ACM Cloud and Autonomic Computing Conference最新文献_第2页

An adaptive data transfer algorithm using block device reconfiguration in virtual MapReduce clusters 基于块设备重构的虚拟MapReduce集群自适应数据传输算法

ACM Cloud and Autonomic Computing Conference Pub Date : 2013-08-09 DOI: 10.1145/2494621.2494645

Kwonyong Lee, Yoonsung Nam, Taekhee Kim, Sungyong Park

{"title":"An adaptive data transfer algorithm using block device reconfiguration in virtual MapReduce clusters","authors":"Kwonyong Lee, Yoonsung Nam, Taekhee Kim, Sungyong Park","doi":"10.1145/2494621.2494645","DOIUrl":"https://doi.org/10.1145/2494621.2494645","url":null,"abstract":"With the proliferation of cloud computing and virtual machine technologies, MapReduce applications are increasingly deployed in clouds to leverage the full potential of cloud computing environments. However, the MapReduce, which is generally used for processing large amount of data, suffers from the I/O virtualization overheads and resource competitions among virtual machines when it is run on virtual clouds. This paper proposes an adaptive data transfer algorithm in virtual MapReduce clusters. The proposed algorithm utilizes a block device reconfiguration scheme, where a block device attached to a virtual machine can be dynamically detached and reattached to other virtual machines hosted in the same physical machine. By reconfiguring the block devices, we can easily move files across different virtual machines located at the same physical machine without any network transfers between virtual machines. When the output of each map task is transferred to the reducer, this algorithm adaptively determines an appropriate transfer method between network transfer and block device reconfiguration based on current CPU utilization values and the data size for the transfer. Even in the case of data transfer between virtual machines across multiple physical machines, we can remove the transfer overheads between the virtual machine and the driver domain, which results in reducing the data transfer time and performance effects to other virtual machines in the shuffle phase. We have implemented our algorithm in Hadoop MapReduce. The benchmarking results show that the overheads incurred by transferring data from mapper virtual machines to reducer virtual machines are minimized and the execution times of MapReduce applications are shortened.","PeriodicalId":190559,"journal":{"name":"ACM Cloud and Autonomic Computing Conference","volume":"72 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-08-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125294086","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: 1

Resilient cloud data storage services 弹性云数据存储服务

ACM Cloud and Autonomic Computing Conference Pub Date : 2013-08-09 DOI: 10.1145/2494621.2494634

Hemayamini Kurra, Y. Al-Nashif, S. Hariri

引用次数: 6

A scalable, non-parametric anomaly detection framework for Hadoop 一个可扩展的、非参数的Hadoop异常检测框架

ACM Cloud and Autonomic Computing Conference Pub Date : 2013-08-09 DOI: 10.1145/2494621.2494643

Li Yu, Z. Lan

引用次数: 20

A vision for monitoring cloud application platforms as sensor networks 将云应用平台监控为传感器网络的愿景

ACM Cloud and Autonomic Computing Conference Pub Date : 2013-08-09 DOI: 10.1145/2494621.2494647

R. Dautov, I. Paraskakis

引用次数: 10

Autonomic load balancing mechanisms in the P2P desktop grid P2P桌面网格中的自主负载平衡机制

ACM Cloud and Autonomic Computing Conference Pub Date : 2013-08-09 DOI: 10.1145/2494621.2494646

Jik-Soo Kim, Beomseok Nam, A. Sussman

{"title":"Autonomic load balancing mechanisms in the P2P desktop grid","authors":"Jik-Soo Kim, Beomseok Nam, A. Sussman","doi":"10.1145/2494621.2494646","DOIUrl":"https://doi.org/10.1145/2494621.2494646","url":null,"abstract":"Peer-to-Peer (P2P) desktop grid computing systems circumvent the performance bottleneck and limited scalability of centralized Grid architectures resulting in a massively scalable and robust system. We have designed a set of protocols that implement a distributed, decentralized desktop grid via P2P techniques. Incoming jobs having different types of resource requirements are matched with system nodes through proximity in an N-dimensional resource space.\u0000 In this paper, we address problems that arise from static load balancing mechanisms for assigning jobs to nodes that can arise for various reasons, including the heterogeneity of the available nodes or the jobs to be run, and from stale information in the P2P system. We greatly improve upon our prior work by providing lightweight yet effective dynamic load balancing mechanisms to overcome load imbalances caused by the limitations of the initial static job assignment scheme. Unlike other systems, we can effectively support resource constraints of jobs during the course of redistribution since we simplify the problem of matchmaking through building a multi-dimensional resource space and mapping jobs and nodes to this space. Throughout extensive simulation results, we show that dynamic load balancing makes the overall system more scalable, by improving system throughput and response time with low additional overhead.","PeriodicalId":190559,"journal":{"name":"ACM Cloud and Autonomic Computing Conference","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-08-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115655830","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: 1

On the role of topology in autonomously coping with failures in content dissemination systems 论拓扑在内容传播系统故障自主处理中的作用

ACM Cloud and Autonomic Computing Conference Pub Date : 2013-08-09 DOI: 10.1145/2494621.2494635

Ryan Stern, S. Pallickara

引用次数: 1

A truthful approximation mechanism for autonomic virtual machine provisioning and allocation in clouds 云环境中自主虚拟机供应和分配的真实逼近机制

ACM Cloud and Autonomic Computing Conference Pub Date : 2013-08-09 DOI: 10.1145/2494621.2494637

Lena Mashayekhy, Mahyar Movahed Nejad, Daniel Grosu

引用次数: 19

A flexible elastic control plane for private clouds 为私有云提供灵活的弹性控制平面

ACM Cloud and Autonomic Computing Conference Pub Date : 2013-08-09 DOI: 10.1145/2494621.2494626

Upendra Sharma, P. Shenoy, S. Sahu

{"title":"A flexible elastic control plane for private clouds","authors":"Upendra Sharma, P. Shenoy, S. Sahu","doi":"10.1145/2494621.2494626","DOIUrl":"https://doi.org/10.1145/2494621.2494626","url":null,"abstract":"While public cloud computing platforms have become popular in recent years, private clouds---operated by enterprises for their internal use---have also begun gaining traction. The configuration and continuous tuning of a private cloud to meet user demands is a complex task. While private cloud management frameworks provide a number of flexible configuration options for this purpose, they leave it to the administrator to determine how to best configure and tune the cloud platform for local needs. In this paper, we argue for an adaptive control plane for private clouds that simplifies the tasks of configuring and operating a private cloud such that each control plane service is adaptive to the workload seen due to end-user requests. We present a logistic regression model to automate the provisioning and dynamic reconfiguration of control plane services in a private cloud. We implement our approach for two control plane services---monitoring and messaging---for OpenStack-based private clouds. Our experimental results on a laboratory private cloud testbed and using public cloud workloads demonstrates the ability of our approach to provision and adapt such services from very small to very large private cloud configurations.","PeriodicalId":190559,"journal":{"name":"ACM Cloud and Autonomic Computing Conference","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-08-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125123189","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: 8

QACO: exploiting partial execution in web servers QACO:利用web服务器中的部分执行

ACM Cloud and Autonomic Computing Conference Pub Date : 2013-08-09 DOI: 10.1145/2494621.2494636

Jinha Kim, S. Elnikety, Yuxiong He, Seung-won Hwang, Shaolei Ren

{"title":"QACO: exploiting partial execution in web servers","authors":"Jinha Kim, S. Elnikety, Yuxiong He, Seung-won Hwang, Shaolei Ren","doi":"10.1145/2494621.2494636","DOIUrl":"https://doi.org/10.1145/2494621.2494636","url":null,"abstract":"Web servers provide content to users, with the requirement of providing high response quality within a short response time. Meeting these requirements is challenging, especially in the event of load spikes. Meanwhile, we observe that a response to a request can be adapted or partially executed depending on current resource availability at the server. For example, a web server can choose to send a low or medium resolution image instead of sending the original high resolution image under resource contention.\u0000 In this paper, we exploit partial execution to expose a trade off between resource consumption and service quality. We show how to manage server resources to improve service quality and responsiveness. Specifically, we develop a framework, called Quota-based Control Optimization (QACO). The quota represents the total amount of resources available for all pending requests. QACO consists of two modules: (1) A control module adjusts the quota to meet the response time target. (2) An optimization module exploits partial execution and allocates the quota to pending requests in a manner that improves total response quality. We evaluate the framework using a system implementation in the Apache Web server, and using a simulation study of a Video-on-Demand server. The results show that under a response time target, QACO achieves a higher response quality than traditional techniques that admit or reject requests without exploiting partial execution.","PeriodicalId":190559,"journal":{"name":"ACM Cloud and Autonomic Computing Conference","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-08-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117189317","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: 6

An integrated management system of virtual resources based on virtualization API and data distribution service 基于虚拟化API和数据分发服务的虚拟资源集成管理系统

ACM Cloud and Autonomic Computing Conference Pub Date : 2013-08-09 DOI: 10.1145/2494621.2494648

Yongseong Cho, Jongsun Choi, Jaeyoung Choi

引用次数: 11