@article{
 title = {Argus: A Multi-tenancy NoSQL store with workload-aware resource reservation},
 type = {article},
 year = {2016},
 volume = {58},
 id = {e81d3f9a-ce87-324a-bb1d-6e6062c7fed0},
 created = {2019-10-01T17:20:45.192Z},
 file_attached = {false},
 profile_id = {42d295c0-0737-38d6-8b43-508cab6ea85d},
 last_modified = {2019-10-01T17:23:16.539Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Zeng2016a},
 folder_uuids = {73f994b4-a3be-4035-a6dd-3802077ce863},
 private_publication = {false},
 abstract = {© 2016 Elsevier B.V. Multi-tenancy in cloud hosted NoSQL data stores is favored by cloud providers as it allows more effective resource sharing amongst different tenants thus lowering operating costs. A NoSQL provider will often present to each tenant a dedicated view of the store but then behind the scenes consolidate tenant access into a shared instance. This multi-tenancy approach with tenant data and workloads coexisting in the same infrastructure, under certain conditions can lead to performance degradation of one tenant caused by another as we show experimentally. This paper introduces Argus, a NoSQL store equipped with resource reservation to prevent performance interference across tenants in a multi-tenancy environment. Cache reservation is enforced through partitioning the cache space and disk reservation enforced through scheduling requests to a Distributed File System (DFS). We model the reservation on various workloads as a constrained optimization problem and use the stochastic hill climbing algorithm to find a near-optimum plan for different resource reservations. Empirical results show that Argus is able to prevent interference, adapt to dynamic workloads, and outperform A-Cache, another interference preventing NoSQL solution.},
 bibtype = {article},
 author = {Zeng, J. and Plale, B.},
 doi = {10.1016/j.parco.2016.06.003},
 journal = {Parallel Computing}
}

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