Guest Editors' Introduction: Special Issue on Green and Energy-Efficient Cloud Computing: Part I

  title={Guest Editors' Introduction: Special Issue on Green and Energy-Efficient Cloud Computing: Part I},
  author={Ricardo Bianchini and Samee Ullah Khan and Carlo Mastroianni},
  journal={IEEE Trans. Cloud Comput.},
The papers in this special section focus on green and energy efficient cloud computing. Cloud computing has had a huge commercial impact and has attracted the interest of the research community. Public clouds allow their customers to outsource the management of physical resources, and rent a variable amount of resources in accordance to their specific needs. Private clouds allow companies to manage on-premises resources, exploiting the capabilities offered by the cloud technologies, such as… 
Reducing the Operational Cost of Cloud Data Centers through Renewable Energy
Investigation of a complex infrastructure composed of data centers located in different geographical areas in which renewable energy generators are installed, co-located with the data centers, to reduce the amount of energy that must be purchased by the power grid shows that renewable energy can be effectively exploited in geographical data centers when a smart load allocation strategy is implemented.
A Comparative Analysis of Data-Driven Consolidation Policies for Energy-Efficient Clouds
  • A. Altomare, Eugenio Cesario
  • Computer Science
    2017 25th Euromicro International Conference on Parallel, Distributed and Network-based Processing (PDP)
  • 2017
A comparative analysis of consolidation strategies of virtual machines in Cloud systems, driven by predictive data mining models, shows several insights in terms of energy saving and most efficient consolidation strategies.
Private databases on the cloud: Models, issues and research perspectives
This paper focuses the attention on state-of-the-art proposals in the area of private databases over Clouds, and proposes critical comments about pros and cons of actual research efforts along with future research directions to be considered in future years.
GREEN SDN — An enhanced paradigm of SDN: Review, taxonomy, and future directions
A comprehensive review on SDN while mapping the characteristics of green computing with SDN is provided and the research stressed on the benefits of Green SDN through a proposed G‐SDN framework.
How to make key 5G wireless technologies environmental friendly: A review
The review concludes that the 5G technology will soon fulfill the critical requirements of low‐energy network while maintaining services with high performance and potential research opportunities related to green 5G are highlighted.


Exploiting Renewable Sources: When Green SLA Becomes a Possible Reality in Cloud Computing
A scheme for green energy management in the presence of explicit and implicit integration of renewable energy in data center is presented and greenSLA algorithm is introduced which leverages the concept of virtualization of green energy to provide per interval specific Green SLA.
Hierarchical SLA-Driven Resource Management for Peak Power-Aware and Energy-Efficient Operation of a Cloud Datacenter
The proposed resource management algorithms reduce the operational cost of a datacenter by about 40 percent while satisfying SLA constraints and decrease the run-time of the management algorithms by up to 86 percent with respect to the state of the art centralized management solution.
Towards Robust Green Virtual Cloud Data Center Provisioning
This paper proposes two effective, computation-efficient and energy-efficient embedding algorithms for virtual data center (VDC) embedding, which are being regarded as a promising technology to provide performance guarantee for cloud computing applications.
Proactive Thermal-Aware Resource Management in Virtualized HPC Cloud Datacenters
An innovative proactive thermal-aware virtual machine consolidation (involving allocations as well as migrations) technique is proposed to maximize computing resource utilization, to minimize datacenter energy consumption for computing, and to improve the efficiency of heat extraction.
On Achieving Energy Efficiency and Reducing CO2 Footprint in Cloud Computing
The experimental and validation results show the potential of the eco-aware approach to significantly reduce the CO2 footprint and consequent environmental impact of cloud applications.
Pervasive Cloud Controller for Geotemporal Inputs
This paper proposes a pervasive cloud controller for dynamic resource reallocation adapting to volatile time- and location-dependent factors, while considering the QoS impact of too frequent migrations and the data quality limits of time series forecasting methods.
Decentralized and Energy-Efficient Workload Management in Enterprise Clouds
An evaluation and comparative study of the proposed approach provides evidence of its merits in terms of elasticity, energy efficiency, and scalability, as well as of its feasibility in the presence of high workload rates.
Energy-Efficient Virtual Machines Scheduling in Multi-Tenant Data Centers
This paper proposes algorithms to reduce energy consumption by data centers by considering the placement of virtual machines onto the servers in the data center intelligently, and examines the performance of these two algorithms in both small and large clusters using real data traces and synthetic workloads, and compares them to other alternatives.
EnReal: An Energy-Aware Resource Allocation Method for Scientific Workflow Executions in Cloud Environment
An energy consumption model is presented for applications deployed across cloud computing platforms, and a corresponding energy-aware resource allocation algorithm is proposed for virtual machine scheduling to accomplish scientific workflow executions.
Off-Peak Energy Optimization for Links in Virtualized Network Environment
Multiple novel energy saving reconfiguration methods that globally/locally optimize VNE’s link power consumption, during off-peak time are discussed, and simulation results prove the proposed solutions are able to save notable amount of energy in physical links During off- peak time.