Datacenters (DCs) are deployed in a large scale to support the ever increasing demand for data processing to support various applications. The energy consumption of DCs becomes a critical issue. Powering DCs with renewable energy can effectively reduce the brown energy consumption and thus alleviates the energy consumption problem. Owing to geographical deployments of DCs, the renewable energy generation and the data processing demands usually vary in different DCs. Migrating virtual machines (VMs) among DCs according to the availability of renewable energy helps match the energy demands and the renewable energy generation in DCs, and thus maximizes the utilization of renewable energy. Since migrating VMs incurs additional traffic in the network, the VM migration is constrained by the network capacity. The inter-datacenter (inter-DC) VM migration with network capacity constraints is an NP-hard problem. In this paper, we propose two heuristic algorithms that approximate the optimal VM migration solution. Through extensive simulations, we show that the proposed algorithms, by migrating VM among DCs, can reduce up to 31 of brown energy consumption.
The growing economical and environmental cost of data centers due to the high energy consumption is becoming a major issue. “Green Data Centers” refers to, energy aware, energy efficient and CO2 emission minimizing designs, protocols, devices, infrastructures and algorithms for data centers. Today's data centers are provisioned for peak load. However, it is shown that servers are idle most of the time. Idle servers and the connected network elements are consuming considerable amount of energy. In this survey, we identify the key enablers of green data center research. Firstly we overview the green metrics that are applicable to data centers. Then we describe the most recent stage of research and give a taxonomy of the related work. We focus on computing and networking proposals for green data centers, even though we briefly describe some other green research related to data centers such as cloud computing, cooling. Data center consumes increasing amount of power nowadays, together with expanding number of data centers and upgrading data center scale, its power consumption becomes a knotty issue. While main efforts of this research focus on server and storage power reduction, network devices as part of the key components of data centers, also contribute to the overall power consumption as data centers expand. In this paper, we address this problem with two perspectives. First, in a macro level, we attempt to reduce redundant energy usage incurred by network redundancies for load balancing. Second, in the micro level, we design algorithm to limit port rate in order to reduce unnecessary power consumption. Given the guidelines we obtained from problem formulation, we propose a solution based on greedy approach with integration of network traffic and minimization of switch link rate. We also present results from a simulation-based performance evaluation which shows that expected power saving is achieved with tolerable delay.