Smart Grid Management Using Cloud and Fog Computing
Autor: | Nadeem Javaid, Faizan Saeed, Sadam Hussain Abbasi, Muhammad Usman Sharif, Muhammad Hassaan Ashraf, Mubariz Rehman |
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Rok vydání: | 2018 |
Předmět: |
Computer science
business.industry Response time 020206 networking & telecommunications Cloud computing 02 engineering and technology computer.software_genre Scheduling (computing) Smart grid Virtual machine Server 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing The Internet Electricity business computer Computer network |
Zdroj: | Advances in Network-Based Information Systems ISBN: 9783319985299 NBiS |
DOI: | 10.1007/978-3-319-98530-5_54 |
Popis: | Cloud computing provides Internet-based services to its consumer. Multiple requests on cloud server simultaneously cause processing latency. Fog computing act as an intermediary layer between Cloud Data Centers (CDC) and end users, to minimize the load and boost the overall performance of CDC. For efficient electricity management in smart cities, Smart Grids (SGs) are used to fulfill the electricity demand. In this paper, a proposed system designed to minimize energy wastage and distribute the surplus energy among energy deficient SGs. A three-layered cloud and fog based architecture described for efficient and fast communication between SG’s and electricity consumers. To manage the SG’s requests, fog computing introduced to reduce the processing time and response time of CDC. For efficient scheduling of SG’s requests, proposed system compare three different load balancing algorithms: Round Robin (RR), Active Monitoring Virtual Machine (AMVM) and Throttled for SGs electricity requests scheduling on fog servers. Dynamic service broker policy is used to decide that which request should be routed on fog server. For evaluation of the proposed system, results performed in cloud analyst, which shows that AMVM and Throttled outperform RR by varying virtual machine placement cost at fog servers. |
Databáze: | OpenAIRE |
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