Software Defined Networking Architecture, Security and Energy Efficiency: A Survey <s> A. Energy Efficiency in SDN <s> Cloud computing is offering utility-oriented IT services to users worldwide. Based on a pay-as-you-go model, it enables hosting of pervasive applications from consumer, scientific, and business domains. However, data centers hosting Cloud applications consume huge amounts of energy, contributing to high operational costs and carbon footprints to the environment. Therefore, we need Green Cloud computing solutions that can not only save energy for the environment but also reduce operational costs. This paper presents vision, challenges, and architectural elements for energy-efficient management of Cloud computing environments. We focus on the development of dynamic resource provisioning and allocation algorithms that consider the synergy between various data center infrastructures (i.e., the hardware, power units, cooling and software), and holistically work to boost data center energy efficiency and performance. In particular, this paper proposes (a) architectural principles for energy-efficient management of Clouds; (b) energy-efficient resource allocation policies and scheduling algorithms considering quality-of-service expectations, and devices power usage characteristics; and (c) a novel software technology for energy-efficient management of Clouds. We have validated our approach by conducting a set of rigorous performance evaluation study using the CloudSim toolkit. The results demonstrate that Cloud computing model has immense potential as it offers significant performance gains as regards to response time and cost saving under dynamic workload scenarios. <s> BIB001 </s> Software Defined Networking Architecture, Security and Energy Efficiency: A Survey <s> A. Energy Efficiency in SDN <s> Networks are a shared resource connecting critical IT infrastructure, and the general practice is to always leave them on. Yet, meaningful energy savings can result from improving a network's ability to scale up and down, as traffic demands ebb and flow. We present ElasticTree, a network-wide power1 manager, which dynamically adjusts the set of active network elements -- links and switches--to satisfy changing data center traffic loads. ::: ::: We first compare multiple strategies for finding minimum-power network subsets across a range of traffic patterns. We implement and analyze ElasticTree on a prototype testbed built with production OpenFlow switches from three network vendors. Further, we examine the trade-offs between energy efficiency, performance and robustness, with real traces from a production e-commerce website. Our results demonstrate that for data center workloads, ElasticTree can save up to 50% of network energy, while maintaining the ability to handle traffic surges. Our fast heuristic for computing network subsets enables ElasticTree to scale to data centers containing thousands of nodes. We finish by showing how a network admin might configure ElasticTree to satisfy their needs for performance and fault tolerance, while minimizing their network power bill. <s> BIB002 </s> Software Defined Networking Architecture, Security and Energy Efficiency: A Survey <s> A. Energy Efficiency in SDN <s> We present the design, implementation, and evaluation of B4, a private WAN connecting Google's data centers across the planet. B4 has a number of unique characteristics: i) massive bandwidth requirements deployed to a modest number of sites, ii) elastic traffic demand that seeks to maximize average bandwidth, and iii) full control over the edge servers and network, which enables rate limiting and demand measurement at the edge. These characteristics led to a Software Defined Networking architecture using OpenFlow to control relatively simple switches built from merchant silicon. B4's centralized traffic engineering service drives links to near 100% utilization, while splitting application flows among multiple paths to balance capacity against application priority/demands. We describe experience with three years of B4 production deployment, lessons learned, and areas for future work. <s> BIB003 </s> Software Defined Networking Architecture, Security and Energy Efficiency: A Survey <s> A. Energy Efficiency in SDN <s> In recent years, Passive Optical Network (PON) is developing rapidly in the access network, in which the high energy consumption problem is attracting more and more attention. In the paper, SDN (Software Defined Network) is first introduced in optical access networks to implement an energy-efficient control mechanism through OpenFlow protocol. Some theoretical analysis work for the energy consumption of this architecture has been conducted. Numeric results show that the proposed SDN based control architecture can reduce the energy consumption of the access network, and facilitates integration of access and metro networks. <s> BIB004 </s> Software Defined Networking Architecture, Security and Energy Efficiency: A Survey <s> A. Energy Efficiency in SDN <s> The power consumption of network devices contributes to a considerable fraction of the energy expenses of data center and service providers. Recently, Software Defined Networking (SDN) has emerged as a novel networking paradigm that allows optimizing the traffic in a variety of ways, ranging from the Ethernet layer to the network layer and above. This makes SDN a versatile approach for a large number of applications. However, little is known about the power consumption of SDN-enabled networking devices, especially OpenFlow switches. This paper presents measurements and derived power consumption models for two SDN devices, namely an OpenFlow-based hardware switch (NEC PF 5240) and the Open vSwitch running on server grade hardware. The effect of configuration, management, and the managed traffic on the resulting power consumption is evaluated. Based on these measurements, a power model is derived, allowing for an estimation of the power consumption based on the configuration and network traffic only. Being available on the OpenFlow controller, the information about the power model enables an estimation of the power consumption of the full network without additional measurement equipment. The resulting model shows an error of less than 8% for the software switch and less than 1% for the hardware switch. <s> BIB005
As discussed in earlier sections, one of the major problems faced by many companies around the world is the amount of energy consumed by networks. The need for continuous availability and its huge architecture make network energy consumption high. The companies pay a significant percentage of their revenue to power their network infrastructures BIB001 . Usage of the energy efficient networks such as SDN is regarded as a solution for reducing the overall consumption of power in the network BIB004 . This attracted companies like Google to incorporate SDN in their networks BIB003 . Implementation of some energy saving strategies in SDN can reduce the overall power consumption which leads to the cost reduction BIB002 . The openness, feasibility and programmability of SDN reduces the complexity to implement energy efficiency approaches in both hardware and software. It would be more efficient to apply power saving schemes in each module for overall energy saving  . For this purpose the power consumed in SDN by each module such as chassis, routers and nodes in the network needs to be known. Furthermore, SDN is regarded as a viable solution where minimal resources could be used to perform a task without degrading overall network performance (such as security) that reduces energy consumption. Measurement model has been presented in BIB005 , where the power consumed by OpenFlow switches such as OF hardware Switch and OF vSwitch running on the server are considered for the experiment. According to the results obtained, enabling sleeping mechanisms can improvise the energy efficiency of OF vSwitch as the power consumption of network is dependent on number of active links in the network. The additional savings up to 6.6% of overall power can be achieved by setting port configuration rate to 10 Mbps. The obtained power measurements are expected to have error less than 1% in hardware switches and 8% in software. The frequent powering off and on can show its impact on decreasing the life time of networking devices. The efficiency can only be achieved when the adopted schemes do not affect the performance of the system. So, the method to be implemented in network should be selected based on characteristics of the network. Table III and Table IV provide a comparison between various energy efficiency techniques that have been proposed to implement in SDN. These tables provide working principle of each method along with advantages and disadvantages that they offer when they are implemented in SDN. The energy efficient schemes that can be implemented in SDN are discussed below.