingsmart gridsmart cityload balancingserver broker policies |
| spellingShingle | Zahoor Ali Khan Ayesha Anjum Butt Turki Ali Alghamdi Aisha Fatima Mariam Akbar Muhammad Ramzan Nadeem Javaid Energy Management in Smart Sectors Using Fog Based Environment and Meta-Heuristic Algorithms IEEE Access Cloud computing fog computing smart grid smart city load balancing server broker policies |
| title | Energy Management in Smart Sectors Using Fog Based Environment and Meta-Heuristic Algorithms |
| title_full | Energy Management in Smart Sectors Using Fog Based Environment and Meta-Heuristic Algorithms |
| title_fullStr | Energy Management in Smart Sectors Using Fog Based Environment and Meta-Heuristic Algorithms |
| title_full_unstemmed | Energy Management in Smart Sectors Using Fog Based Environment and Meta-Heuristic Algorithms |
| title_short | Energy Management in Smart Sectors Using Fog Based Environment and Meta-Heuristic Algorithms |
| title_sort | energy management in smart sectors using fog based environment and meta heuristic algorithms |
| topic | Cloud computing fog computing smart grid smart city load balancing server broker policies |
| url | https://ieeexplore.ieee.org/document/8884157/ |
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