PERSPECTIVE: A Home Storage Solution
The home provides a new and challenging environment for data management, with both the number of storage-enhanced devices and the amount/variety of content growing rapidly. Moreover, devices in the home are extremely heterogeneous in computational power, storage capacity, and usage model. We need much simpler and more automated data management approaches to allow users to manage data in this new environment, sharing information across devices, finding information when needed, handling reliability issues, and so on. Perspective is a distributed data management system for home/consumer storage architected around the concept of a view. A view is a description of data about which a device is interested, published to other Perspective devices. Views provide a solid building block for efficient consistency management, inter-device search, device departure and arrival handling, and data protection. Within Perspective, we are also exploring automated data distribution approaches, effective search mechanisms, and security management for home/consumer storage.
This diagram shows how views facilitate object update or addition. In this case, Steve’s laptop has received a new movie (perhaps from the Internet). Because it holds all the views in the system, it knows that both the desktop and DVR need to see update messages for this new object. Note that the cell phone’s view does not include the object and, therefore, does not need to see the update.
Lily Mummert (Intel)
- Toward Strong, Usable Access Control for Shared Distributed Data. Michelle L. Mazurek, Yuan Liang, William Melicher, Manya Sleeper, Lujo Bauer, Gregory R. Ganger, Nitin Gupta, and Michael K. Reiter. In FAST
2014: USENIX Conference on File and Storage Technologies, February 2014.
Abstract / PDF [395K]
- Exploring Reactive Access Control.
Michelle L. Mazurek, Peter F. Klemperer, Richard Shay, Hassan Takabi, Lujo Bauer, Lorrie Faith Cranor. CHI 2011, May 7–12, 2011, Vancouver, BC, Canada.
Abstract / PDF [293k]
- Of Passwords and People: Measuring the Effect of Password-Composition Policies. Saranga Komanduri, Richard Shay, Patrick Gage Kelley, Michelle L. Mazurek, Lujo Bauer, Nicolas Christin, Lorrie Faith Cranor, Serge Egelman. CHI 2011, May 7–12, 2011, Vancouver, BC, Canada.
Abstract / PDF [405K]
- Access Control for Home Data Sharing: Attitudes, Needs and Practices. Michelle L. Mazurek, J.P. Arsenault, Joanna Bresee, Nitin Gupta, Iulia Ion, Christina Johns, Daniel Lee, Yuan Liang, Jenny Olsen, Brandon Salmon, Richard Shay, Kami Vaniea, Lujo Bauer, Lorrie Faith Cranor, Gregory R. Ganger, Michael K. Reiter. CHI 2010, April 10 – 15, 2010, Atlanta, Georgia. Supersedes Carnegie Mellon University Parallel Data Lab Technical Report CMU-PDL-09-110, October 2009.
Abstract / PDF [250K]
- Perspective: Semantic Data Management for the Home. Brandon Salmon, Steven W. Schlosser, Lorrie Faith Cranor, Gregory R. Ganger. ;LOGIN Vol. 34, No. 5
Abstract / PDF [403K]
- Putting Home Data Management
into Perspective. Brandon Watts Salmon. Carnegie Mellon University ECE Ph.D. Dissertation, CMU-PDL-09-113, August 17, 2009.
Abstract / PDF [3.6M]
- Perspective: Semantic Data Management for the Home. Brandon Salmon, Steven W. Schlosser, Lorrie Faith Cranor, Gregory R. Ganger. 7th USENIX Conference on File and Storage Technologies (FAST '09). Feb. 24-27, 2009. San Francisco, CA. Supercedes Carnegie
Mellon University Parallel Data Lab Technical Report CMU-PDL-08-105, May
Abstract / PDF [275KM]
- Learning to Share: A Study of Sharing Among Home Storage Devices. Brandon Salmon, Frank Hady, Jay Melican. Carnegie Mellon University Parallel Data Lab Technical Report CMU-PDL-07-107, October, 2007.
Abstract / PDF [726K]
- Putting Home Storage Management into Perspective. Brandon Salmon, Steven W. Schlosser, Lily B. Mummert, Gregory R. Ganger.
Carnegie Mellon University Parallel Data Lab Technical Report CMU-PDL-06-110, September 2006.
Abstract / PDF [382K]
- Towards Efficient Semantic Object Storage for the Home. Brandon Salmon, Steven W. Schlosser, Gregory R. Ganger. Carnegie Mellon University Parallel Data Lab Technical Report CMU-PDL-06-103, May 2006.
Abstract / PDF [ 297K]
We thank the members and companies of the PDL Consortium: Actifio, American Power Conversion, EMC Corporation, Facebook, Fusion-io,Google, Hewlett-Packard Labs, Hitachi, Huawei Technologies Co., Intel Corporation, Microsoft Research, NEC Laboratories, NetApp, Inc., Oracle Corporation, Panasas, Samsung Information Systems America, Seagate Technology, Symantec Corporation, VMware, Inc., and Western Digital for their interest, insights, feedback, and support.