Green Computing and Power Saving in HPC Data Centers

2011 ◽  
Author(s):  
Osvaldo Marra ◽  
Maria Mirto ◽  
Massimo Cafaro ◽  
Aloisio Giovanni
Keyword(s):  
Data Centers ◽  
Power Saving ◽  
Green Computing

Green Computing: Design of a Reactive Monitoring Solution for Power Saving

2011 ◽  
Author(s):  
Osvaldo Marra ◽  
Maria Mirto ◽  
Massimo Cafaro ◽  
Aloisio Giovanni
Keyword(s):  
Power Saving ◽  
Green Computing ◽  
Reactive Monitoring

Energy-Efficiency in a Cloud Computing Backbone

2013 ◽  
pp. 283-305
Author(s):  
Burak Kantarci ◽  
Hussein T. Mouftah
Keyword(s):  
Cloud Computing ◽  
Energy Consumption ◽  
High Performance ◽  
Data Centers ◽  
High Capacity ◽  
Power Saving ◽  
Cloud Services ◽  
Mixed Integer ◽  
Ip Over Wdm ◽  
Challenges And Opportunities

Cloud computing combines the advantages of several computing paradigms and introduces ubiquity in the provisioning of services such as software, platform, and infrastructure. Data centers, as the main hosts of cloud computing services, accommodate thousands of high performance servers and high capacity storage units. Offloading the local resources increases the energy consumption of the transport network and the data centers although it is advantageous in terms of energy consumption of the end hosts. This chapter presents a detailed survey of the existing mechanisms that aim at designing the Internet backbone with data centers and the objective of energy-efficient delivery of the cloud services. The survey is followed by a case study where Mixed Integer Linear Programming (MILP)-based provisioning models and heuristics are used to guarantee either minimum delayed or maximum power saving cloud services where high performance data centers are assumed to be located at the core nodes of an IP-over-WDM network. The chapter is concluded by summarizing the surveyed schemes with a taxonomy including the cons and pros. The summary is followed by a discussion focusing on the research challenges and opportunities.

scholarly journals Energy Aware Data Centers and Networks: a Survey

2018 ◽  
Vol 4 ◽  
pp. 26-36 ◽  
Author(s):  
Piotr Arabas
Keyword(s):  
Power Control ◽  
Data Centers ◽  
Hierarchical Control ◽  
Power Saving ◽  
Control Algorithms ◽  
Control Mechanisms ◽  
Energy Aware ◽  
The Past ◽  
Need For Power ◽  
Network Topologies

The past years have brought about a great variety of clusters and clouds. This, combined with their increasing size and complexity, has resulted in an obvious need for power-saving control mechanisms. Upon presenting a basis on which such solutions - namely low-level power control interfaces, CPU governors and network topologies – are constructed, the paper summarizes network and cluster resources control algorithms. Finally, the need for integrated, hierarchical control is expressed, and specific examples are provided.

Power-saving policies for annual energy cost savings in green computing

2019 ◽  
Vol 33 (4) ◽  
pp. e4225
Author(s):  
Bhisham Sharma ◽  
Payal Mittal ◽  
Mohammad S. Obaidat
Keyword(s):  
Energy Cost ◽  
Power Saving ◽  
Cost Savings ◽  
Green Computing

Autonomic Green Computing in Large-Scale Data Centers

2012 ◽  
pp. 271-299 ◽  
Author(s):  
Haoting Luo ◽  
Bithika Khargharia ◽  
Salim Hariri ◽  
Youssif Al-Nashif
Keyword(s):  
Large Scale ◽  
Data Centers ◽  
Green Computing ◽  
Large Scale Data ◽  
Scale Data

Incentive-Based Scheduling for Green Computational Grid

2021 ◽  
pp. 272-293
Author(s):  
Low Tang Jung ◽  
Ahmed Abba Haruna
Keyword(s):  
High Performance ◽  
Data Centers ◽  
Large Data ◽  
Computing System ◽  
Green Computing ◽  
Grid Environment ◽  
Computing Grid ◽  
Main Component ◽  
It Operations ◽  
Over Time

In the computing grid environment, jobs scheduling is fundamentally the process of allocating computing jobs with choices relevant to the available resources. As the scale of grid computing system grows in size over time, exponential increase in energy consumption is foreseen. As such, large data centers (DC) are embarking on green computing initiatives to address the IT operations impact on the environment. The main component within a computing system consuming the most electricity and generating the most heat is the microprocessor. The heat generated by these high-performance microprocessors is emitting high CO2 footprint. Therefore, jobs scheduling with thermal considerations (thermal-aware) to the microprocessors is important in DC grid operations. An approach for jobs scheduling is proposed in this chapter for reducing electricity usage (green computing) in DC grid. This approach is the outcome of the R&D works based on the DC grid environment in Universiti Teknologi PETRONAS, Malaysia.

scholarly journals Virtual CPU Scaling for Efficient Server Power Consumption in Cloud Data Center

2020 ◽  
Vol 3 (2) ◽  
pp. 11-20
Author(s):  
Noora N. Bhaya ◽  
Rabah A. Ahmed
Keyword(s):  
Cloud Computing ◽  
Power Efficiency ◽  
Data Centers ◽  
Power Saving ◽  
Processing Unit ◽  
Cloud Infrastructure ◽  
Financial Benefit ◽  
Cloud Data Center ◽  
Cloud Data ◽  
Central Processing

Cloud computing is a fast-growing technology used by major corporations these days because of the flexibility framework it provides to consumers. Cloud technology requires large data centers consisting of multiple IT equipment and servers. One main problem with these data centers is the vast amount of power consumed during servers operation. This reduces financial benefit and increases the need to produce more energy to cover the needs of operating the cloud infrastructure. This paper proposes an approach for managing the virtual central processing unit (vCPU) of a virtual machine to improve server power efficiency. A framework is used to study the proposed approach while processing different types of workloads widely found in most general-purpose cloud computing applications. Results indicate an improvement in server power saving.

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