2008 International Conference on Autonomic Computing最新文献

Autonomic Software Development Methodology Based on Darwinian Evolution 基于达尔文进化论的自主软件开发方法

2008 International Conference on Autonomic Computing Pub Date : 2008-06-02 DOI: 10.1109/ICAC.2008.19

Benjamin E. Beckmann, L. Grabowski, P. McKinley, C. Ofria

引用次数: 7

Digital Evolution of Behavioral Models for Autonomic Systems 自主系统行为模型的数字进化

2008 International Conference on Autonomic Computing Pub Date : 2008-06-02 DOI: 10.1109/ICAC.2008.26

H. Goldsby, B. Cheng, P. McKinley, David B. Knoester, C. Ofria

引用次数: 36

Tailoring Resources: The Energy Efficient Consolidation Strategy Goes Beyond Virtualization 裁剪资源:超越虚拟化的节能整合策略

2008 International Conference on Autonomic Computing Pub Date : 2008-06-02 DOI: 10.1109/ICAC.2008.11

J. Torres, David Carrera, Vicencc Beltran, Nicolás Poggi, Kevin Hogan, J. L. Berral, Ricard Gavaldà, E. Ayguadé, Toni Moreno, Jordi Guitart

{"title":"Tailoring Resources: The Energy Efficient Consolidation Strategy Goes Beyond Virtualization","authors":"J. Torres, David Carrera, Vicencc Beltran, Nicolás Poggi, Kevin Hogan, J. L. Berral, Ricard Gavaldà, E. Ayguadé, Toni Moreno, Jordi Guitart","doi":"10.1109/ICAC.2008.11","DOIUrl":"https://doi.org/10.1109/ICAC.2008.11","url":null,"abstract":"Virtualization and consolidation are two complementary techniques widely adopted in a global strategy to reduce system management complexity. In this paper we show how two simple and well-known techniques can be combined to dramatically increase the energy efficiency of a virtualized and consolidated data center. This result is obtained by introducing a new approach to the consolidation strategy that allows an important reduction in the amount of active nodes required to process a web workload without degrading the offered service level. Furthermore, when the system eventually gets overloaded and no energy can be saved without loosing performance, we show how these techniques can still improve the overall value obtained from the workload. The two techniques are memory compression and request discrimination, and were separately studied and validated in a previous work to be now combined in a joint effort. Our results indicate that an important improvement can be achieved by deciding not only how resources are allocated, but also how they are used. Moreover, we believe that this serves as an illustrative example of a new way of management: tailoring the resources to meet high level energy efficiency goals.","PeriodicalId":436716,"journal":{"name":"2008 International Conference on Autonomic Computing","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129437007","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: 22

Self-Configuration in Autonomic Systems Using Clustered CBR Approach 基于聚类CBR方法的自主系统自配置

2008 International Conference on Autonomic Computing Pub Date : 2008-06-02 DOI: 10.1109/ICAC.2008.10

M. Khan, M. Awais, S. Shamail

引用次数: 10

Enabling Autonomic Meta-Scheduling in Grid Environments 在网格环境中实现自主元调度

2008 International Conference on Autonomic Computing Pub Date : 2008-06-02 DOI: 10.1109/ICAC.2008.15

Yanbin Liu, S. M. Sadjadi, L. Fong, I. Rodero, David Villegas, Selim Kalayci, N. Bobroff, Juan Carlos Martínez

{"title":"Enabling Autonomic Meta-Scheduling in Grid Environments","authors":"Yanbin Liu, S. M. Sadjadi, L. Fong, I. Rodero, David Villegas, Selim Kalayci, N. Bobroff, Juan Carlos Martínez","doi":"10.1109/ICAC.2008.15","DOIUrl":"https://doi.org/10.1109/ICAC.2008.15","url":null,"abstract":"Grid computing supports workload execution on computing resources that are shared across a set of collaborative organizations. At the core of workload management for grid computing is a software component, called meta-scheduler or grid resource broker, that provides a virtual layer on top of heterogeneous grid middleware, schedulers, and resources. Meta-schedulers typically enable end-users and applications to compete over distributed shared resources through the use of one or more instances of the same meta-scheduler, in a centralized or distributed manner, respectively. We propose an approach to enabling autonomic meta-scheduling through the use of a new communication protocol that -if adopted by different meta-schedulers or by the applications using them- can improve the workload execution while avoiding potential chaos, which can be resulted from blind competition over resources. This can be made possible by allowing the meta- schedulers and/or their applications to engage in a process to negotiate their roles (e.g., consumer, provider, or both), scheduling policies, service-level agreement, etc. To show the feasibility of our approach, we developed a prototype that enables some preliminary autonomic management among three different meta-schedulers, namely, GridWay, eNANOS, andTDWB.","PeriodicalId":436716,"journal":{"name":"2008 International Conference on Autonomic Computing","volume":"139 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127394421","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

Multi-Level Intrusion Detection System (ML-IDS) 多级入侵检测系统(ML-IDS)

2008 International Conference on Autonomic Computing Pub Date : 2008-06-02 DOI: 10.1109/ICAC.2008.25

Y. Al-Nashif, Aarthi Arun Kumar, S. Hariri, Yi Luo, F. Szidarovszky, Guangzhi Qu

引用次数: 65

CARVE: A Cognitive Agent for Resource Value Estimation 资源价值评估的认知代理

2008 International Conference on Autonomic Computing Pub Date : 2008-06-02 DOI: 10.1109/ICAC.2008.27

Jonathan Wildstrom, P. Stone, E. Witchel

{"title":"CARVE: A Cognitive Agent for Resource Value Estimation","authors":"Jonathan Wildstrom, P. Stone, E. Witchel","doi":"10.1109/ICAC.2008.27","DOIUrl":"https://doi.org/10.1109/ICAC.2008.27","url":null,"abstract":"Recently, industry has begun investigating and moving towards utility computing, where computational resources (processing, memory and I/O) are availably on demand at a market cost. On-demand access to computational resources enables fine-grained resource allocation for web-based applications, e.g., the possibility of provisioning for a minimum workload while allowing the rental of additional resources for unexpected workload changes. However, renting additional resources relies on the ability to quickly and accurately estimate the value of the resource. This paper introduces CARVE: a cognitive agent for resource value estimation. CARVE is a machine-learning based approach that learns to predict the change in system value of having more or less system resources. Using only low-level statistics and with no custom instrumentation of the operating system or middleware, CARVE is able to make informed decisions about the return on investment of physical memory when implemented and evaluated on a partitioned system running a multi-partition, multi-process distributed benchmark. We show that CARVE is competitive with static choices of computing resources over a variety of test workloads and also has the ability to outperform all static configurations.","PeriodicalId":436716,"journal":{"name":"2008 International Conference on Autonomic Computing","volume":"122 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116842862","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: 29

Utility-Based Reinforcement Learning for Reactive Grids 基于效用的反应网格强化学习

2008 International Conference on Autonomic Computing Pub Date : 2008-06-02 DOI: 10.1109/ICAC.2008.18

Julien Perez, C. Germain, B. Kégl, C. Loomis

引用次数: 24

Towards a Self-Configurable Weather Research and Forecasting System 面向自配置的天气研究预报系统

2008 International Conference on Autonomic Computing Pub Date : 2008-06-02 DOI: 10.1109/ICAC.2008.17

K. Saleem, S. M. Sadjadi, Shu‐Ching Chen

引用次数: 11

Clustering Analysis for the Management of Self-Monitoring Device Networks 基于聚类分析的自监控设备网络管理

2008 International Conference on Autonomic Computing Pub Date : 2008-06-02 DOI: 10.1109/ICAC.2008.30

Andres Quiroz, M. Parashar, N. Gnanasambandam, Naveen Sharma

引用次数: 7