Abstract
The concept of fog computing is initiated to mitigate the load on cloud. Fog computing assists cloud computing services. It extends the services of cloud computing. The permanent storage of the data is come to pass in cloud. An environment based on fog and cloud is providd to manage the energy demand of the consumers. It deals with the data of buildings which are linked with clusters. To assist cloud, six fogs are deployed in three regions, which are found on three continents of the world. In addition, each fog is connected with clusters of buildings. There are eighty buildings in each cluster. These buildings are Smart Grid (SG) buildings. For the management of consumers energy demand, Micro Grids (MGs) are available near by buildings and reachable by fogs. The central object is to manage the energy requirements, so, fog assists consumers to attain their energy requirements by using MGs and cloud servers that are near to them. However, for balancing the load on cloud the implementation of an algorithm is needed. Virtual Machines (VMs) are also required. Pigeon hole algorithm is used for this purpose. Using proposed techniques results are compared with Round Robin (RR) which gives better results. The proposed technique in this paper is showing better results in terms of response time.
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Gilani, W.A., Javaid, N., Khan, M.K., Maqbool, H., Ali, S., Qureshi, D.M. (2019). Optimized Load Balancing Using Cloud Computing. In: Barolli, L., Kryvinska, N., Enokido, T., Takizawa, M. (eds) Advances in Network-Based Information Systems. NBiS 2018. Lecture Notes on Data Engineering and Communications Technologies, vol 22. Springer, Cham. https://doi.org/10.1007/978-3-319-98530-5_22
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DOI: https://doi.org/10.1007/978-3-319-98530-5_22
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