Lerna: an active storage framework for flexible data access and management

In the present paper, we examine the problem of supporting application-specific computation within a network file server. Our objectives are (i) to introduce an easy to use yet powerful architecture for executing both custom-developed and legacy applications close to the stored data, (ii) to investigate the performance improvement that we get from data proximity in I/O-intensive processing, and (in) to exploit the I/O-traffic information available within the file server for more effective resource management. One main difference from previous active storage research is our emphasis on the expressive power and usability of the network server interface. We describe an extensible active storage framework that we built in order to demonstrate the feasibility of the proposed system design. We show that accessing large datasets over a wide-area network through a regular file system can penalize the system performance, unless application computation is moved close to the stored data. Our conclusions are substantiated through experimentation with a popular multilayer map warehouse application.