Titlebook: Searchable Storage in Cloud Computing; Yu Hua,Xue Liu Book 2019 Springer Nature Singapore Pte Ltd. 2019 Searchable storage.hashing computa

depreciate

Backgrounds of Searchable Storage,in providing an integrated structure for multiple queries on multi-dimensional data in a distributed environment. We propose a new data structure, called BR-tree (Bloom filter based R-tree), and implement such a prototype in the context of a distributed system. The node in a BR-tree, viewed as an ex

钝剑

APRON

The Component of Searchable Storage: Semantic-Aware Namespace,agement scheme is in desperate need to provide both the ease and efficiency of data access. In almost all today’s file systems, the namespace management is based on hierarchical directory trees. This tree-based namespace scheme is prone to severe performance bottlenecks and often fails to provide re

Arrhythmia

Semantic-Aware Metadata Organization for Exact-Matching Queries,onentially growing datasets and increasingly complex metadata queries in large-scale, Exabyte-level file systems with billions of files. This section proposes a novel decentralized semantic-aware metadata organization, called SmartStore, which exploits semantics of files’ metadata to judiciously agg

hemophilia

玷污

MERIT

Data Similarity-Aware Computation Infrastructure for the Cloud,e computation infrastructure requires efficient data placement and proper management for cached data. We propose an efficient and cost-effective multilevel caching scheme, called ., as computation infrastructure of the cloud. The idea behind . is to explore and exploit data similarity and support ef

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ations, open-source code sets and the basis of cloud computiThis book presents the state-of-the-art work in terms of searchable storage in cloud computing. It introduces and presents new schemes for exploring and exploiting the searchable storage via cost-efficient semantic hashing computation. Spec

miniature

Hashing Computation for Scalable Metadata,ed through extensive trace-driven simulations and a prototype implementation in Linux. Experimental results show that this scheme can significantly improve metadata management scalability and query efficiency in ultra large-scale storage systems (©{2011}IEEE. Reprinted, with permission, from Ref. [.].).