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.
Mandal ph et al @cite_14 studied green energy aware VM migration techniques to reduce the energy consumption of DCs. They proposed an algorithm to enhance the green energy utilization by migrating VMs according to the available green energy in DCs. However, they did not consider the network constraints while migrating VMs among DCs. In the optical networks, the available spectrum is limited. The large amount of traffic generated by the VM migration may congest the optical networks and increase the blocking rate of the network. Therefore, it is important to consider the network constraints in migrating VMs. In this paper, we propose algorithms to solve the green energy aware inter-DC VM migration problem with network constraints.
@cite_14
1983667143
Cloud computing is the new paradigm of operation in information technology. While cloud computing infrastructures have benefits, their energy consumption is becoming a growing concern. Data centers, which are used to provide the infrastructure and resource pool for cloud computing, consume a large amount of energy. Future energy consumption predictions of these data centers are even bigger concerns. To reduce this energy consumption, and hence the carbon footprint and greenhouse gas emission of cloud computing, and information technology in general, energy-efficient methods of operation have to be investigated and adopted. In addition, renewable energy usage in place of non-renewable can also reduce carbon emission. However, due to its intermittency and volatility, renewable energy cannot be used to its full potential. In this study, we introduce the renewable-energy- aware cloud service and virtual machine migration to relocate energy demand using dynamic and flexible cloud resource allocation techniques, and help overcome the challenges of renewable energy. Results from a U.S.-wide cloud network infrastructure show that, using simple migration techniques, up to 30 percent nonrenewable energy can be replaced by renewable energy, while consuming only a small amount of extra resources and energy to perform demand relocation.