Resource Sharing for Multi-Tenant NoSQL Data Store in Cloud
Jiaan Zeng

TL;DR
This paper investigates resource sharing in multi-tenant cloud NoSQL data stores, proposing solutions to mitigate interference in local file systems and improve efficiency over parallel file systems, with experimental validation.
Contribution
It introduces workload-aware resource reservation and scheduling schemes for local file systems and a lightweight key-value store for shared parallel file systems, enhancing performance and resource management.
Findings
Proposed scheduling and reservation schemes prevent tenant interference.
New lightweight KVS outperforms Cassandra and Voldemort in various workloads.
Approaches adapt to dynamic workloads and improve efficiency in multi-tenant environments.
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…
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Taxonomy
TopicsCloud Computing and Resource Management · Distributed and Parallel Computing Systems · Advanced Data Storage Technologies
