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Wen H.,University of Minnesota | Du D.H.C.,University of Minnesota | Shetti M.,HP Storage | Voigt D.,National Defence University | Li S.,HP Storage
Proceedings of the International Conference on Parallel Processing | Year: 2016

In cloud environment, most services are provided by virtual machines (VMs). Providing storage quality of service (QoS) for VMs is essential to user experiences while challenging. It first requires an accurate estimate and description of VM requirements, however, people usually describe this via rules of thumb. The problems are exacerbated by the diversity and special characteristics of VMs in a computing environment. This paper chooses Virtual Desktop Infrastructure (VDI), a prevalent and complicated VM application, to characterize QoS requirements of VMs and to guarantee QoS with minimal required resources. We create a model to describe QoS requirements of VDI. We have collected real VDI traces from HP to validate the correctness of the model. Then we generate QoS requirements of VDI and determine bottlenecks. Based on this, we can tell what minimum capability a storage appliance needs in order to satisfy a given VDI configuration and QoS requirements. By comparing with industry experience, we validate our model. And our model can describe more fine-grained VM requirements varying with time and virtual disk types, and provide more confidence on sizing storage for VDI as well. © 2016 IEEE.


Keeton K.,Hewlett - Packard | Sombrio E.,HP Storage | Nunes L.,HP Storage | Veitch A.,Hewlett - Packard | Zangaro S.,HP Storage
HP Laboratories Technical Report | Year: 2014

The explosive growth in unstructured (file) data in today's IT systems causes significant information management and compliance issues. For example, system administrators need to quickly and efficiently find files that match a given criteria, applications need to "tag" files with custom metadata and query that metadata, utilities need to efficiently determine which files have changed and are in need of backup, and legal staff need to find files that meet e-discovery criteria. In today's huge file systems, comprising billions of files and petabytes of data, these operations can be extremely difficult and time consuming. HP's StoreAll with ExpressQuery provides a scale-out retentionenabled file system for use in archival applications, coupled with a scalable embedded database to accelerate metadata queries. StoreAll's REST API enables users to assign custom metadata to files, and to query system and custom metadata from Express Query efficiently. Queries through the REST API offer over 30,000-fold speedups over file system scans for common file management queries; this speedup increases as the size of the file system grows. This paper summarizes the issues we addressed in translating REST API requests into efficient SQL queries to the Express Query database. © 2014 Hewlett-Packard Development Company, L.P.


Fan Z.,University of Minnesota | Du D.H.C.,University of Minnesota | Voigt D.,HP Storage
IEEE Symposium on Mass Storage Systems and Technologies | Year: 2014

With the rapid development of new types of nonvolatile memory (NVM), one of these technologies may replace DRAM as the main memory in the near future. Some drawbacks of DRAM, such as data loss due to power failure or a system crash can be remedied by NVM's non-volatile nature. In the meantime, solid state drives (SSDs) are becoming widely deployed as storage devices for faster random access speed compared with traditional hard disk drives (HDDs). For applications demanding higher reliability and better performance, using NVM as the main memory and SSDs as storage devices becomes a promising architecture. Although SSDs have better performance than HDDs, SSDs cannot support in-place updates (i.e., an erase operation has to be performed before a page can be updated) and suffer from a low endurance problem that each unit will wear out after certain number of erase operations. In an NVM based main memory, any updated pages called dirty pages can be kept longer without the urgent need to be flushed to SSDs. This difference opens an opportunity to design new cache policies that help extend the lifespan of SSDs by wisely choosing cache eviction victims to decrease storage write traffic. However, it is very challenging to design a policy that can also increase the cache hit ratio for better system performance. Most existing DRAM-based cache policies have mainly concentrated on the recency or frequency status of a page. On the other hand, most existing NVM-based cache policies have mainly focused on the dirty or clean status of a page. In this paper, by extending the concept of the Adaptive Replacement Cache (ARC), we propose a Hierarchical Adaptive Replacement Cache (H-ARC) policy that considers all four factors of a page's status: dirty, clean, recency, and frequency. Specifically, at the higher level, H-ARC adaptively splits the whole cache space into a dirty-page cache and a clean-page cache. At the lower level, inside the dirty-page cache and the clean-page cache, H-ARC splits them into a recency-page cache and a frequency-page cache separately. During the page eviction process, all parts of the cache will be balanced towards to their desired sizes. © 2014 IEEE.


Lillibridge M.,Hewlett - Packard | Eshghi K.,Hewlett - Packard | Bhagwat D.,HP Storage
HP Laboratories Technical Report | Year: 2013

Slow restoration due to chunk fragmentation is a serious problem facing inline chunk-based data deduplication systems: restore speeds for the most recent backup can drop orders of magnitude over the lifetime of a system. We study three techniques-increasing cache size, container capping, and using a forward assembly area- for alleviating this problem. Container capping is an ingest-time operation that reduces chunk fragmentation at the cost of forfeiting some deduplication, while using a forward assembly area is a new restore-time caching and prefetching technique that exploits the perfect knowledge of future chunk accesses available when restoring a backup to reduce the amount of RAM required for a given level of caching at restore time. We show that using a larger cache per stream-we see continuing benefits even up to 8 GB-can produce up to a 5-16X improvement, that giving up as little as 8% deduplication with capping can yield a 2-6X improvement, and that using a forward assembly area is strictly superior to LRU, able to yield a 2-4X improvement while holding the RAM budget constant. © Copyright 2013 Hewlett-Packard Development Company.


Meixner B.,University of Passau | Ettengruber M.,HP Storage | Kosch H.,University of Passau
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | Year: 2012

Preserving access to multimedia data over time may prove to be the most challenging task in all things concerning multimedia. Preserving access to data from previous technical generations has always been a rather difficult endeavor, but multimedia data with an almost endless succession of encoding and compression algorithms sets the stakes even higher, especially when not only considering migrating the data from one generation earlier to a current technology but from decades ago. The time to start thinking and developing techniques and methodologies to keep data accessible over time is right now because the first challenges become visible on the horizon: How to archive the ever growing (and growing exponentially so) amounts of data without major manual intervention as soon as a storage media runs out of free space. Is there such a thing as "endless storage capacity"? Would an "endless storage capacity" really help? Or do we need totally new ways of thinking in regard to archiving digital data for the future? © 2012 Springer-Verlag.


Eshghi K.,Hewlett - Packard | Lillibridge M.,Hewlett - Packard | Bhagwat D.,HP Storage | Bhagwat D.,PernixData | Watkins M.,HP Storage
HP Laboratories Technical Report | Year: 2015

High capacity, high throughput, chunk-based inline deduplication systems for backup have been commercially successful, but scaling them out has proved challenging. In such multi-node systems, the data needs to be routed at a large enough granularity to sustain locality at the back ends. Two routing algorithms, Min Hash and Auction, have been put forth for this purpose. We demonstrate that these algorithms perform poorly on interleaved data. Interleaved data occurs when multiple streams are multiplexed into a single high-speed stream to speed up backups. Of particular commercial importance, database backup procedures produce such interleaved data, where multiple threads read database files in parallel. We present a new routing algorithm, Sticky Auction routing, that, unlike existing algorithms, handles interleaved data with little deduplication loss. It also achieves comparable or better deduplication performance for non-interleaved data and good load balancing, especially when multiple streams are used, the typical case. © Copyright 2015 Hewlett-Packard Development Company, L.P.


Fan Z.,University of Minnesota | Haghdoost A.,University of Minnesota | Du D.H.C.,University of Minnesota | Voigt D.,HP Storage
Proceedings - IEEE Computer Society's Annual International Symposium on Modeling, Analysis, and Simulation of Computer and Telecommunications Systems, MASCOTS | Year: 2015

Most computer systems currently consist of DRAM as main memory and hard disk drives (HDDs) as storage devices. Due to the volatile nature of DRAM, the main memory may suffer from data loss in the event of power failures or system crashes. With rapid development of new types of non-volatile memory (NVRAM), such as PCM, Memristor, and STT-RAM, it becomes likely that one of these technologies will replace DRAM as main memory in the not-too-distant future. In an NVRAM based buffer cache, any updated pages can be kept longer without the urgency to be flushed to HDDs. This opens opportunities for designing new buffer cache policies that can achieve better storage performance. However, it is challenging to design a policy that can also increase the cache hit ratio. In this paper, we propose a buffer cache policy, named I/O-Cache, that regroups and synchronizes long sets of consecutive dirty pages to take advantage of HDDs' fast sequential access speed and the non-volatile property of NVRAM. In addition, our new policy can dynamically separate the whole cache into a dirty cache and a clean cache, according to the characteristics of the workload, to decrease storage writes. We evaluate our scheme with various traces. The experimental results show that I/O-Cache shortens I/O completion time, decreases the number of I/O requests, and improves the cache hit ratio compared with existing cache policies. © 2015 IEEE.


Rabinovici-Cohen S.,IBM | Cummings R.,Antesignanus | Fineberg S.,HP Storage
CEUR Workshop Proceedings | Year: 2014

Long term preservation of digital information, including machine generated large data sets, is a growing necessity in many domains. A key challenge to this need is the creation of vendor-neutral storage containers that can be interpreted over time. We describe SIRF, the Self-contained Information Retention Format, which is being developed by the Storage Networking Industry Association (SNIA) to support this challenge. We define the SIRF components, its metadata, categories and elements, along with some security guidelines. SIRF metadata includes the semantic information as well as schema and ontological information needed to preserve the physical integrity and logical meaning of preservation objects. We also describe how the SIRF logical format is serialized for storage containers in the cloud and for tape based containers. Aspects of SIRF serialization for the cloud are being experimented with OpenStack Swift object storage in the ForgetIT EU project.


News Article | October 28, 2016
Site: www.techrepublic.com

Enterprise server customers demand an efficient, reliable virtual data backup and archiving solution while keeping costs under control. HP Storage provides a variety of reliable data storage solutions that address such requirements. HP StoreEver Storage with Veeam Backup & Replication can provide a complete disk-to-disk-to-tape implementation. Read More

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