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Adjusting OS Scheduler Parameters to Improve Server Application Performance
Taehyun Han, Hyeonmyeong Lee, Heeseung Jo
http://doi.org/10.5626/JOK.2020.47.7.643
Modern Linux servers are used in a variety of ways, from large servers to small IOTs, and most machines run their services through the default scheduler provided by Linux. Although it is possible to optimize for a specific purpose, there is a problem in which the average user cannot optimize all modern Linux applications. In this paper, we propose SCHEDTUNE to automatically optimize the scheduler configuration to maximize Linux server performance. SCHEDTUNE allows users to improve performance without modification to the application or basic kernel source running on the server. This makes it easy for administrators to configure schedulers that operate specifically for their servers. Experimental results showed that when SCHEDTUNE is applied, the maximum performance is achieved up to 19 %, and in most cases performance improvement is achieved as well.
Boosting the Forwarding Performance of Virtual Switches through Kernel-level Memory Optimization
Heungsik Choi, Kyoungwoon Lee, Chuck Yoo
http://doi.org/10.5626/JOK.2018.45.6.511
A virtual switch enables network resources to be utilized by a wide range of virtual machines or containers. Many types of virtual switches have been developed to offer a variety of functions. However, due to the inefficient processing of existing virtual switches and the Linux networking stack, current high bandwidth requirements cannot be met. To solve this problem, various studies have been carried out to propose a method using a unique networking stack in a user-level rather than an existing kernel. However, various problems still exist such as reimplementation overhead, relatively low security, excessive memory usage, etc. This paper proposes kernel-level optimization techniques to improve network processing of the kernel networking stack as well as to overcome the limitations of existing techniques.
AIOPro: A Fully-Integrated Storage I/O Profiler for Android Smartphones
Sangwook Shane Hahn, Inhyuk Yee, Donguk Ryu, Jihong Kim
Application response time is critical to end-user response time in Android smartphones. Due to the plentiful resources of recent smartphones, storage I/O response time becomes a major key factor in application response time. However, existing storage I/O trace tools for Android and Linux give limited information only for a specific I/O layer which makes it difficult to combine I/O information from different I/O layers, because not helpful for application developer and researchers. In this paper, we propose a novel storage I/O trace tool for Android, called AIOPro (Android I/O profiler). It traces storage I/O from application - Android platform - system call - virtual file system - native file system - page cache - block layer - SCSI layer and device driver. It then combines the storage I/O information from I/O layers by linking them with file information and physical address. Our evaluations of real smartphone usage scenarios and benchmarks show that AIOPro can track storage I/O information from all I/O layers without any data loss under 0.1% system overheads.
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