# Resource Management in SDN-Based Cloud and SDN-Based Fog Computing: Taxonomy Study
## 4 SDN-Based Cloud Computing Resource Management in Energy Efficiency  
Many techniques were employed in order to minimize the power consumption. For example, in [21], the authors used dynamic overbooking of resources in software-defined data centers; dynamic overbooking is claimed to reduce power consumption for both hosts and network resources. Hosts and network resources are overbooked using a dynamic ratio that is determined based on current workloads, which results in the obligation of SLAs. SLA violation was measured based on response time, such that each request is measured in advance to obtain the response time under no overbooking strategy. After that, with proposed overbooking strategy, the number of requests that exceed the response time, which was previously measured, will be considered as a violation of the SLA. The performance is evaluated in the CloudSimSDN simulation tool using Wikipedia workloads as datasets. Extensive experiments were conducted that show that dynamic overbooking has an advantage over static overbooking in terms of decreasing the SLA violation rate and reduced power consumption. On the other hand, FCTcon [22] deploys a flow completion time FCT for dynamic flow management especially for delay sensitive applications. It aims to decrease the power consumption in data center networks while guarantee the required FCT. It considers the burst nature of the flow. Basically, Ftcon will receive requests with specified bandwidth requirements. Then, it will send it, with control knob = 1 to have their proposed bandwidth requirement, to traffic the consolidation unit that will determine what flow will be used, and the rest of flows will be set into sleep mode. After that, the FCT monitor unit will observe the FCT of requests and then acknowledge FCTon controller in order to modify the control knob that will either be increased or decreased value, which, in turn, will indicate number of flows to be either wake up or sleep by traffic consolidation unit in order to accommodate the FCT. The proposed work is evaluated in testbed environment using Wikipedia and Yahoo traffic files. The results show that Ftcon achieves the required request file completion time. Even though it succeeds on coping with the optimal power consumption levels, some of baselines manage to reduce power consumption below the optimal levels. Additionally, PowerFTC [23] works by considering FCT, especially for delay-sensitive flows in order to reduce the power consumption. In order to impose FCT during the consolidation process, it obtains flow paths and switch settings in advance. The evaluation, which is conducted in testbed and simulation, show that, loosely, FCT requirements lead to a higher power saving while the FCT miss ratio is the minimum in all cases. While DISCO [24] is developed to optimize power consumption in the data center networks by utilizing traffic consolidation, it offers cloud providers with two algorithms, DISCO-F and DISCO-S, to be chosen from based on the most desirable objectives which are power efficiency, scalability and enhancing the delay performance of the data center network. Both Disco-F and Disco -S perform consolidations; however, the difference lies in where the consolidation takes place. DISCO-F performs individual flow consolidation, while DISCO-S performs multiple flow consolidation on individual switches. Using Wikipedia and Yahoo traces, the evaluation results show that, in terms of delay, DISCO algorithms manage to obtain lower delay than most of baseline algorithms. However, regarding power saving, both algorithms consume more power than most baseline algorithms. Additionally, Elastic Tree [25] is a power optimizer that switches unused resources ON or OFF based on its current usability by monitoring traffic. Additionally, it targets fault tolerant and performance when making the decision of which subnet is supposed to be ON.