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Articles by Peng Yuxing
Total Records ( 2 ) for Peng Yuxing
  Huang Bin and Peng Yuxing
  For its perception of unlimited resources and infinite scalability, Cloud Computing has emerged as a pervasive paradigm for hosting? data-centric applications in large computing infrastructures. The data produced by these applications are essentially sparse and wide and may change schema frequently, traditional relational data model is inappropriate for their data management. A new data model, called Sparse Wide Table, was introduced for this task. Unfortunately, we have to face many challenges in building the secondary index for Sparse Wide Table in cloud, as the distributed and column-oriented storage which eliminates a number of NULLs. In this study, we present a three-level index scheme for efficient data processing in the Cloud. Our approach can be summarized as follows. First, we build an index for each column by which the records can be rebuilt easily. Second, we build a bitmap index for each storage node which only indexes the data residing on the node. Third, we organize the storage nodes as a structured overlay and each node maintains a portion of the global index for the all different data. The global index is a bitmap index to indicate the node each data resides in. Finally, based on the three-level index scheme, some query algorithms are implemented. We conduct extensive experiments on a LAN and the results demonstrate that our indexing scheme is dynamic, efficient and scalable.
  Huang Bin , Peng Yuxing and Peng Xiaoning
  There are well known anomalies permitted by snapshot isolation that can lead to violations of data consistency by interleaving transactions that individually maintain consistency. Until now, there are some ways to prevent these anomalies only in single computer and there are not the corresponding solving methods in cloud computing. This paper describes our PDCC algorithm to detect cycles in a snapshot isolation dependency graph and abort transactions to break the cycle in cloud computing. The algorithm ensures serializable executions for SI transactions in cloud computing. Based on the transaction concurrency control of Percolator, we have implemented our algorithm in an open source cloud database system (HBase) and our performance study shows that PDCC throughput and scalability are good.
 
 
 
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