Mathematical Models for Task Assignment with Service Level Agreement in Fog Computing Networks
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Fog computing was proposed to bridge the gap between the cloud computing capabilities and the new requirements introduced by 5G and IoT applications. Assigning clients' requests to fog nodes for processing while meeting the quality of service requirements is still a challenge. In this thesis, we propose two mathematical models for the task assignment problem in fog networks. The main objective of both models is to maximize the fog service provider's profit while satisfying the service level agreement requirements of the offloaded tasks. In addition, each model addresses multiple requirements to satisfy various service provider's needs. The first model addresses green computing requirements through an energy efficient fog nodes operation. The second model addresses load balancing requirements by minimizing the difference between the node's utilization across the fog network. Since these models provide optimal solutions, they can be useful with historical data and for benchmarking various real-time algorithms.
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Copyright © 2022 the author(s). Theses may be used for non-commercial research, educational, or related academic purposes only. Such uses include personal study, research, scholarship, and teaching. Theses may only be shared by linking to Carleton University Institutional Repository and no part may be used without proper attribution to the author. No part may be used for commercial purposes directly or indirectly via a for-profit platform; no adaptation or derivative works are permitted without consent from the copyright owner.
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salem-mathematicalmodelsfortaskassignmentwithservice.pdf | 2023-05-05 | Public | Download |