Paper Info
Title
Goal-driven Optimization Strategy for Energy and Performance-Aware Data Centers for Cloud-Based Wind Farm CMS.
Abstract
A cloud computing system can be characterized by the provision of resources in the form of services to third parties on a leased, usage-based basis, as well as the private infrastructures maintained and utilized by individual organizations. To attain the desired reliability and energy efficiency in a cloud data center, trade-offs need to be carried out between system performance and power consumption. Resolving these conflicting goals is often the major challenge encountered in the design of optimization strategies for cloud data centers. The work presented in this paper is directed towards the development of an Energy-efficient and Performance-aware Cloud System equipped with strategies for dynamic switching of optimization approach. Moreover, a platform is also provided for the deployment of a Wind Farm CMS (Condition Monitoring System) which allows ubiquitous access. Due to the geographically-dispersed nature of wind farms, the CMS can take advantage of the cloud's highly scalable architecture in order to keep a reliable and efficient operation capable of handling multiple simultaneous users and huge amount of monitoring data. Using the proposed cloud architecture, a Wind Farm CMS is deployed in a virtual platform to monitor and evaluate the aging conditions of the turbine's major components in concurrent, yet isolated working environments.
Year
DOI
Venue
2016
10.3837/tiis.2016.03.024
KSII TRANSACTIONS ON INTERNET AND INFORMATION SYSTEMS
Keywords
Field
DocType
Cloud Data Centers,Cloud Computing,Green Computing,Wind Turbines,Condition Monitoring System
Software deployment,Green computing,Computer science,Efficient energy use,Dynamic switching,Condition monitoring,Turbine,Wind power,Cloud computing,Distributed computing
Journal
Volume
Issue
ISSN
10
3
1976-7277
Citations 
PageRank 
References 
0
0.34
0
Authors
3
Name
Order
Citations
PageRank
Frank Elijorde151.61
Sungho Kim221924.80
Jaewan Lee36214.66