Proceedings. Data Compression Conference最新文献_第2页

Optimized VM memory allocation based on monitored cache hit ratio 根据监控的缓存命中率优化虚拟机内存分配

Proceedings. Data Compression Conference Pub Date : 2016-07-25 DOI: 10.1145/2955193.2955200

Saneyasu Yamaguchi, Eita Fujishima

{"title":"Optimized VM memory allocation based on monitored cache hit ratio","authors":"Saneyasu Yamaguchi, Eita Fujishima","doi":"10.1145/2955193.2955200","DOIUrl":"https://doi.org/10.1145/2955193.2955200","url":null,"abstract":"Cloud computing by the use of virtual machines has become increasingly important in various situations. In such an environment, multiple virtual machines run on a single physical machine. Many hypervisor implementations have a ballooning function. This function enables virtual machine memory size to be dynamically changed at runtime. Hence, it is expected that dynamic memory resource management while considering the application loads can improve its performance. In particular, I/O performance is expected to be improved significantly because it strongly depends on the size of the HDD cache in an operating system, e.g., a page cache in Linux. The Xen hypervisor has xenballoon, which dynamically changes the size of the virtual machine memory based on the size of memory consumed by the processes in the virtual machines and does not consider the size of the page cache. Therefore, the I/O performance is not improved. In a study, a method for adjusting virtual machine memory size was proposed. However, it assumes applications to be homogeneous. In this paper, we propose a method for dynamic management of virtual machine memory size without assumption for applications. The method takes into account the page cache hit ratio. We show the performance evaluation of the method for various read/write applications. The experimental results demonstrate that our method can improve performance of I/O intensive applications in virtual machines.","PeriodicalId":91161,"journal":{"name":"Proceedings. Data Compression Conference","volume":"31 1","pages":"8:1-8:6"},"PeriodicalIF":0.0,"publicationDate":"2016-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84224291","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 4

The misbelief in delay scheduling 对延迟调度的误解

Proceedings. Data Compression Conference Pub Date : 2016-07-25 DOI: 10.1145/2955193.2955203

Derek Schatzlein, Srivatsan Ravi, Youngtae Noh, Masoud Saeida Ardekani, P. Eugster

{"title":"The misbelief in delay scheduling","authors":"Derek Schatzlein, Srivatsan Ravi, Youngtae Noh, Masoud Saeida Ardekani, P. Eugster","doi":"10.1145/2955193.2955203","DOIUrl":"https://doi.org/10.1145/2955193.2955203","url":null,"abstract":"Big-data processing frameworks like Hadoop and Spark, often used in multi-user environments, have struggled to achieve a balance between the full utilization of cluster resources and fairness between users. In particular, data locality becomes a concern, as enforcing fairness policies may cause poor placement of tasks in relation to the data on which they operate. To combat this, the schedulers in many frameworks use a heuristic called delay scheduling, which involves waiting for a short, constant interval for data-local task slots to become free if none are available; however, a fixed delay interval is inefficient, as the ideal time to delay varies depending on input data size, network conditions, and other factors.\u0000 We propose an adaptive solution (Dynamic Delay Scheduling), which uses a simple feedback metric from finished tasks to adapt the delay scheduling interval for subsequent tasks at runtime. We present a dynamic delay implementation in Spark, and show that it outperforms a fixed delay in TPC-H benchmarks. Our preliminary experiments confirm our intuition that job latency in batch-processing scheduling can be improved using simple adaptive techniques with almost no extra state overhead.","PeriodicalId":91161,"journal":{"name":"Proceedings. Data Compression Conference","volume":"45 1","pages":"9:1-9:6"},"PeriodicalIF":0.0,"publicationDate":"2016-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81885368","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

DSB-SEIS: a deduplicating secure backup system with encryption intensity selection DSB-SEIS:具有加密强度选择的重复数据删除安全备份系统

Proceedings. Data Compression Conference Pub Date : 2016-07-25 DOI: 10.1145/2955193.2955208

Mortada A. Aman, Egemen K. Çetinkaya

引用次数: 1

The CAT theorem and performance of transactional distributed systems 事务性分布式系统的CAT定理与性能

Proceedings. Data Compression Conference Pub Date : 2016-07-25 DOI: 10.1145/2955193.2955205

S. Ahsan, Indranil Gupta

引用次数: 2

Adaptive resilient routing via preorders in SDN 自适应弹性路由通过预定在SDN

Proceedings. Data Compression Conference Pub Date : 2016-07-25 DOI: 10.1145/2955193.2955204

Eman Ramadan, Hesham Mekky, Braulio Dumba, Zhi-Li Zhang

引用次数: 8

vMCN: virtual mobile cloud network for realizing scalable, real-time cyber physical systems vMCN:用于实现可扩展、实时的网络物理系统的虚拟移动云网络

Proceedings. Data Compression Conference Pub Date : 2016-07-25 DOI: 10.1145/2955193.2955201

K. Nakauchi, F. Bronzino, Y. Shoji, I. Seskar, D. Raychaudhuri

{"title":"vMCN: virtual mobile cloud network for realizing scalable, real-time cyber physical systems","authors":"K. Nakauchi, F. Bronzino, Y. Shoji, I. Seskar, D. Raychaudhuri","doi":"10.1145/2955193.2955201","DOIUrl":"https://doi.org/10.1145/2955193.2955201","url":null,"abstract":"This paper presents virtual Mobile Cloud Network (vMCN), an architecture for scalable, real-time Cyber Physical Systems (CPS) based on virtualization-capable network infrastructure and highly distributed edge clouds. Emerging CPS applications running on mobile devices, such as Augmented Reality (AR) based navigation and self-driving cars, have fundamental limitations; (1) the response time over the networks is unmanageable and CPS applications suffer from large response times, especially over shared wireless links; (2) the number of real-virtual object mappings cannot be scaled to the approaching trillion order of magnitude in an unified manner. vMCN addresses these issues by introducing novel network virtualization techniques that exploit the \"named object\" abstraction provided by a fast and scalable global name service. Coordinating virtualized resources across multiple domains, vMCN supports the distributed edge cloud model by deploying an application aware anycast services that achieve the strict requirements of CPS while still scaling to the expected order of magnitude of devices. An initial vMCN prototype system has been developed using the ORBIT testbed resources and the NICT's virtualization-capable WiFi base station. Experimental results reveal the vMCN can support up to about 94% CPS cycles under the set goal of 100 ms, outperforming the baseline system by almost two times.","PeriodicalId":91161,"journal":{"name":"Proceedings. Data Compression Conference","volume":"80 1","pages":"2:1-2:6"},"PeriodicalIF":0.0,"publicationDate":"2016-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79320558","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 9

Towards migrating computation to distributed memory caches 将计算迁移到分布式内存缓存

Proceedings. Data Compression Conference Pub Date : 2016-07-25 DOI: 10.1145/2955193.2955202

Adam Schaub, Michael F. Spear

引用次数: 0

A cluster-based approach to compression of Quality Scores. 基于聚类的质量分数压缩方法。

Proceedings. Data Compression Conference Pub Date : 2016-03-01 Epub Date: 2016-12-19 DOI: 10.1109/DCC.2016.49

Mikel Hernaez, Idoia Ochoa, Tsachy Weissman

{"title":"A cluster-based approach to compression of Quality Scores.","authors":"Mikel Hernaez, Idoia Ochoa, Tsachy Weissman","doi":"10.1109/DCC.2016.49","DOIUrl":"https://doi.org/10.1109/DCC.2016.49","url":null,"abstract":"Massive amounts of sequencing data are being generated thanks to advances in sequencing technology and a dramatic drop in the sequencing cost. Storing and sharing this large data has become a major bottleneck in the discovery and analysis of genetic variants that are used for medical inference. As such, lossless compression of this data has been proposed. Of the compressed data, more than 70% correspond to quality scores, which indicate the sequencing machine reliability when calling a particular basepair. Thus, to further improve the compression performance, lossy compression of quality scores is emerging as the natural candidate. Since the data is used for genetic variants discovery, lossy compressors for quality scores are analyzed in terms of their rate-distortion performance, as well as their effect on the variant callers. Previously proposed algorithms do not do well under all performance metrics, and are hence unsuitable for certain applications. In this work we propose a new lossy compressor that first performs a clustering step, by assuming all the quality scores sequences come from a mixture of Markov models. Then, it performs quantization of the quality scores based on the Markov models. Each quantizer targets a specific distortion to optimize for the overall rate-distortion performance. Finally, the quantized values are compressed by an entropy encoder. We demonstrate that the proposed lossy compressor outperforms the previously proposed methods under all analyzed distortion metrics. This suggests that the effect that the proposed algorithm will have on any downstream application will likely be less noticeable than that of previously proposed lossy compressors. Moreover, we analyze how the proposed lossy compressor affects Single Nucleotide Polymorphism (SNP) calling, and show that the variability introduced on the calls is considerably smaller than the variability that exists between different methodologies for SNP calling.","PeriodicalId":91161,"journal":{"name":"Proceedings. Data Compression Conference","volume":"2016 ","pages":"261-270"},"PeriodicalIF":0.0,"publicationDate":"2016-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/DCC.2016.49","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"35532453","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 10

An Evaluation Framework for Lossy Compression of Genome Sequencing Quality Values. 基因组测序质量值的有损压缩评估框架。

Proceedings. Data Compression Conference Pub Date : 2016-03-01 Epub Date: 2016-12-19 DOI: 10.1109/DCC.2016.39

Claudio Alberti, Noah Daniels, Mikel Hernaez, Jan Voges, Rachel L Goldfeder, Ana A Hernandez-Lopez, Marco Mattavelli, Bonnie Berger

引用次数: 0

Denoising of Quality Scores for Boosted Inference and Reduced Storage. 为提升推理和减少存储而对质量分数去噪。

Proceedings. Data Compression Conference Pub Date : 2016-03-01 Epub Date: 2016-12-19 DOI: 10.1109/DCC.2016.92

Idoia Ochoa, Mikel Hernaez, Rachel Goldfeder, Tsachy Weissman, Euan Ashley

{"title":"Denoising of Quality Scores for Boosted Inference and Reduced Storage.","authors":"Idoia Ochoa, Mikel Hernaez, Rachel Goldfeder, Tsachy Weissman, Euan Ashley","doi":"10.1109/DCC.2016.92","DOIUrl":"10.1109/DCC.2016.92","url":null,"abstract":"Massive amounts of sequencing data are being generated thanks to advances in sequencing technology and a dramatic drop in the sequencing cost. Much of the raw data are comprised of nucleotides and the corresponding quality scores that indicate their reliability. The latter are more difficult to compress and are themselves noisy. Lossless and lossy compression of the quality scores has recently been proposed to alleviate the storage costs, but reducing the noise in the quality scores has remained largely unexplored. This raw data is processed in order to identify variants; these genetic variants are used in important applications, such as medical decision making. Thus improving the performance of the variant calling by reducing the noise contained in the quality scores is important. We propose a denoising scheme that reduces the noise of the quality scores and we demonstrate improved inference with this denoised data. Specifically, we show that replacing the quality scores with those generated by the proposed denoiser results in more accurate variant calling in general. Moreover, a consequence of the denoising is that the entropy of the produced quality scores is smaller, and thus significant compression can be achieved with respect to lossless compression of the original quality scores. We expect our results to provide a baseline for future research in denoising of quality scores. The code used in this work as well as a Supplement with all the results are available at http://web.stanford.edu/~iochoa/DCCdenoiser_CodeAndSupplement.zip.","PeriodicalId":91161,"journal":{"name":"Proceedings. Data Compression Conference","volume":"2016 ","pages":"251-260"},"PeriodicalIF":0.0,"publicationDate":"2016-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5663231/pdf/nihms910316.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"35567963","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0