Task aware optimized energy cost and carbon emission-based virtual machine placement in sustainable data centers

2021 ◽  
pp. 1-13
Author(s):  
T. Renugadevi ◽  
K. Geetha
Keyword(s):  
Energy Management ◽  
Energy Cost ◽  
Carbon Emission ◽  
Data Centers ◽  
Cloud Services ◽  
It Services ◽  
Allocation Algorithm ◽  
Cloud Data ◽  
Services Delivery ◽  
Workload Allocation

Management of IT services is rapidly adapting to the cloud computing environment due to optimized service delivery models. Geo distributed cloud data centers act as a backbone for providing fundamental infrastructure for cloud services delivery. Conversely, their high growing energy consumption rate is the major problem to be addressed. Cloud providers are in a hunger to identify different solutions to tackle energy management and carbon emission. In this work, a multi-cloud environment is modeled as geographically distributed data centers with varying solar power generation corresponding to its location, electricity price, carbon emission, and carbon tax. The energy management of the workload allocation algorithm is strongly dependent on the nature of the application considered. The task deadline and brownout information is used to bring in variation in task types. The renewable energy-aware workload allocation algorithm adaptive to task nature is proposed with migration policy to explore its impact on carbon emission, total energy cost, brown and renewable power consumption.

Energy-Efficiency in Cloud Data Centers

2013 ◽  
pp. 241-263
Author(s):  
Burak Kantarci ◽  
Hussein T. Mouftah
Keyword(s):  
Cloud Computing ◽  
Energy Consumption ◽  
Data Center ◽  
Energy Efficient ◽  
Large Scale ◽  
Data Centers ◽  
High Energy ◽  
It Services ◽  
Data Center Network ◽  
Cloud Data

Cloud computing aims to migrate IT services to distant data centers in order to reduce the dependency of the services on the limited local resources. Cloud computing provides access to distant computing resources via Web services while the end user is not aware of how the IT infrastructure is managed. Besides the novelties and advantages of cloud computing, deployment of a large number of servers and data centers introduces the challenge of high energy consumption. Additionally, transportation of IT services over the Internet backbone accumulates the energy consumption problem of the backbone infrastructure. In this chapter, the authors cover energy-efficient cloud computing studies in the data center involving various aspects such as: reduction of processing, storage, and data center network-related power consumption. They first provide a brief overview of the existing approaches on cool data centers that can be mainly grouped as studies on virtualization techniques, energy-efficient data center network design schemes, and studies that monitor the data center thermal activity by Wireless Sensor Networks (WSNs). The authors also present solutions that aim to reduce energy consumption in data centers by considering the communications aspects over the backbone of large-scale cloud systems.

Cloud Load Balancing Algorithms: A Comparative Assessment

2019 ◽  
Vol 16 (9) ◽  
pp. 3989-3994
Author(s):  
Jaspreet Singh ◽  
Deepali Gupta ◽  
Neha Sharma
Keyword(s):  
Cloud Computing ◽  
Load Balancing ◽  
Data Centers ◽  
Research Area ◽  
Comparative Assessment ◽  
Cloud Services ◽  
Cloud Data ◽  
Cloud Data Centers ◽  
Cloud Users

Nowadays, Cloud computing is developing quickly and customers are requesting more administrations and superior outcomes. In the cloud domain, load balancing has turned into an extremely intriguing and crucial research area. Numbers of algorithms were recommended to give proficient mechanism for distributing the cloud user’s requests for accessing pool cloud resources. Also load balancing in cloud should provide notable functional benefits to cloud users and at the same time should prove out to be eminent for cloud services providers. In this paper, the pre-existing load balancing techniques are explored. The paper intends to provide landscape for classification of distinct load balancing algorithms based upon the several parameters and also address performance assessment bound to various load balancing algorithms. The comparative assessment of various load balancing algorithms will helps in proposing a competent load balancing technique for intensify the performance of cloud data centers.

scholarly journals Network Traffic Analysis in Cloud: A Survey

2019 ◽  
Vol 8 (S2) ◽  
pp. 61-65
Author(s):  
K. Ruckshana ◽  
G. Ravi
Keyword(s):  
Network Traffic ◽  
Data Centers ◽  
Service Providers ◽  
Instant Messaging ◽  
Detection System ◽  
It Services ◽  
Cloud Data ◽  
Traffic Characteristics ◽  
Secure Cloud Computing ◽  
The One

A data center (DC) denotes to any huge faithful group of computers that is retained and operated by an organization. Data centers of numerous sizes are being made and hired for a dissimilar set of resolves today. On the one hand, big universities and isolated enterprises gradually consolidating their IT services within on-site data centers comprising hundreds to thousands of servers. On the other hand, huge online service providers such as Google, Microsoft, and Amazon quickly constructing geographically varied cloud data centers often have more than 10K servers; to offer a variation of cloud-based services such as Email, Web servers, Gaming, Storage, and Instant Messaging. Though there is great interest in planning developed networks for data centers, very little is identified about the network-level traffic characteristics of present data centers. In this paper, we focused on a study of the network traffic in data centers and defining the anomaly detection system in secure cloud computing environment.

Virtual machine placement mechanisms in the cloud environments: a systematic review

Kybernetes ◽  
2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Haiyan Zhuang ◽  
Babak Esmaeilpour Ghouchani
Keyword(s):  
Data Centers ◽  
Virtual Machines ◽  
Cloud Services ◽  
Future Research ◽  
Cloud Environment ◽  
Content Type ◽  
Cloud Data ◽  
Refining Performance ◽  
Cloud Data Centers ◽  
Cloud Environments

Purpose Virtual machines (VMs) are suggested by the providers of cloud services as the services for the users over the internet. The consolidation of VM is the tactic of the competent and smart utilization of resources from cloud data centers. Placement of a VM is one of the significant issues in cloud computing (CC). Physical machines in a cloud environment are aware of the way of the VM placement (VMP) as the mapping VMs. The basic target of placement of VM issue is to reduce the physical machines' items that are running or the hosts in cloud data centers. The VMP methods have an important role in the CC. However, there is no systematic and complete way to discuss and analyze the algorithms. The purpose of this paper is to present a systematic survey of VMP techniques. Also, the benefits and weaknesses connected with selected VMP techniques have been debated, and the significant issues of these techniques are addressed to develop the more efficient VMP technique for the future. Design/methodology/approach Because of the importance of VMP in the cloud environments, in this paper, the articles and important mechanisms in this domain have been investigated systematically. The VMP mechanisms have been categorized into two major groups, including static and dynamic mechanisms. Findings The results have indicated that an appropriate VMP has the capacity to decrease the resource consumption rate, energy consumption and carbon emission rate. VMP approaches in computing environment still need improvements in terms of reducing related overhead, consolidation of the cloud environment to become an extremely on-demand mechanism, balancing the load between physical machines, power consumption and refining performance. Research limitations/implications This study aimed to be comprehensive, but there were some limitations. Some perfect work may be eliminated because of applying some filters to choose the original articles. Surveying all the papers on the topic of VMP is impossible, too. Nevertheless, the authors are trying to present a complete survey over the VMP. Practical implications The consequences of this research will be valuable for academicians, and it can provide good ideas for future research in this domain. By providing comparative information and analyzing the contemporary developments in this area, this research will directly support academics and working professionals for better knowing the growth in the VMP area. Originality/value The gathered information in this paper helps to inform the researchers with the state of the art in the VMP area. Totally, the VMP's principal intention, current challenges, open issues, strategies and mechanisms in cloud systems are summarized by explaining the answers.

scholarly journals Cost Efficient Real Time Electricity Management Services for Green Community Using Fog

Energies ◽  
2020 ◽  
Vol 13 (12) ◽  
pp. 3164
Author(s):  
Rasool Bukhsh ◽  
Muhammad Umar Javed ◽  
Aisha Fatima ◽  
Nadeem Javaid ◽  
Muhammad Shafiq ◽  
...  
Keyword(s):  
Real Time ◽  
Energy Management ◽  
Data Center ◽  
Energy Cost ◽  
Energy Demand ◽  
Data Centers ◽  
Management Service ◽  
Cooling Systems ◽  
Electricity Cost ◽  
Cost Efficient

The computing devices in data centers of cloud and fog remain in continues running cycle to provide services. The long execution state of large number of computing devices consumes a significant amount of power, which emits an equivalent amount of heat in the environment. The performance of the devices is compromised in heating environment. The high powered cooling systems are installed to cool the data centers. Accordingly, data centers demand high electricity for computing devices and cooling systems. Moreover, in Smart Grid (SG) managing energy consumption to reduce the electricity cost for consumers and minimum rely on fossil fuel based power supply (utility) is an interesting domain for researchers. The SG applications are time-sensitive. In this paper, fog based model is proposed for a community to ensure real-time energy management service provision. Three scenarios are implemented to analyze cost efficient energy management for power-users. In first scenario, community’s and fog’s power demand is fulfilled from the utility. In second scenario, community’s Renewable Energy Resources (RES) based Microgrid (MG) is integrated with the utility to meet the demand. In third scenario, the demand is fulfilled by integrating fog’s MG, community’s MG and the utility. In the scenarios, the energy demand of fog is evaluated with proposed mechanism. The required amount of energy to run computing devices against number of requests and amount of power require cooling down the devices are calculated to find energy demand by fog’s data center. The simulations of case studies show that the energy cost to meet the demand of the community and fog’s data center in third scenario is 15.09% and 1.2% more efficient as compared to first and second scenarios, respectively. In this paper, an energy contract is also proposed that ensures the participation of all power generating stakeholders. The results advocate the cost efficiency of proposed contract as compared to third scenario. The integration of RES reduce the energy cost and reduce emission of CO 2 . The simulations for energy management and plots of results are performed in Matlab. The simulation for fog’s resource management, measuring processing, and response time are performed in CloudAnalyst.

scholarly journals Real-Time Energy Management for Cloud Data Centers in Smart Microgrids

IEEE Access ◽  
2016 ◽  
Vol 4 ◽  
pp. 941-950 ◽  
Author(s):  
Liang Yu ◽  
Tao Jiang ◽  
Yulong Zou
Keyword(s):  
Real Time ◽  
Energy Management ◽  
Data Centers ◽  
Cloud Data ◽  
Cloud Data Centers
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