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dc.contributor.advisor Plale, Beth en
dc.contributor.author Zeng, Jiaan en
dc.date.accessioned 2016-01-05T02:28:25Z en
dc.date.available 2016-01-05T02:28:25Z en
dc.date.issued 2015-12 en
dc.identifier.uri http://hdl.handle.net/2022/20579 en
dc.description Thesis (Ph.D.) - Indiana University, Informatics and Computing, 2015 en
dc.description.abstract Multi-tenancy hosting of users in cloud NoSQL data stores is favored by cloud providers because it enables resource sharing at low operating cost. Multi-tenancy takes several forms depending on whether the back-end file system is a local file system (LFS) or a parallel file system (PFS), and on whether tenants are independent or share data across tenants In this thesis I focus on and propose solutions to two cases: independent data-local file system, and shared data-parallel file system. In the independent data-local file system case, resource contention occurs under certain conditions in Cassandra and HBase, two state-of-the-art NoSQL stores, causing performance degradation for one tenant by another. We investigate the interference and propose two approaches. The first provides a scheduling scheme that can approximate resource consumption, adapt to workload dynamics and work in a distributed fashion. The second introduces a workload-aware resource reservation approach to prevent interference. The approach relies on a performance model obtained offline and plans the reservation according to different workload resource demands. Results show the approaches together can prevent interference and adapt to dynamic workloads under multi-tenancy. In the shared data-parallel file system case, it has been shown that running a distributed NoSQL store over PFS for shared data across tenants is not cost effective. Overheads are introduced due to the unawareness of the NoSQL store of PFS. This dissertation targets the key-value store (KVS), a specific form of NoSQL stores, and proposes a lightweight KVS over a parallel file system to improve efficiency. The solution is built on an embedded KVS for high performance but uses novel data structures to support concurrent writes, giving capability that embedded KVSs are not designed for. Results show the proposed system outperforms Cassandra and Voldemort in several different workloads. en
dc.language.iso en_US en
dc.publisher [Bloomington, Ind.] : Indiana University en
dc.rights Attribution 4.0 International (CC BY 4.0) en
dc.rights.uri https://creativecommons.org/licenses/by/4.0/ en
dc.subject NoSQL en
dc.subject database management en
dc.subject cloud computing en
dc.subject multi-tenancy en
dc.subject resource scheduling en
dc.title Resource Sharing for Multi-Tenant Nosql Data Store in Cloud en
dc.type Doctoral Dissertation en
dc.altmetrics.display false en


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