Energy Efficient Storage Management Cooperated with Large Data Intensive Applications

Power, especially that consumed for storing data, and cooling costs for data centers have increased rapidly. The main applications running at data centers are data intensive applications such as large file servers or database systems. Recently, power management of the data intensive applications has been emphasized in the literature. Such reports discuss the importance of power savings. However, these reports lack research on power management models for the efficient use of data intensive applications' I/O behaviors. This paper proposes a novel energy efficient storage management system that monitors both application- and device-level I/O patterns at run time, and uses not only the device-level I/O pattern but also application level patterns. First, the design of the proposed model combined with such large data intensive applications will be shown. The key features of the model are i) classifying application-level I/O into four patterns using run-time access behaviors such as the length of idle time and read/write frequency, and ii) adopting an appropriate power-saving method-based on these application level I/O patterns. Next, the proposed method is quantitatively evaluated with typical data intensive applications such as file servers, OLTP, and DSS. It is shown that energy efficient storage management is effective in achieving large power savings compared with traditional approaches while an application is running.

I. Introduction

The amount of digital data produced by humans is increasing every day. Based on the IDC report [1], the amount of information and content created and stored digitally will grow to over 7 zettabytes by 2015. This explosion of digital data must be managed and used with data intensive applications such as sensor data archives, search engines, and customer management systems (OLTP). As well, the increased data must be stored somewhere, which implies that storage capacity must also increase. The report [2] says that the storage capacity shipment in 2014 will be 7 times as large as that in 2009.