ANTELOPE: a semantic-aware data cube scheme for cloud data center networks. Today’s cloud data centers contain more than millions of servers and offer high bandwidth. A fundamental problem is how to significantly improve the large-scale system’s scalability to interconnect a large number of servers and meanwhile support various online services in cloud computing. One way is to deal with the challenge of potential mismatching between the network architecture and the data placement. To address this challenge, we present ANTELOPE, a scalable distributed data-centric scheme in cloud data centers, in which we systematically take into account both the property of network architecture and the optimization of data placement. The basic idea behind ANTELOPE is to leverage precomputation based data cube to support online cloud services. Since the construction of data cube suffers from the high costs of full materialization, we use a semantic-aware partial materialization solution to significantly reduce the operation and space overheads. Extensive experiments on real system implementations demonstrate the efficacy and efficiency of our proposed scheme.
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References in zbMATH (referenced in 3 articles , 1 standard article )
Showing results 1 to 3 of 3.
- Wu, Sheng-Jhih; Chu, Moody T.: Markov chains with memory, tensor formulation, and the dynamics of power iteration (2017)
- Cheng, Dongqin; Hao, Rong-Xia: Fault-tolerant cycles embedding in hypercubes with faulty edges (2014)
- Hua, Yu; Liu, Xue; Jiang, Hong: ANTELOPE: a semantic-aware data cube scheme for cloud data center networks (2014)