Abstract
Fog computing idea is presented to reduce the burden on cloud and deliver similar facilities as cloud. However, fog encompasses small area relatively to cloud by saving the data for shorter amount of time and sending it to cloud for permanent storage. In this paper, a joint cloud and fog centered environment for efficient energy supervision of buildings is proposed. It caters for the data of groups of buildings at buyers’ end. 12 fogs are utilized for 6 different regions in the world which are based on 6 continents. Additionally, each fog is linked to a group of buildings and two fogs are linked to two groups. Each group comprises of multiple smart buildings and these buildings has at least 100 apartments. To manage the energy requirement of consumers, micro grids (MGs) are available near the buildings and accessible by the fogs. Energy is managed for the apartments and fog helps the consumers to fulfill their load demands through nearby MGs and cloud servers’ communication. So, the load on cloud and fog should be balanced and load balancing algorithms are used to manage the load using VMs. These algorithms are round robin (RR) and throttled and Priority Based load balancing and these algorithms are compared for a single service broker policy. Service broker policy considered in this paper is; dynamically reconfigure with load. Priority based load balancing is proposed for balancing the load on fog and results of proposed balancing algorithm are compared with other algorithms. While considering the proposed algorithm, results are compared with two load balancing algorithms and from this, the proposed algorithm gives better results than RR algorithm rather than throttled.
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Tariq, S., Javaid, N., Majeed, M., Ahmed, F., Nazir, S. (2019). Priority Based Load Balancing in Cloud and Fog Based Systems. In: Barolli, L., Leu, FY., Enokido, T., Chen, HC. (eds) Advances on Broadband and Wireless Computing, Communication and Applications. BWCCA 2018. Lecture Notes on Data Engineering and Communications Technologies, vol 25. Springer, Cham. https://doi.org/10.1007/978-3-030-02613-4_65
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