Resources Allocation in smart grids using fog computing

نوع: Type: thesis

مقطع: Segment: Masters

عنوان: Title: Resources Allocation in smart grids using fog computing

ارائه دهنده: Provider: Mohammad Reza Yousefi Kebria

اساتید راهنما: Supervisors: Dr Mohammad Nasiri and Dr Reza Mohammadi

اساتید مشاور: Advisory Professors:

اساتید ممتحن یا داور: Examining professors or referees: Dr Hatam Abdoli and Dr Mehdi sakhaeinia

زمان و تاریخ ارائه: Time and date of presentation: 2022/3/13 15:30

مکان ارائه: Place of presentation: online

چکیده: Abstract: A smart grid is a complete set of technologies that can be used to build or upgrade a power grid. This network can use digital devices to track energy consumption and monitor how it is consumed during its peak time (peak). In addition, it can control the energy consumption in the house or building in such a way that, if possible, high-consumption devices are turned off at peak consumption. The smart grid can have indoor surveillance systems that allow users to better manage their energy consumption. It is also possible for smart grids to allow independent energy sources, such as home solar panels or underfloor heating systems, to inject their energy into the grid. With the increasing growth of smart devices, microgrid technology has also been developed. Increasing the number of requests has increased the volume of data and computational loads on a large scale. For this reason, cloud computing is used as a solution for this amount of data. However, given the importance of service quality, the cloud computing solution may not be responsive to latency-sensitive requests. Processing workloads at the edge of the network reduces request delays; On the other hand, processing requests at the edge of the network increases energy consumption despite reducing latency. Therefore, modification of the delay model of fog devices in smart grids is much needed. In this study, we try to reduce latency and energy consumption. The forward and backward algorithm has been used due to the large number of requests and problem constraints. The proposed method reduces the delay for smart grid requests.

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