# An Initial Load-Based Green Software Defined Network +
## 1 Introduction  
Since [PERSON] et al. proposed OpenFlow in 2008 [1], the concept of software defined network (SDN) has gradually rooted in the network field. Different from traditional networks, SDN moves the control function from the data forwarding devices to a centralized control plane, simplifying data forwarding devices and providing more flexibility and controllability to the network administrators. In the centralized control plane, one or more controllers manage the traffic flow according to the global view of the network, providing a higher capability for handling network problems. In this paper, we mainly focus on the energy waste problem in SDN. As reported in [2], the energy consumption of information and communication technologies (ICT) were responsible for more than 8% of the global electricity consumption in 2008. Furthermore, it has been predicted that this percentage will increase dramatically in future years. Under such high energy consumption, the efficiency of the network energy is very low, which results in a serious energy waste problem. Generally, networks are always designed to satisfy the peak periods of the network traffic. However, for most of the time, the traffic load of the network is far below that in peak periods. This causes underutilization of the network devices. For example, in the previous network of Google,the average utilization of all the links was 30\(\sim\)40% [3]. Yet the energy consumption of the devices in low utilization periods is almost as same as that in heavy load periods [4], resulting in low energy efficiency of the network devices. It is of great importance to improve the energy efficiency of the network, both for reducing the operation cost of internet service provider (ISP) and for environment pollution reasons. Much research has studied the energy waste problem from different network levels. For both wireless networks and core wired networks, a common way to reduce energy waste is by putting the idle devices into low-power sleep mode or switching them off when in low traffic periods. For example, in [5, 6], the authors propose a switch on/off algorithm to improve the energy efficiency of the base stations in LTE-Advanced networks. The work in [7, 8] considers the problem in general cellular networks, and addresses the problem on the premise of switching off base stations. Reference [9] works on the energy saving problem in heterogeneous networks based on the switch off strategy. For core wired networks, instead of base stations, the devices such as routers and switches (or parts of them, such as ports) are considered to turn to sleep mode for energy saving. In [10], sleeping methods are divided into two categories, uncoordinated sleeping and coordinated sleeping. Uncoordinated sleeping refers to systems where network devices determine whether turn to sleep according to their own respective status. In coordinated sleeping which devices turn to sleep is determined by all the network devices jointly, routing the traffic on part of the devices according to the current traffic load, and sleeping the idle part. Obviously, in regard to the ability of saving energy coordinated sleeping performs better than uncoordinated sleeping. Much research such as [4, 11, 12] based on the premise of coordinated sleeping made efforts to improve the energy efficiency of the network. However, there are many difficulties in executing the coordinated sleeping in traditional networks. As discussed in [10], first, some network protocols must be changed. For example, the Hello message should be sent only among the active devices. Secondly, which devices should be put into sleep mode is a complicated problem for distributed control networks. Thirdly, some unexpected side effects such as route oscillation may be caused. Thanks to the centralized controller(s), in SDN coordinated sleeping will be easy to deploy without these difficulties.