Journal
IEEE COMMUNICATIONS LETTERS
Volume 26, Issue 7, Pages 1623-1627Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/LCOMM.2022.3168500
Keywords
Costs; Time factors; Cloud computing; Optimization; Servers; Edge computing; Computational modeling; Edge computing; Lagrangian cooperation; fog computing; internet of things
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As a new paradigm, smart cities face challenges such as processing huge volumes of data within limited time constraints. To tackle this, fog computing is introduced, enabling cooperation between servers from the network edge to the cloud. Although it reduces response time, it also increases data volume in the fog layer and thus energy costs. To address this, a convex problem is introduced and solved using a Lagrangian Cooperation algorithm, which outperforms existing approaches.
As a new paradigm, smart cities face many issues such as huge volumes of data and limited time for processing. To meet these challenges, fog computing via cooperation between servers from the network edge to the cloud is introduced. This can significantly reduce the response time, but also increase the amount of data in the fog layer and thus energy costs. Therefore, a convex problem is introduced to minimize the response time and energy costs. This problem is solved via a Lagrangian Cooperation (LC) algorithm. Results are presented which show that the proposed LC algorithm provides better performance than existing approaches.
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