Shared-Disk File System

Keyword(s):  
2018 ◽  
Vol 2018 ◽  
pp. 1-11 ◽  
Author(s):  
Guangsheng Chen ◽  
Pei Nie ◽  
Weipeng Jing

With the development of network communication, a 1000-fold increase in traffic demand from 4G to 5G, it is critical to provide efficient and fast spatial data access interface for applications in mobile environment. In view of the low I/O efficiency and high latency of existing methods, this paper presents a memory-based spatial data query method that uses the distributed memory file system Alluxio to store data and build a two-level index based on the Alluxio key-value structure; moreover, it aims to solve the problem of low efficiency of traditional method; according to the characteristics of Spark computing framework, a data input format for spatial data query is proposed, which can selectively read the file data and reduce the data I/O. The comparative experiments show that the memory-based file system Alluxio has better I/O performance than the disk file system; compared with the traditional distributed query method, the method we proposed reduces the retrieval time greatly.


1985 ◽  
Author(s):  
Masatsugu Tanji ◽  
Ryoichi Imanaka ◽  
Yoshihiro Okino ◽  
Seizo Tsuji ◽  
Wataru Masuda

2019 ◽  
Vol 78 (11) ◽  
pp. 973-985 ◽  
Author(s):  
K.Yu. Shekhanin ◽  
A.O. Kolhatin ◽  
E.E. Demenko ◽  
A. A. Kuznetsov
Keyword(s):  

Author(s):  
Mustapha Mohammed Baua'a

The I\O file system Read\Write operations are considered the most significant characteristics. Where, many researchers focus on their works on how to decrease the response time of I\O file system read\write operations. However, most articles concentrate on how to read\write content of the file in parallelism manner. Here in this paper, the author considers the parallelizing Read\Write whole file bytes not only its contents. A case study has been applied in order to make the idea more clear. It talks about two techniques of uploading\downloading files via Web Service. The first one is a traditional way where the files uploaded and downloaded serially. While the second one is uploaded\ downloaded files using Java thread in order to simulate parallelism technique. Java Netbeans 8.0.2 have been used as a programming environment to implement the Download\Upload files through Web Services. Validation results are also presented via using Mat-lab platform as benchmarks. The visualized figures of validation results are clearly clarifying that the second technique shows better response time in comparison to the traditional way.


Author(s):  
Linda Apriliana ◽  
Ucuk Darusala Darusalam ◽  
Novi Dian Nathasia

Layanan dan data teknologi Cloud Computing tersimpan pada server, hal ini menjadikan faktor pentingnya server sebagai pendukung ketersediaan layanan. Semakin banyak pengguna yang mengakses layanan tersebut akan mengakibatkan beban kinerja mesin server menjadi lebih berat dan kurang optimal, karena layanan harus bekerja menyediakan data terus-menerus yang dapat diakses kapanpun oleh penggunanya melalui jaringan terkoneksi. Perangkat keras server memiliki masa performa kinerja. Hal serupa dengan perangkat lunak yang dapat mengalami crash. Dengan fungsi server yang memberikan layanan kepada client, server dituntut untuk memiliki tingkat availability yang tinggi. Hal tersebut memungkinkan mesin server mengalami down. Server juga harus dimatikan untuk keperluan pemeliharaan. Penelitian bertujuan ini membangun Clustering Server yang dapat bekerja bersama yang seolah merupakan sistem tunggal diatas lingkungan virtual. Hal ini merupakan solusi untuk mengatasi permasalahan tersebut. Pada penelitian ini penulis menggunakan server virtualisasi proxmox, FreeNAS sebagai server NAS dan DRBD untuk pendukung ketersediaan layanan tinggi dalam lingkup HA, sinkronisasi data dalam High Availability (HA) yang dapat melakukan mirroring sistem kemesin lain. Dengan diterapkannya metode HA dan sinkronasi DRBD serta penggunaan NFS (Network File System) pada sistem cluster didapatkan hasil rata-rata waktu migrasi sebesar 9.7(s) pada node1 menuju node2, 3.7(s) node2 menuju node3, dan 3(s) pada node3 menuju node1. Didaptkan juga waktu downtime yang lebih sedikit yaitu sebesar 0.58 ms pada node1, 0.02 ms pada node2, dan 0.02 ms pada node3.


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