Docker container scheduler for I/O intensive applications running on NVMe SSDs

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dc.contributor.author Bhimani, Janki
dc.contributor.author Yang, Zhengyu
dc.contributor.author Mi, Ningfang
dc.contributor.author Yang, Jingpei
dc.contributor.author Xu, Qiumin
dc.contributor.author Awasthi, Manu
dc.contributor.author Pandurangan, Rajinikanth
dc.contributor.author Balakrishnan, Vijay
dc.date.accessioned 2018-02-23T04:59:10Z
dc.date.available 2018-02-23T04:59:10Z
dc.date.issued 2018-02
dc.identifier.citation Bhimani, Janki; Yang, Zhengyu; Mi, Ningfang; Yang, Jingpei; Xu, Qiumin; Awasthi, Manu; Pandurangan, Rajinikanth and Balakrishnan, Vijay, “Docker container scheduler for I/O intensive applications running on NVMe SSDs”, IEEE Transactions on Multi-Scale Computing Systems, DOI: 10.1109/TMSCS.2018.2801281, Feb. 2018. en_US
dc.identifier.issn 2332-7766
dc.identifier.uri https://repository.iitgn.ac.in/handle/123456789/3473
dc.identifier.uri http://dx.doi.org/10.1109/TMSCS.2018.2801281
dc.description.abstract By using fast back-end storage, performance benefits of a lightweight container platform can be leveraged with quick I/O response. Nevertheless, the performance of simultaneously executing multiple instances of same or different applications may vary significantly with the number of containers. The performance may also vary with the nature of applications because different applications can exhibit different nature on SSDs in terms of I/O types (read/write), I/O access pattern (random/sequential), I/O size, etc. Therefore, this paper aims to investigate and analyze the performance characterization of both homogeneous and heterogeneous mixtures of I/O intensive containerized applications, operating with high performance NVMe SSDs and derive novel design guidelines for achieving an optimal and fair operation of the both homogeneous and heterogeneous mixtures. By leveraging these design guidelines, we further develop a new docker controller for scheduling workload containers of different types of applications. Our controller decides the optimal batches of simultaneously operating containers in order to minimize total execution time and maximize resource utilization. Meanwhile, our controller also strives to balance the throughput among all simultaneously running applications. We develop this new docker controller by solving an optimization problem using five different optimization solvers. We conduct our experiments in a platform of multiple docker containers operating on an array of three enterprise NVMe drives. We further evaluate our controller using different applications of diverse I/O behaviors and compare it with simultaneous operation of containers without the controller. Our evaluation results show that our new docker workload controller helps speed-up the overall execution of multiple applications on SSDs. en_US
dc.description.statementofresponsibility Janki Bhimani,Zhengyu Yang,Ningfang Mi,Jingpei Yang,Jingpei Yang,Manu Awasthi, Rajinikanth Pandurangan,Vijay Balakrishnan
dc.language.iso en en_US
dc.publisher IEEE xplore digital library en_US
dc.subject Containers en_US
dc.subject Resource management en_US
dc.subject Databases en_US
dc.subject Nonvolatile memory en_US
dc.subject Virtual machining en_US
dc.subject Interference en_US
dc.subject Design methodology en_US
dc.title Docker container scheduler for I/O intensive applications running on NVMe SSDs en_US
dc.type Article en_US
dc.relation.journal IEEE Transactions on Multi-Scale Computing Systems


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