A Tabu Search Algorithm for the Location of Data Centers and Software Components in Green Cloud Computing Networks

Larumbe, Federico; Sansò, Brunilde

doi:10.1109/tcc.2013.2

Cited by 101 publications

(40 citation statements)

References 21 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In order to deliver the infrastructure, platform, and software as a service, that is, IaaS, PaaS, and SaaS, to cloud users, cloud providers need to build clusters of servers or even a number of cloud centers located across the country or the whole world to serve worldwide users. Therefore, service resources need to be efficiently deployed in various locations of cloud centers [Larumbe and Sanso 2013]. Moreover, different cloud providers can be grouped together to form a cloud federation that delivers more efficient cloud services or a more balanced cloud center workload, or save energy.…”

Section: Scheduling In the Deployment Layermentioning

confidence: 99%

Cloud Computing Resource Scheduling and a Survey of Its Evolutionary Approaches

et al. 2015

View full text Add to dashboard Cite

A disruptive technology fundamentally transforming the way that computing services are delivered, cloud computing offers information and communication technology users a new dimension of convenience of resources, as services via the Internet. Because cloud provides a finite pool of virtualized on-demand resources, optimally scheduling them has become an essential and rewarding topic, where a trend of using Evolutionary Computation (EC) algorithms is emerging rapidly. Through analyzing the cloud computing architecture, this survey first presents taxonomy at two levels of scheduling cloud resources. It then paints a landscape of the scheduling problem and solutions. According to the taxonomy, a comprehensive survey of state-of-the-art approaches is presented systematically. Looking forward, challenges and potential future research directions are investigated and invited, including real-time scheduling, adaptive dynamic scheduling, large-scale scheduling, multiobjective scheduling, and distributed and parallel scheduling. At the dawn of Industry 4.0, cloud computing scheduling for cyber-physical integration with the presence of big data is also discussed. Research in this area is only in its infancy, but with the rapid fusion of information and data technology, more exciting and agenda-setting topics are likely to emerge on the horizon. Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from Permissions@acm.org.

show abstract

Section: Scheduling In the Deployment Layermentioning

confidence: 99%

Cloud Computing Resource Scheduling and a Survey of Its Evolutionary Approaches

et al. 2015

View full text Add to dashboard Cite

show abstract

“…Peter Xiang Geo And et al [20] proposed FORTE (Flow Optimization based framework for request-routing and traffic engineering) to control the three-way tradeoff between average job time, electricity cost, and carbon emissions. In another study done by Federico Larumbe and Brunilde Sanso [21], a cloud network planning problem presented and a model proposed that allowed planners to evaluate different solutions and to make variations in the optimization priorities.…”

Section: Related Workmentioning

confidence: 99%

Providing a Cloud Broker-based Approach to Improve the Energy Consumption and Achieve a Green Cloud Computing

Nikoui¹,

Jabbehdari²,

Bagheri³

2016

IJCA

View full text Add to dashboard Cite

Today`s, cloud computing has been widely accepted in the industry. With the increasing popularity of cloud computing, many users and companies want to use and offer cloud computing services. The growth of cloud computing services may lead to consume a huge amount of energy and emit considerable amount of carbon dioxide. In recent years raising concerns about global warming and environment impact of greenhouse gases emission has led many researchers to engage in research in the field of green and energy aware computing. In this paper, "two phase carbon aware cloud broker" has been proposed that attempt to minimize energy and carbon by considering the energy and carbon efficiency of data centers. General TermsCloud computing, carbon emissions, energy aware.

show abstract

“…Although the resource optimization scheme proposed by Larumbe et al [21] is the closest applicable to the ITV application scenario motivating this paper [5], a number of significant drawbacks exist. Firstly, the optimization scheme, as with similar methods in the literature, does not consider the potential multicasting nature of ITV applications, i.e., when the same media is requested by several user domains.…”

Section: Related Workmentioning

confidence: 99%