Direction-aware resource discovery in large-scale distributed computing environments

被引:9
作者
Chung, Wu-Chun [1 ]
Hsu, Chin-Jung [1 ]
Lai, Kuan-Chou [2 ]
Li, Kuan-Ching [3 ]
Chung, Yeh-Ching [1 ]
机构
[1] Natl Tsing Hua Univ, Dept Comp Sci, Hsinchu 300, Taiwan
[2] Natl Taichung Univ, Dept Comp Sci, Taichung 403, Taiwan
[3] Providence Univ, Dept Comp Sci & Informat Engn, Taichung 433, Taiwan
关键词
Resource discovery; Grid computing; Cloud computing; Unstructured overlay; PEER-TO-PEER; GRIDS; CONVERGENCE; SEARCH; SYSTEM; P2P;
D O I
10.1007/s11227-013-0899-6
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
As a system scales up, the peer-to-peer (P2P) approach is attractive to distributed computing environments, such as Grids and Clouds, due to the amount of resources increased. The major issue in large-scale distributed systems is to prevent the phenomenon of a communication bottleneck or a single point of failure. Conventional approaches may not be able to apply directly to such environments due to restricted queries and varied resource characteristics. Alternatively, a fully decentralized resource discovery service based on an unstructured overlay, which relies only on the information of resource attributes and characteristics, may be a feasible solution. One major challenge of such service is to locate desired and suitable resources without the global knowledge of distributed sharing resources. As a consequence, the more nodes the resource discovery service involves, the higher the network overhead incurs. In this paper, we proposed a direction-aware strategy which can alleviate the network traffic among unstructured information systems for distributed resource discovery service. Experimental results have demonstrated that the proposed approach achieves higher success rate at low cost and higher scalability.
引用
收藏
页码:229 / 248
页数:20
相关论文
共 27 条
[1]   Mercury: Supporting scalable multi-attribute range queries [J].
Bharambe, AR ;
Agrawal, M ;
Seshan, S .
ACM SIGCOMM COMPUTER COMMUNICATION REVIEW, 2004, 34 (04) :353-366
[2]  
Cai M., 2004, J GRID COMPUT, V2, P3, DOI DOI 10.1007/S10723-004-1184-Y
[3]   The data grid: Towards an architecture for the distributed management and analysis of large scientific datasets [J].
Chervenak, A ;
Foster, I ;
Kesselman, C ;
Salisbury, C ;
Tuecke, S .
JOURNAL OF NETWORK AND COMPUTER APPLICATIONS, 2000, 23 (03) :187-200
[4]   A new mechanism for resource monitoring in Grid computing [J].
Chung, Wu-Chun ;
Chang, Ruay-Shiung .
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE, 2009, 25 (01) :1-7
[5]   G2G: A Meta-Grid Framework for the convergence of P2P and Grids [J].
Chung, Wu-Chun ;
Hsu, Chin-Jung ;
Lin, Yi-Hsiang ;
Lai, Kuan-Chou ;
Chung, Yeh-Ching .
INTERNATIONAL JOURNAL OF GRID AND HIGH PERFORMANCE COMPUTING, 2010, 2 (03) :1-16
[6]  
Czajkowski K, 2001, 10TH IEEE INTERNATIONAL SYMPOSIUM ON HIGH PERFORMANCE DISTRIBUTED COMPUTING, PROCEEDINGS, P181, DOI 10.1109/HPDC.2001.945188
[7]   Cloud Computing Distributed Internet Computing for IT and Scientific Research [J].
Dikaiakos, Marios D. ;
Pallis, George ;
Katsaros, Dimitrios ;
Mehra, Pankaj ;
Vakali, Athena .
IEEE INTERNET COMPUTING, 2009, 13 (05) :10-13
[8]  
Filali Imen, 2010, Proceedings 2010 10th IEEE/ACM International Conference on Cluster, Cloud and Grid Computing (CCGrid), P438, DOI 10.1109/CCGRID.2010.66
[9]   A directory service for configuring high-performance distributed computations [J].
Fitzgerald, S ;
Foster, I ;
Kesselman, C ;
vonLaszewski, G ;
Smith, W ;
Tuecke, S .
SIXTH IEEE INTERNATIONAL SYMPOSIUM ON HIGH PERFORMANCE DISTRIBUTED COMPUTING, PROCEEDINGS, 1997, :365-375
[10]  
Foster I, 2003, LECT NOTES COMPUT SC, V2735, P118