Abstract:
Significant growth of Big Data leads to a great opportunity for data analysis. Data centers are continuously becoming more popular. At the same time data centers' cost ar...Show MoreMetadata
Abstract:
Significant growth of Big Data leads to a great opportunity for data analysis. Data centers are continuously becoming more popular. At the same time data centers' cost are increasing as the amount of data is growing. Simply as Big Data is significantly increasing, data centers are facing new challenges. Hence the idea of geo-distributed data center is introduced. This paper investigates on the main challenges that data centers face and presents analyses for cost minimization methods. Parameters involved are analyzed. Simulation results show that joint parameters techniques outperformed separate parameter techniques.
Date of Conference: 26-27 July 2016
Date Added to IEEE Xplore: 09 January 2017
ISBN Information:
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- IEEE Keywords
- Index Terms
- Data Center ,
- Minimum Cost ,
- Geo-distributed Data Center ,
- Big Data ,
- Service Providers ,
- Service Quality ,
- Data Storage ,
- Big Data Analytics ,
- Mixed-integer Programming ,
- Load Distribution ,
- Communication Cost ,
- Mixed Integer Linear Programming ,
- Mixed-integer Nonlinear Programming ,
- Data Placement ,
- Big Data Processing ,
- Data Chunks ,
- Dynamic Policy ,
- Minimum Cost Flow
- Author Keywords
Keywords assist with retrieval of results and provide a means to discovering other relevant content. Learn more.
- IEEE Keywords
- Index Terms
- Data Center ,
- Minimum Cost ,
- Geo-distributed Data Center ,
- Big Data ,
- Service Providers ,
- Service Quality ,
- Data Storage ,
- Big Data Analytics ,
- Mixed-integer Programming ,
- Load Distribution ,
- Communication Cost ,
- Mixed Integer Linear Programming ,
- Mixed-integer Nonlinear Programming ,
- Data Placement ,
- Big Data Processing ,
- Data Chunks ,
- Dynamic Policy ,
- Minimum Cost Flow
- Author Keywords