{"title":"Hierarchical Replication Control in a Global File System","authors":"Jiaying Zhang, P. Honeyman","doi":"10.1109/CCGRID.2007.57","DOIUrl":"https://doi.org/10.1109/CCGRID.2007.57","url":null,"abstract":"We develop a consistent mutable replication extension for NFSv4 tuned to meet the rigorous demands of large-scale data sharing in global collaborations. The system uses a hierarchical replication control protocol that dynamically elects a primary server at various granularities. Experimental evaluation indicates a substantial performance advantage over a single server system. With the introduction of the hierarchical replication control, the overhead of replication is negligible even when applications mostly write and replication servers are widely distributed.","PeriodicalId":278535,"journal":{"name":"Seventh IEEE International Symposium on Cluster Computing and the Grid (CCGrid '07)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132836644","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}
{"title":"Performance Evaluation in Grid Computing: A Modeling and Prediction Perspective","authors":"Hui Li","doi":"10.1109/CCGRID.2007.84","DOIUrl":"https://doi.org/10.1109/CCGRID.2007.84","url":null,"abstract":"Experimental performance studies on computer systems, including Grids, require deep understandings on their workload characteristics. The need arises from two important and closely related topics in performance evaluation, namely, workload modeling and performance prediction. Both topics rely heavily on the representative workload data and have their arsenal from statistics and machine learning. Nevertheless, their goals and the nature of research differ considerably. Workload modeling aims at building mathematical models to generate workloads that can be used in simulation-based performance evaluation studies. It should statistically resemble the original real-world data therefore marginal statistics and second-order properties such as autocorrelation and power spectrum are important matching criteria. Performance prediction, on the other hand, intends to provide realtime forecast of important performance metrics (such as application run time and queue wait time) which can support Grid scheduling decisions. From this perspective prediction accuracy as well as performance should be considered to evaluate candidate techniques. My PhD research focuses primarily on these two topics in space-shared, data-intensive Grid environments. Starting from a comprehensive workload analysis with emphasis on the correlation structures and the scaling behavior, several basic job arrival patterns such as pseudo-periodicity and long range dependence are identified. Models are further proposed to capture these important arrival patterns and a complete workload model including run time is being investigated. The strong autocorrelations present in run time and queue wait time series inspire the research for performance prediction based on learning from historical data. Techniques based on a instance based learning algorithm and several improvements are proposed and empirically evaluated. Research plans are proposed to use the results of workload modeling and performance prediction in the evaluation of scheduling strategies in data-intensive Grid environments.","PeriodicalId":278535,"journal":{"name":"Seventh IEEE International Symposium on Cluster Computing and the Grid (CCGrid '07)","volume":"65 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133764734","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}
{"title":"A Robust Decentralized Job Scheduling Approach for Mobile Peers in Ad-hoc Grids","authors":"K. Hummel, Gerda Jelleschitz","doi":"10.1109/CCGRID.2007.9","DOIUrl":"https://doi.org/10.1109/CCGRID.2007.9","url":null,"abstract":"The increasing capabilities and spreading of mobile technology raise the opportunity to integrate potentially unstable mobile devices as resources into grids. In this work, we contribute by proposing and evaluating a robust decentralized job scheduling approach for mobile peers forming an ad-hoc grid. The scheduling approach is based on a first come first serve strategy executed locally by each peer. Additionally, the peer performs matchmaking between a job's requirements and the device's capabilities autonomously. Coordination between mobile peers is based on job queues shared within a distributed virtual shared memory (VSM). By applying proactive and reactive fault tolerance mechanisms we were able to increase the robustness of the scheduler. A prototypical implementation using the VSM CORSO, Java, and Condor ClassAds demonstrates the feasibility of our approach. The conducted experiments show that the job loss ratio and the average job response time can be decreased by adding fault tolerance mechanisms.","PeriodicalId":278535,"journal":{"name":"Seventh IEEE International Symposium on Cluster Computing and the Grid (CCGrid '07)","volume":"310 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131817285","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}
{"title":"Incremental Trust in Grid Computing","authors":"Michael Brinklov, Robin Sharp","doi":"10.1109/CCGRID.2007.63","DOIUrl":"https://doi.org/10.1109/CCGRID.2007.63","url":null,"abstract":"This paper describes a comparative simulation study of some incremental trust and reputation algorithms for handling behavioural trust in large distributed systems. Two types of reputation algorithm (based on discrete and Bayesian evaluation of ratings) and two ways of combining direct trust and reputation (discrete combination and combination based on fuzzy logic) are considered. The various combinations of these methods are evaluated from the point of view of their ability to respond to changes in behaviour and the ease with which suitable parameters for the algorithms can be found in the context of Grid systems.","PeriodicalId":278535,"journal":{"name":"Seventh IEEE International Symposium on Cluster Computing and the Grid (CCGrid '07)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126380886","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}
{"title":"Distributed Visualization Using VTK in Grid Environments","authors":"M. L. Dutra, P. Rodrigues, G. Giraldi, B. Schulze","doi":"10.1109/CCGRID.2007.43","DOIUrl":"https://doi.org/10.1109/CCGRID.2007.43","url":null,"abstract":"In this paper we focus on distributed visualization using the visualization toolkit (VTK) in grid environments. We propose a distributed architecture, based on data parallelism, that allows the distribution of visualization tasks over a grid environment. We decided for globus toolkit as a middleware to provide access and location transparencies. We also add facilities for dynamic allocation of resources by using a Java framework. The focused visualization technique is Laplacian smoothing which is provided by a specific filter of the VTK library. We emphasize the obtained speedup in the experiments and discuss the implementation of pipeline parallelism as well as the generalization of our architecture for other VTK applications.","PeriodicalId":278535,"journal":{"name":"Seventh IEEE International Symposium on Cluster Computing and the Grid (CCGrid '07)","volume":"182 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123005298","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}
Ariadne A. Cruz, Fabio A. L. Gomes, Fabbryccio A. C. M. Cardoso, Ernesto B. Martin, D. Arantes
{"title":"Development of a Robust and Flexible Weblab Framework based on AJAX and Design Patterns","authors":"Ariadne A. Cruz, Fabio A. L. Gomes, Fabbryccio A. C. M. Cardoso, Ernesto B. Martin, D. Arantes","doi":"10.1109/CCGRID.2007.40","DOIUrl":"https://doi.org/10.1109/CCGRID.2007.40","url":null,"abstract":"The objective of this paper is to present a generic and extensible access framework architecture for WebLab integration. In this framework each Weblab becomes accessible by means of a preinstalled plug-in. This modular approach makes it possible to add, remove or modify a plug-in, and its corresponding Weblab, without framework recompilation.","PeriodicalId":278535,"journal":{"name":"Seventh IEEE International Symposium on Cluster Computing and the Grid (CCGrid '07)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120957143","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}
R. Souto, R. Ávila, P. Navaux, M. X. Py, T. A. Diverio, H. Velho, S. Stephany, A. J. Preto, J. Panetta, E. Rodrigues, E. Almeida, P. Dias, A. W. Gandu
{"title":"Processing Mesoscale Climatology in a Grid Environment","authors":"R. Souto, R. Ávila, P. Navaux, M. X. Py, T. A. Diverio, H. Velho, S. Stephany, A. J. Preto, J. Panetta, E. Rodrigues, E. Almeida, P. Dias, A. W. Gandu","doi":"10.1109/CCGRID.2007.86","DOIUrl":"https://doi.org/10.1109/CCGRID.2007.86","url":null,"abstract":"Enhancing the quality of weather and climate forecasts are central scientific research objectives worldwide. However, simulations of the atmosphere, usually demand high processing power and large storage resources. In this context, we present the GBRAMS project, that applies grid computing to speed up the generation of a regional model climatology for Brazil. A grid infrastructure was built to perform long-term integrations of a mesoscale numerical model (BRAMS), managing a queue of up to nine independent jobs submitted to three clusters spread over Brazil- Three distinct middlewares, Globus Toolkit, OurGrid and OAR/CIGRI, were compared in their ability to manage these jobs, and results on the usage of each node of the grid are provided. We analyze the impact of the resulted climatology in the accuracy of climate forecast, showing model bias removal which indicates correctness of the generated climatology. Our central contribution are how to use grid computing to speed-up climatology generation and the middleware impact on this enterprise.","PeriodicalId":278535,"journal":{"name":"Seventh IEEE International Symposium on Cluster Computing and the Grid (CCGrid '07)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117041718","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}
{"title":"Active Data: Supporting the Grid Data Life Cycle","authors":"Tim Ho, D. Abramson","doi":"10.1109/CCGRID.2007.16","DOIUrl":"https://doi.org/10.1109/CCGRID.2007.16","url":null,"abstract":"Scientific applications often involve computation intensive workflows and may generate large amount of derived data. In this paper we consider a life cycle, which starts when the data is first generated, and tracks its progress through replication, distribution, deletion and possible re-computation. We describe the design and implementation of an infrastructure, called active data, which combines existing grid middleware to support the scientific data lifecycle in a platform-neutral environment.","PeriodicalId":278535,"journal":{"name":"Seventh IEEE International Symposium on Cluster Computing and the Grid (CCGrid '07)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129467933","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}
Kaoutar El Maghraoui, Travis Desell, B. Szymanski, Carlos A. Varela
{"title":"Dynamic Malleability in Iterative MPI Applications","authors":"Kaoutar El Maghraoui, Travis Desell, B. Szymanski, Carlos A. Varela","doi":"10.1109/CCGRID.2007.45","DOIUrl":"https://doi.org/10.1109/CCGRID.2007.45","url":null,"abstract":"Malleability enables a parallel application's execution system to split or merge processes modifying granularity. While process migration is widely used to adapt applications to dynamic execution environments, it is limited by the granularity of the application's processes. Malleability empowers process migration by allowing the application's processes to expand or shrink following the availability of resources. We have implemented malleability as an extension to the PCM (process checkpointing and migration) library, a user-level library for iterative MPI applications. PCM is integrated with the Internet operating system (IOS), a framework for middleware-driven dynamic application reconfiguration. Our approach requires minimal code modifications and enables transparent middleware- triggered reconfiguration. Experimental results using a two-dimensional data parallel program that has a regular communication structure demonstrate the usefulness of malleability.","PeriodicalId":278535,"journal":{"name":"Seventh IEEE International Symposium on Cluster Computing and the Grid (CCGrid '07)","volume":"112 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122938444","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}
{"title":"Design and Implementation of a Middleware for Data Storage in Opportunistic Grids","authors":"R. Camargo, Fabio Kon","doi":"10.1109/CCGRID.2007.37","DOIUrl":"https://doi.org/10.1109/CCGRID.2007.37","url":null,"abstract":"Shared machines in opportunistic grids typically have large quantities of unused disk space. These resources could be used to store application and checkpointing data when the machines are idle, allowing those machines to share not only computational cycles, but also disk space. In this paper, we present the design and implementation of OppStore, a middleware that provides reliable distributed data storage using the free disk space from shared grid machines. The system utilizes a two-level peer-to-peer organization to connect grid machines in a scalable and fault- tolerant way. Finally, we use the concept of virtual ids to deal with resource heterogeneity, enabling heterogeneity- aware load-balancing selection of storage sites.","PeriodicalId":278535,"journal":{"name":"Seventh IEEE International Symposium on Cluster Computing and the Grid (CCGrid '07)","volume":"142 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116581377","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}