Architectures and Algorithms to Exploit Probe-Based Storage
利用基于探针的存储的架构和算法
基本信息
- 批准号:0073509
- 负责人:
- 金额:$ 34.52万
- 依托单位:
- 依托单位国家:美国
- 项目类别:Continuing Grant
- 财政年份:2000
- 资助国家:美国
- 起止时间:2000-09-01 至 2005-06-30
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
The storage density of rotating magnetic recording is approaching itstheoretical maximum. Magnetic probe-based technology avoids these limitations by using techniques such as orthogonal recording which promise very high density storage within the next five to ten years. Probe-based storage devices promise improved access times, enormous potential parallelism gains, and remarkable storage densities. However, because of the unique characteristics of these devices there is a highprobability that existing file system architectures and algorithms will be suboptimal. By reexamining these basic structures in the context of probe-based storage, it is likely that significant performance gains can be achieved.The proposed work comprises fundamental research in four areas: simulation of probe-based storage devices, architectural issues such as parallelism and caching, storage allocation and file layout, and request scheduling. In reexamining these basic issues for this new technology, this research creates a body of work that will lead the way in the development of secondary storage systems for such devices. This research is likely to result in a better understanding of the implementation details associated with probe-based storage devices to provide a set of algorithms and structures that can be used in systems implementations employing them.
旋转磁记录的存储密度正接近其理论最大值。基于磁探头的技术通过使用正交记录等技术避免了这些限制,这些技术有望在未来五到十年内实现非常高密度的存储。基于探针的存储设备有望改善访问时间、获得巨大的潜在并行性和显著的存储密度。然而,由于这些设备的独特特性,现有的文件系统架构和算法很可能不是最优的。通过在基于探测的存储上下文中重新检查这些基本结构,很可能实现显著的性能提升。提出的工作包括四个领域的基础研究:基于探针的存储设备的模拟,架构问题,如并行性和缓存,存储分配和文件布局,以及请求调度。在为这项新技术重新审视这些基本问题的过程中,这项研究创造了一系列工作,将为此类设备的二级存储系统的开发开辟道路。这项研究可能会导致更好地理解与基于探测的存储设备相关的实现细节,从而提供一组算法和结构,这些算法和结构可用于采用它们的系统实现。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Darrell Long其他文献
Oasis: 一种基于对象的主动存储框架
- DOI:
- 发表时间:
2016 - 期刊:
- 影响因子:0
- 作者:
Yulai Xie;Dan Feng;Yan Li;Darrell Long - 通讯作者:
Darrell Long
Paradise: Real-Time, Generalized, and Distributed Provenance-Based Intrusion Detection
- DOI:
10.1109/TDSC.2022.3160879 - 发表时间:
2022 - 期刊:
- 影响因子:7.3
- 作者:
Yafeng Wu;Yulai Xie;Lin Wu;Xuelong Liao;Dan Feng;Pan Zhou;Xuan Li;Avani Wildani;Darrell Long - 通讯作者:
Darrell Long
Efficient Provenance Management via Clustering and Hybrid Storage in Big Data Environments
在大数据环境中通过集群和混合存储进行高效的来源管理
- DOI:
10.1109/tbdata.2019.2907116 - 发表时间:
2020-12 - 期刊:
- 影响因子:7.2
- 作者:
Die Hu;Dan Feng;Yulai Xie;Gongming Xu;Xinrui Gu;Darrell Long - 通讯作者:
Darrell Long
Darrell Long的其他文献
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{{ truncateString('Darrell Long', 18)}}的其他基金
CSR: Small: A Multi-Layered Deniable Steganographic File System
CSR:小型:多层可否认的隐写文件系统
- 批准号:
1814347 - 财政年份:2018
- 资助金额:
$ 34.52万 - 项目类别:
Standard Grant
CSR: Small: Automatic Storage and Network Contention Management for Large-scale High-performance Computing Systems
CSR:小型:大规模高性能计算系统的自动存储和网络争用管理
- 批准号:
1528179 - 财政年份:2015
- 资助金额:
$ 34.52万 - 项目类别:
Standard Grant
SHF:AF:Small:Collaborative Research:RESAR: Robust, Efficient, Scalable, Autonomous Reliable Storage for the Cloud
SHF:AF:Small:协作研究:RESAR:稳健、高效、可扩展、自主可靠的云存储
- 批准号:
1219163 - 财政年份:2012
- 资助金额:
$ 34.52万 - 项目类别:
Standard Grant
TC: Small: LockBox: Enabling Users to Keep Data Safe
TC:小型:LockBox:使用户能够保证数据安全
- 批准号:
1018928 - 财政年份:2010
- 资助金额:
$ 34.52万 - 项目类别:
Standard Grant
A Scalable On-Line Associative Deep Store
可扩展的在线关联深度存储
- 批准号:
0310888 - 财政年份:2003
- 资助金额:
$ 34.52万 - 项目类别:
Continuing Grant
Applications of Data Grouping for Effective Mobility
数据分组在有效移动中的应用
- 批准号:
0204358 - 财政年份:2002
- 资助金额:
$ 34.52万 - 项目类别:
Continuing Grant
COLLABORATIVE RESEARCH: An Experimental Study of Broadcasting Protocols for Video-on-Demand
合作研究:视频点播广播协议的实验研究
- 批准号:
9988363 - 财政年份:2000
- 资助金额:
$ 34.52万 - 项目类别:
Standard Grant
High Performance Integration of Advanced Tertiary Stores
高级三级商店的高性能集成
- 批准号:
9972212 - 财政年份:1999
- 资助金额:
$ 34.52万 - 项目类别:
Standard Grant
Improving Cache Performance by Predicting I/O System Actions
通过预测 I/O 系统操作来提高缓存性能
- 批准号:
9704347 - 财政年份:1997
- 资助金额:
$ 34.52万 - 项目类别:
Standard Grant
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