18-06-2012, 01:44 PM
HBA: Distributed Metadata Management for Large Cluster-Based Storage Systems
Abstract of the Project:-
An efficient and distributed scheme for file mapping or file lookup is critical in decentralizing metadata management within a group of metadata servers, here the technique used called HIERARCHICAL BLOOM FILTER ARRAYS (HBA) to map filenames to the metadata servers holding their metadata. The Bloom filter arrays with different levels of accuracies are used on each metadata server.
The first one with low accuracy and used to capture the destination metadata server information of frequently accessed files. The other array is used to maintain the destination metadata information of all files. Simulation results show our HBA design to be highly effective and efficient in improving the performance and scalability of file systems in clusters with 1,000 to 10,000 nodes (or superclusters) and with the amount of data in the petabyte scale or higher. HBA is reducing metadata operation by using the single metadata architecture instead of 16 metadata server.
Existing System:-
File mapping or file lookup is critical in decentralizing metadata management within a group of metadata servers. Following approaches are used in the Existing system.
Table-Based Mapping : It fails to balance the load.
Hashing-Based Mapping : It has slow directory operations, such as listing the
Directory contents And renaming directories .
Static Tree Partitioning : Cannot balance the load and has a medium lookup
Time.
Dynamic Tree Partitioning : Small memory overhead, incurs a large migration
overhead.
Proposed Systems:-
Here we are using the new approaches called HIERARCHICAL BLOOM FILTER ARRAYS (HBA), efficiently route metadata request within a group of metadata servers. There are two arrays used here. First array is used to reduce memory overhead, because it captures only the destination metadata server information of frequently accessed files to keep high management efficiency. And the second one is used to maintain the destination metadata information of all files. Both the arrays are mainly used for fast local lookup.
Environment:-
• Servers:
• Operating System Server: - Microsoft Windows XP/2000 or Higher
• Data Base Server: Microsoft SQL Server 2005/2008
• Clients: Microsoft Internet Explorer (Client Browser)
• Development Tools: Microsoft Visual Studio .Net 2008/2010
• Documentation Tools: MS Office 2007/2010
• Drawing Tools: IBM Rational Rose Enterprise, MS Office Visio 2007
• User Interface: ASP.NET With AJAX
• Code Behind: VC#.NET
HARDWARE REQUIREMENTS:-
• PIV 2.8 GHz Processor and Above
• RAM 1GB and Above
• HDD 40 GB Hard Disk Space and Above
SOFTWARE REQUIREMENTS:-
• WINDOWS OS (XP / 2000 / 2000 Server / 2003 Server)
• Visual Studio .Net 2008/2010 Enterprise/Professional Edition
• Internet Information Server 5.0 (IIS)
• MS.Net Framework 3.5
• SQL Server 2005/2008 Enterprise Edition
Abstract of the Project:-
An efficient and distributed scheme for file mapping or file lookup is critical in decentralizing metadata management within a group of metadata servers, here the technique used called HIERARCHICAL BLOOM FILTER ARRAYS (HBA) to map filenames to the metadata servers holding their metadata. The Bloom filter arrays with different levels of accuracies are used on each metadata server.
The first one with low accuracy and used to capture the destination metadata server information of frequently accessed files. The other array is used to maintain the destination metadata information of all files. Simulation results show our HBA design to be highly effective and efficient in improving the performance and scalability of file systems in clusters with 1,000 to 10,000 nodes (or superclusters) and with the amount of data in the petabyte scale or higher. HBA is reducing metadata operation by using the single metadata architecture instead of 16 metadata server.
Existing System:-
File mapping or file lookup is critical in decentralizing metadata management within a group of metadata servers. Following approaches are used in the Existing system.
Table-Based Mapping : It fails to balance the load.
Hashing-Based Mapping : It has slow directory operations, such as listing the
Directory contents And renaming directories .
Static Tree Partitioning : Cannot balance the load and has a medium lookup
Time.
Dynamic Tree Partitioning : Small memory overhead, incurs a large migration
overhead.
Proposed Systems:-
Here we are using the new approaches called HIERARCHICAL BLOOM FILTER ARRAYS (HBA), efficiently route metadata request within a group of metadata servers. There are two arrays used here. First array is used to reduce memory overhead, because it captures only the destination metadata server information of frequently accessed files to keep high management efficiency. And the second one is used to maintain the destination metadata information of all files. Both the arrays are mainly used for fast local lookup.
Environment:-
• Servers:
• Operating System Server: - Microsoft Windows XP/2000 or Higher
• Data Base Server: Microsoft SQL Server 2005/2008
• Clients: Microsoft Internet Explorer (Client Browser)
• Development Tools: Microsoft Visual Studio .Net 2008/2010
• Documentation Tools: MS Office 2007/2010
• Drawing Tools: IBM Rational Rose Enterprise, MS Office Visio 2007
• User Interface: ASP.NET With AJAX
• Code Behind: VC#.NET
HARDWARE REQUIREMENTS:-
• PIV 2.8 GHz Processor and Above
• RAM 1GB and Above
• HDD 40 GB Hard Disk Space and Above
SOFTWARE REQUIREMENTS:-
• WINDOWS OS (XP / 2000 / 2000 Server / 2003 Server)
• Visual Studio .Net 2008/2010 Enterprise/Professional Edition
• Internet Information Server 5.0 (IIS)
• MS.Net Framework 3.5
• SQL Server 2005/2008 Enterprise Edition