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Supporting Cluster-Based Network Services on Functionally Symmetric Software Architecture
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Source Conference on High Performance Networking and Computing archive
Proceedings of the 2004 ACM/IEEE conference on Supercomputing table of contents
Page: 9  
Year of Publication: 2004
ISBN:0-7695-2153-3
Authors
Kai Shen  University of Rochester
Lingkun Chu  Ask Jeeves Inc. and University of California at Santa Barbara
Tao Yang  Ask Jeeves Inc. and University of California at Santa Barbara
Sponsor
SIGARCH: ACM Special Interest Group on Computer Architecture
Publisher
IEEE Computer Society  Washington, DC, USA
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Downloads (6 Weeks): 6,   Downloads (12 Months): 24,   Citation Count: 0
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DOI Bookmark: 10.1109/SC.2004.55

ABSTRACT

Server and storage clustering has become a popular platform for hosting large-scale online services. Elements of the service clustering support are often constructed using centralized or hierarchical architectures, in order to meet performance and policy objectives desired by online applications. For instance, a central Executive node can be employed to make efficient resource management decisions based on a complete view of cluster-wide resource availability as well as request demands. Functionality symmetric software architecture can enhance the robustness of cluster-based network services due to its inherent absence of vulnerability points. However, such a design must satisfy performance requirements and policy objectives desired by online services. This paper argues for the improved robustness of functionally symmetric architectures and presents the designs of two specific clustering support elements: energy-conserving server consolidation and service availability management. Our emulation and experimentation on a 117-server cluster show that the proposed designs do not significantly compromise the system performance and policy objectives compared with the centralized approaches.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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Collaborative Colleagues:
Kai Shen: colleagues
Lingkun Chu: colleagues
Tao Yang: colleagues