@conference {60, title = {The Economics of Long-Term Digital Storage}, booktitle = {The Memory of the World in the Digital Age: Digitization and Preservation}, year = {2012}, month = {09/2012}, publisher = {United Nations Educational, Scientific and Cultural Organization (UNESCO)}, organization = {United Nations Educational, Scientific and Cultural Organization (UNESCO)}, address = {Vancouver, Canada}, abstract = {

Paper as the medium for the world{\textquoteright}s memory has one great advantage; it survives benign neglect well. Bits, on the other hand, need continual care, and thus a con- tinual flow of money. A Blue Ribbon panel described economic sustainability as the major issue facing long- term digital preservation. This is despite Kryder{\textquoteright}s Law, the 30-year history of the cost of digital storage media dropping exponentially. If economics are the major con- cern even when Kryder{\textquoteright}s Law holds, what will happen if it slows or stops? We present evidence that it will, and some simulations of the impact on digital preservation costs.

}, url = {http://www.fsl.cs.stonybrook.edu/docs/unesco12/UNESCO2012-storage-econ.pdf}, author = {David S. H. Rosenthal and Daniel C. Rosenthal and Ethan L. Miller and Ian F. Adams and Mark W. Storer and Erez Zadok} } @conference {63, title = {On the Energy Consumption and Performance of Systems Software}, booktitle = {4th Israeli Experimental Systems Conference (ACM SYSTOR {\textquoteright}11)}, year = {2011}, month = {06/2011}, address = {Haifa, Israel}, abstract = {

Models of energy consumption and performance are necessary to understand and identify system behavior, prior to designing advanced controls that can balance out performance and energy use. This paper considers the energy consumption and performance of servers running a relatively simple file-compression workload. We found that standard techniques for system identification do not produce acceptable models of energy consumption and performance, due to the intricate interplay between the discrete nature of software and the continuous nature of energy and performance. This motivated us to perform a detailed empirical study of the energy consumption and performance of this system with varying compression algorithms and compression levels, file types, persistent storage media, CPU DVFS levels, and disk I/O schedulers. Our results identify and illustrate factors that complicate the system{\textquoteright}s energy consumption and performance, including nonlinearity, instability, and multi-dimensionality. Our results provide a basis for future work on modeling energy consumption and performance to support principled design of controllable energy-aware systems.

}, url = {http://www.fsl.cs.stonybrook.edu/docs/erss11model/erss11model.pdf}, author = {Zhichao L and Radu Grosu and Priya Sehgal and Scott A. Smolka and Scott D. Stoller and Erez Zadok} } @conference {64, title = {Evaluating Performance and Energy in File System Server Workloads}, booktitle = {USENIX Conference on File and Storage Technologies (FAST {\textquoteright}10)}, year = {2011}, month = {07/2011}, address = {Orlando, FL}, abstract = {

Recently, power has emerged as a critical factor in designing components of storage systems, especially for power-hungry data centers. While there is some research into power-aware storage stack components, there are no systematic studies evaluating each component{\textquoteright}s impact separately. This paper evaluates the file system{\textquoteright}s impact on energy consumption and performance. We studied several popular Linux file systems, with various mount and format options, using the FileBench workload generator to emulate four server workloads: Web, database, mail, and file server. In case of a server node consisting of a single disk, CPU power generally exceeds diskpower consumption. However, file system design, implementation, and available features have a significant effect on CPU/disk utilization, and hence on performance and power. We discovered that default file system options are often suboptimal, and even poor. We show that a careful matching of expected workloads to file system types and options can improve power-performance efficiency by a factor ranging from 1.05 to 9.4 times.

}, url = {http://www.fsl.cs.stonybrook.edu/docs/fsgreen-bench/fs-green-comparison.pdf}, author = {Priya Sehgal and Vasily Tarasov and Erez Zadok} } @conference {65, title = {Energy and Performance Evaluation of Lossless File Data Compression on Server Systems}, booktitle = {The Israeli Experimental Systems Conference (SYSTOR {\textquoteright}09)}, year = {2009}, month = {05/2009}, publisher = {ACM}, organization = {ACM}, address = {Haifa, Israel}, abstract = {

Data compression has been claimed to be an attractive solution to save energy consumption in high-end servers and data centers. However, there has not been a study to explore this. In this paper, we present a comprehensive evaluation of energy consumption for various file compression techniques implemented in software. We apply various compression tools available on Linux to a variety of data files, and we try them on server class and workstation class systems. We compare their energy and performance results against raw reads and writes. Our results reveal that software based data compression cannot be considered as a universal solution to reduce energy consumption. Various factors like the type of the data file, the compression tool being used, the read-to-write ratio of the workload, and the hardware configuration of the system impact the efficacy of this technique. In some cases, however, we found compression to save substantial energy and improve performance.

}, url = {http://www.fsl.cs.stonybrook.edu/docs/greencomp/green-compress.pdf}, author = {Rachita Kothiyal and Vasily Tarasov and Priya Sehgal and Erez Zadok} }