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Virtual Machine (VM) live storage migration is widely performed in the current cloud data centers, for the purposes of load balance, hardware maintenance and system upgrade. Nevertheless, conventional migration approaches, such as Dirty Block Tracking (DBT), do not address the problem of IO interference between VM IO requests and Migration IO requests during the migration period, which degrades both...
In this paper, we propose a Versatile Searchable File System, VSFS, which builds POSIX-compatible namespace using a novel Namespace-based File Query Language (NFQL). This enables analytics applications to utilize VSFS high-performance file-search service without changing their data model. VSFS versatile file-indexing mechanism is designed to offer great flexibility for applications to control indices...
Due to the relatively low bandwidth of WAN (Wide Area Network) that supports cloud backup services, both the backup time and restore time in the cloud backup environment are in desperate need for reduction to make cloud backup a practical and affordable service for small businesses and telecommuters alike. Existing solutions that employ the deduplication technology for cloud backup services only focus...
Existing de-duplication solutions in cloud backup environment either obtain high compression ratios at the cost of heavy de-duplication overheads in terms of increased latency and reduced throughput, or maintain small de-duplication overheads at the cost of low compression ratios causing high data transmission costs, which results in a large backup window. In this paper, we present SAM, a Semantic-Aware...
Flash memory SSDs pose a well-known challenge, that is, the erase-before-write problem. Researchers try to solve this inherent problem from two different angles by either designing sophisticated Flash Translation Layer (FTL) schemes to postpone and minimize erasures or designing flash-aware buffer management algorithms to absorb unnecessary erasures. Our experimental results show that buffer management...
This paper presents a scalable and adaptive decentralized metadata lookup scheme for ultra large-scale file systems (ges Petabytes or even Exabytes). Our scheme logically organizes metadata servers (MDS) into a multi-layered query hierarchy and exploits grouped bloom filters to efficiently route metadata requests to desired MDS through the hierarchy. This metadata lookup scheme can be executed at...
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