Research On The Energy Optimizing Strategy Of Software Defined Mobile Networking

With the rapid growth of mobile internet and popularization of 4 G, more and more mobile users want to access audios and videos which are stored in the internet at any time and in any place. So, the mobile users' load is increasing day after day. In order to deal with the peak value of mobile data, the resources of mobile network must be deployed overly. And, the energy consumption is huge. This paper chooses SDN (Software Defined Networks) as the researching network framework. The constraint of original static network frame can be removed via introducing the SDN network frame which is characterized by separation of control plane and data plane.This kind of new network frame is easy to be managed and controlled. So, more theories and more technologies are able to be applied in the mobile network energy saving. Network controller supports programming and is easy to be deployed. Those characters make our energy saving strategies more robust, more efficient, and more simplicity.Huge energy consumption decreases the input-output ratio, operator's profit, and mobile users' QoE. So, under the guarantee of mobile users' QoS,mobile network energy consumption optimization has been a research hot spot. This paper is going to be started from the part of wireless resource schedule to research mobile network energy consumption optimization. The high energy consumption BSs are chosen as the research objects. Through researching, plenty of idle resources are found to exist in the mobile network for a long time. These idle mobile network resources are able to be predicted and found. So these idle mobile network resources can be gained and put into sleeping states, then the purpose of energy saving can be gained. This has been the paper5 s core researching target.Researches are carried out from three aspects.1. In the research of mobile network datacenter energy saving, aimed at the question of idle network frame and unreasonable processes scheduling,the SDN idea is drawn into the datacenter network frame. Network controller interacts with network components and every server by using OpenFlow protocol. Network states can be collected full-scaly and timely. This information is necessary for the design of energy optimizing strategy. In order to gain the most utilization of active RAMs, this paper uses optimizing theory to design processes scheduling strategy.2. In the backbone network energy consumption optimization researching of mobile network, aimed at the problem of control and forwarding tight coupling,network states instant collecting and how to keep low network responding time, SDN is choosen as network frame. In SDN network frame, network controller is able to gain the states of network topology at any time. So, the network management becomes more easy and effective. The energy saving strategy is based on OSPF protocol. So, the network reconfiguration time is reduced dramatically when the energy saving strategy is running. This reduces the energy saving strategy is more feasibility. The energy saving problem is abstracted as MCP (Maximum Clique Problem) and design an energy saving strategy which is named as SNESS (Backbone networks energy saving strategy). The purpose is gained via running this energy saving strategy.3. In the access network BSs energy saving strategy,aimed at the problem of energy strategy influences the video stream's quality and how to choose the video stream's quality level under the guaranteeing video stream's smoothly playing,video stream is choosen as the researching object. In this part, the SDMN is also choosen as the network architect and introduce the idea of SDN to access network. The access network energy saving strategy is abstracted as MILP (Mixed-Integer Linear Programming). Firstly,a BSs' grouping strategy is given. More BSs are able to be set to sleeping mode via running this strategy. Secondly, an active BSs' transmitting time optimization strategy is provided. Under the guarantee of users' QoS, the BSs'transmission time can be reduced effectively via running this strategy. The energy saving goal is gained.