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- Type of Document: M.Sc. Thesis
- Language: Farsi
- Document No: 53798 (19)
- University: Sharif University of Technology
- Department: Computer Engineering
- Advisor(s): Koohi, Somayyeh
- Abstract:
- It is well known that data centres consume high amounts of energy, which has become a major concern in the field of cloud computing. Therefore, energy consumption could be reduced by using intelligent mechanisms work to adapt the set of network components to the total traffic volume. SDN is an efficient way to do so because it has many benefits over traditional approaches, such as centralised management, low capex, flexibility, scalability and virtualisation of network functions. In our work will we use the heuristic energy-aware routing (HEAR) model, which is composed of the proposed heuristic algorithm and the energy-aware routing algorithm. This work identifies the unused links and switches then puts it is into sleep mode during periods of low traffic load that will saves energy by using the algorithms with SDN. We used simulations with Mininet and the Ryu controller with a fat-tree topology. To analyse the test-data collection, the proposed HEAR model was compared to each of the Dijkstra algorithms and to a traffic prediction-based energy efficiency optimisation (TPEO) algorithm. The results show that the proposed model achieved a 60.8% energy saving, In addition, improving network performance by decreasing the network delay, low jitter, and enhance network throughput to limits the packets loss
- Keywords:
- Traffic Management ; Fat Tree ; Heuristic Algorithm ; Software Defined Networks (SDN) ; Data Center ; Energy Aware ; Energy-aware Routing
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