Abstract
To support online index and range queries, the Distributed B-tree is adopted to index the mass and rapidly in- creasing data in cloud computing. But current Distributed B-tree has three defects: low degree of concurrency, frequent node splitting and high cost of updates in clients. For above mentioned defects, this paper presents efficient distribute B- tree index in cloud computing environment, which effectively enhances the performance of the distributed B-tree index. First, it improves concurrent access by the distributed B-tree high concurrency access method based on node split history. Second, it reduces the splitting frequency by the method of dynamic changing node size. Finally, it reduces node update cost in all client buffers by the regional delayed update method. Experimental results show that, this method has high per- formance in cloud computing environments.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
