@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 {62, title = {Model Discovery for Energy-Aware Computing Systems: An Experimental Evaluation}, booktitle = {1st Workshop on Energy Consumption and Reliability of Storage Systems (ERSS {\textquoteright}11)}, year = {2011}, month = {07/2011}, address = {Orlando, FL}, abstract = {
We present a model-discovery methodology for energy-aware computing systems that achieves high prediction accuracy. Model discovery, or system identification, is a critical first step in designing advanced controllers that can dynamically manage the energy-performance trade-off in an optimal manner. Our methodology favors Multiple-Inputs-Multiple-Outputs (MIMO) models over a collection of Single-Input-Single-Output (SISO) models, when the inputs and outputs of the system are coupled in a nontrivial way. In such cases, MIMO is generally more accurate than SISO over a wide range of inputs in predicting system behavior. Our experimental evaluation, carried out on a representative server workload, validates our approach. We obtained an average prediction accuracy of 77\% and 76\% for MIMO power and performance, respectively. We also show that MIMO models are consistently more accurate than SISO ones.
}, url = {http://www.fsl.cs.stonybrook.edu/docs/erss11model/erss11model.pdf}, author = {Zhichao Li and Radu Grosu and Koundinya Muppalla and Scott A. Smolka and Scott D. Stoller and Erez Zadok} } @proceedings {48, title = {To cloud or not to cloud?: musings on costs and viability}, year = {2011}, month = {01/2011}, publisher = {ACM}, edition = {Article No. 29 }, abstract = {

In this paper we aim to understand the types of applications for which cloud computing is economically tenable, i.e., for which the cost savings associated with cloud placement outweigh any associated deployment costs. We discover two scenarios. (i) In an "unified client" scenario, where the cloud-hosted applications are only accessed by a single cloud customer (or small set of associates), it is important to ensure that the cost savings (mainly computation-related) can offset the often significant client-cloud distance (network costs etc). Today, from a technological, cost-centric point of view, this includes only compute-intensive applications with at least 1000 CPU cycles per each 32 bits of client-cloud transferred data. Naturally a number of other considerations may make clouds attractive even for less compute intensive tasks (services, security, pay-as-you-go nature etc). (ii) In a "multi-client" setting on the other hand, when outsourced applications serve numerous different third parties, we show that clouds begin to act similarly in nature to content-distribution networks - their better network integration is simply too good to pass on, when compared to locally hosting the applications (and incurring associated network costs). Thus, in multi-client scenarios, today{\textquoteright}s compute, energy and general technology costs suggest that outsourcing to clouds is profitable for almost any application. Ultimately, we hope this work will constitute a first step in an objective evaluation of the technological side of costs of outsourcing and computing in general.

}, isbn = {978-1-4503-0976-9 }, doi = {10.1145/2038916.2038945 }, url = {http://dl.acm.org/citation.cfm?doid=2038916.2038945}, author = {Yao Chen and Radu Sion} } @mastersthesis {67, title = {Optimizing Energy and Performance for Server-Class File System Workloads}, volume = {Master of Science}, year = {2010}, month = {05/2010}, pages = {33}, school = {Stony Brook University}, type = {Master of Science Degree Thesis}, address = {Stony Brook, NY}, 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. Various factors like workloads, hardware configurations, and software configurations impact the performance and energy efficiency of the system. This thesis 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, on two different hardware configurations. The 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. In this thesis we show that a careful matching of expected workloads and hardware configuration to a single software configuration{\textemdash}the file system{\textemdash}can improve power-performance efficiency by a factor ranging from 1.05 to 9.4 times.

}, url = {http://www.fsl.cs.stonybrook.edu/docs/priya-thesis/priya_thesis.pdf}, author = {Priya Sehgal} } @article {58, title = {Optimizing Energy and Performance for Server-Class File System Workloads}, journal = {ACM Transactions on Storage (TOS {\textquoteright}10)}, volume = {6}, year = {2010}, month = {09/2010}, 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. Various factors like workloads, hardware configurations, and software configurations impact the performance and energy efficiency of the system. This article 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 fileserver, on two different hardware configurations. The 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. In this article we show that a careful matching of expected workloads and hardware configuration to a single software configuration{\textemdash}the file system{\textemdash}can improve power-performance efficiency by a factor ranging from 1.05 to 9.4 times.

}, url = {http://dl.acm.org/citation.cfm?id=1837918}, 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} } @book {54, title = {Verification of Security Policy Enforcement in Enterprise Systems}, series = {Emerging Challenges for Security, Privacy and Trust }, number = {297}, year = {2009}, pages = {202-213}, publisher = {Springer Berlin Heidelberg}, organization = {Springer Berlin Heidelberg}, edition = {2009}, abstract = {

Many security requirements for enterprise systems can be expressed in a natural way as high-level access control policies. A high-level policy may refer to abstract information resources, independent of where the information is stored; it controls both direct and indirect accesses to the information; it may refer to the context of a request, i.e., the request{\textquoteright}s path through the system; and its enforcement point and enforcement mechanism may be unspecified. Enforcement of a high-level policy may depend on the system architecture and the configurations of a variety of security mechanisms, such as firewalls, host login permissions, file permissions, DBMS access control, and application-specific security mechanisms. This paper presents a framework in which all of these can be conveniently and formally expressed, a method to verify that a high-level policy is enforced, and an algorithm to determine a trusted computing base for each resource.

}, isbn = {978-3-642-01243-3}, doi = {10.1007/978-3-642-01244-0_18}, url = {http://link.springer.com/chapter/10.1007\%2F978-3-642-01244-0_18}, author = {Puneet Gupta and Scott Stoller} } @conference {66, title = {GreenFS: Making Enterprise Computers Greener by Protecting Them Better}, booktitle = {3rd ACM SIGOPS/EuroSys European Conference on Computer Systems 2008 (EuroSys {\textquoteright}08)}, year = {2008}, month = {04/2008}, publisher = {ACM}, organization = {ACM}, address = {Glasgow, Scotland}, abstract = {

Hard disks contain data - frequently an irreplaceable asset of high monetary and non-monetary value. At the same time, hard disks are mechanical devices that consume power, are noisy, and fragile when their platters are rotating.

In this paper we demonstrate that hard disks cause different kinds of problems for different types of computer systems and demystify several common misconceptions. We show that solutions developed to date are incapable of solving the power consumption, noise, and data reliability problems without sacrificing hard disk life-time, data reliability, or user convenience.

We considered data reliability, recovery, performance, user convenience, and hard disk-caused problems together at the enterprise scale. We have designed GreenFS: a fan-out stackable file system that offers all-time all-data run-time data protection, improves performance under typical user workloads, and allows hard disks to be kept off most of the time. As a result, GreenFS improves enterprise data protection, minimizes disk drive-related power consumption and noise and increases the chances of disk drive survivability in case of unexpected external impacts.

}, isbn = {978-1-60558-013-5}, url = {http://www.fsl.cs.stonybrook.edu/docs/greenfs/greenfs-eurosys08.pdf}, author = {Nikolai Joukov and Josef Sipek} }