PASSI: A Parallel, Reliable and Scalable Storage Software Infrastructure for active storage system and I/O environments

Author(s):  
Hsing-bung Chen ◽  
Song Fu
Author(s):  
Ahmet Artu Yıldırım ◽  
Dan Watson

Major Internet services are required to process a tremendous amount of data at real time. As we put these services under the magnifying glass, It's seen that distributed object storage systems play an important role at back-end in achieving this success. In this chapter, overall information of the current state-of –the-art storage systems are given which are used for reliable, high performance and scalable storage needs in data centers and cloud. Then, an experimental distributed object storage system (CADOS) is introduced for retrieving large data, such as hundreds of megabytes, efficiently through HTML5-enabled web browsers over big data – terabytes of data – in cloud infrastructure. The objective of the system is to minimize latency and propose a scalable storage system on the cloud using a thin RESTful web service and modern HTML5 capabilities.


10.12737/2420 ◽  
2013 ◽  
Vol 4 (4) ◽  
pp. 127-142
Author(s):  
Екатерина Тютляева ◽  
Ekaterina Tyutlyaeva

This paper describes a modified parallel Batcher sort algorithm for big data processing. The main novelty of implemented sort algorithm is to integrate effective parallel batcher sort and Active Storage concept. We use Active Storage based on Lustre File System and TSim C++ template library for parallelization. This paper presents experimental testing results for scientific processing real seismic data. Presented results indicate that described algorithm can reach linear acceleration on sorting big data sets (More then 100 Gb).


2015 ◽  
Vol 49 ◽  
pp. 133-141 ◽  
Author(s):  
Hai Jiang ◽  
Feng Shen ◽  
Su Chen ◽  
Kuan-Ching Li ◽  
Young-Sik Jeong

Big Data ◽  
2016 ◽  
pp. 828-847
Author(s):  
Ahmet Artu Yıldırım ◽  
Dan Watson

Major Internet services are required to process a tremendous amount of data at real time. As we put these services under the magnifying glass, it's seen that distributed object storage systems play an important role at back-end in achieving this success. In this chapter, overall information of the current state-of –the-art storage systems are given which are used for reliable, high performance and scalable storage needs in data centers and cloud. Then, an experimental distributed object storage system (CADOS) is introduced for retrieving large data, such as hundreds of megabytes, efficiently through HTML5-enabled web browsers over big data – terabytes of data – in cloud infrastructure. The objective of the system is to minimize latency and propose a scalable storage system on the cloud using a thin RESTful web service and modern HTML5 capabilities.


Sign in / Sign up

Export Citation Format

Share Document