In the last few years, highly distributed, heterogeneous and dynamic environments have become usual contexts for scientific and business domains. In this work, we consider query scheduling over a grid-enabled distributed database, where the data may be partially or totally replicated into the component sites. Although there have been some previous proposals for query scheduling in distributed databases, they did not consider site reputation, which is important in autonomous and heterogeneous distributed systems. We propose a reputation-based election-inspired query scheduling strategy. Sites are autonomous concerning candidacy for answering queries, in which case they must report an expected response time commitment to those queries. A reputation system is used for ranking sites on their response time estimations. Commitment information and subsequent outcome allows the reputation-based election-inspired approach to improve the overall mean response time of the system. We compare it experimentally with other distributed schedulers to show that the use of reputation and elections improves performance in heterogeneous autonomous environments.
{"title":"Runtime Estimations, Reputation and Elections for Top Performing Distributed Query Scheduling","authors":"Rogério Luís de Carvalho Costa, P. Furtado","doi":"10.1109/CCGRID.2009.34","DOIUrl":"https://doi.org/10.1109/CCGRID.2009.34","url":null,"abstract":"In the last few years, highly distributed, heterogeneous and dynamic environments have become usual contexts for scientific and business domains. In this work, we consider query scheduling over a grid-enabled distributed database, where the data may be partially or totally replicated into the component sites. Although there have been some previous proposals for query scheduling in distributed databases, they did not consider site reputation, which is important in autonomous and heterogeneous distributed systems. We propose a reputation-based election-inspired query scheduling strategy. Sites are autonomous concerning candidacy for answering queries, in which case they must report an expected response time commitment to those queries. A reputation system is used for ranking sites on their response time estimations. Commitment information and subsequent outcome allows the reputation-based election-inspired approach to improve the overall mean response time of the system. We compare it experimentally with other distributed schedulers to show that the use of reputation and elections improves performance in heterogeneous autonomous environments.","PeriodicalId":118263,"journal":{"name":"2009 9th IEEE/ACM International Symposium on Cluster Computing and the Grid","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-05-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128997330","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}
Free riders in Peer-to-peer (P2P) networks are the nodes only consume services but provide little or nothing. They seriously degrade the fault-tolerance and scalability of the P2P networks. A Cluster-Based Incentive Mechanism (CBIM) is proposed in this paper to prevent free riding problem in P2P networks regardless of their topologies and service diversity. Nodes with asymmetric interests are organized in clusters that consist of service exchange rings. A node in a ring can receive a service from its predecessor by providing a requested service to its successor. Free riders can not complete their requested services since a ring will collapse once free riding is detected. We firstly identify five design requirements, namely, adaptability, service diversity, reward and penalty, altruism and performance. Second, we describe the cluster formation process and a graph theory based ring identification algorithm. Finally, we describe our coarse-grained probability-based free riding prevention algorithm. Through a set of simulations, we find that the CBIM is feasible and outperforms other incentive mechanisms.
{"title":"Towards a Cluster Based Incentive Mechanism for P2P Networks","authors":"Kan Zhang, N. Antonopoulos","doi":"10.1109/CCGRID.2009.92","DOIUrl":"https://doi.org/10.1109/CCGRID.2009.92","url":null,"abstract":"Free riders in Peer-to-peer (P2P) networks are the nodes only consume services but provide little or nothing. They seriously degrade the fault-tolerance and scalability of the P2P networks. A Cluster-Based Incentive Mechanism (CBIM) is proposed in this paper to prevent free riding problem in P2P networks regardless of their topologies and service diversity. Nodes with asymmetric interests are organized in clusters that consist of service exchange rings. A node in a ring can receive a service from its predecessor by providing a requested service to its successor. Free riders can not complete their requested services since a ring will collapse once free riding is detected. We firstly identify five design requirements, namely, adaptability, service diversity, reward and penalty, altruism and performance. Second, we describe the cluster formation process and a graph theory based ring identification algorithm. Finally, we describe our coarse-grained probability-based free riding prevention algorithm. Through a set of simulations, we find that the CBIM is feasible and outperforms other incentive mechanisms.","PeriodicalId":118263,"journal":{"name":"2009 9th IEEE/ACM International Symposium on Cluster Computing and the Grid","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-05-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124605647","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}
Dongmei Yue, Ruisheng Zhang, Chen Zhao, Ruipeng Wei, Lian Li
E-Research aims to facilitate collaboration across time and distance. Researchers need techniques and tools to support their collaborative work. Groupware is one technique that supports groups of people engaging in a common task over the network. Besides, it is also one of the most effective means to solve the collaboration problem. Existing groupware projects provide fixed functions such as messaging, conferen- cing, electronic meeting, document management, document collaboration and so on. However, they put limited emphasis on scientists’ research work in their specific fields. This paper proposes a groupware environment, and tries to give a domain-specific group editor to facilitate researchers’ collaboration. The groupware implements a visual molecule group editor for chemists to co-edit molecular structures over network. And it has a plug-in extensible architecture intending to easily integrate other tools which is useful for chemists’ collaboration. The idea given in this paper could be a possible solution to facilitate chemists’ collaborative research work.
{"title":"Domain-Specific Groupware Environment for E-research on Chemistry","authors":"Dongmei Yue, Ruisheng Zhang, Chen Zhao, Ruipeng Wei, Lian Li","doi":"10.1109/CCGRID.2009.45","DOIUrl":"https://doi.org/10.1109/CCGRID.2009.45","url":null,"abstract":"E-Research aims to facilitate collaboration across time and distance. Researchers need techniques and tools to support their collaborative work. Groupware is one technique that supports groups of people engaging in a common task over the network. Besides, it is also one of the most effective means to solve the collaboration problem. Existing groupware projects provide fixed functions such as messaging, conferen- cing, electronic meeting, document management, document collaboration and so on. However, they put limited emphasis on scientists’ research work in their specific fields. This paper proposes a groupware environment, and tries to give a domain-specific group editor to facilitate researchers’ collaboration. The groupware implements a visual molecule group editor for chemists to co-edit molecular structures over network. And it has a plug-in extensible architecture intending to easily integrate other tools which is useful for chemists’ collaboration. The idea given in this paper could be a possible solution to facilitate chemists’ collaborative research work.","PeriodicalId":118263,"journal":{"name":"2009 9th IEEE/ACM International Symposium on Cluster Computing and the Grid","volume":"105 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-05-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124762812","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}
Identifying websites hosting malicious code is a priority for helping protect consumers using the web and for the collection of malicious code for analysis by malware researchers. We have been running an InternetNZ sponsored study where homepages of almost all New Zealand Web servers are scanned on a regular basis by a set of client honeypots. This paper reflects upon our experience of running moderate scale scans over a period of several months manually and identifies some requirements for automation of such a system using workflow and related middleware.
{"title":"Automating Malware Scanning Using Workflows","authors":"D. Stirling, I. Welch, P. Komisarczuk, C. Seifert","doi":"10.1109/CCGRID.2009.90","DOIUrl":"https://doi.org/10.1109/CCGRID.2009.90","url":null,"abstract":"Identifying websites hosting malicious code is a priority for helping protect consumers using the web and for the collection of malicious code for analysis by malware researchers. We have been running an InternetNZ sponsored study where homepages of almost all New Zealand Web servers are scanned on a regular basis by a set of client honeypots. This paper reflects upon our experience of running moderate scale scans over a period of several months manually and identifies some requirements for automation of such a system using workflow and related middleware.","PeriodicalId":118263,"journal":{"name":"2009 9th IEEE/ACM International Symposium on Cluster Computing and the Grid","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-05-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132022949","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}
Gregory P. Johnson, S. Mock, Brandt M. Westing, Gregory S. Johnson
Scientific visualization is the process of transforming raw numeric data into a visual form, and is a key element of computational science. While many tools exist, they are unnecessarily difficult to use. This complexity increases time to insight and inhibits casual inquiry. The complexity derives from the need to support arbitrarily formatted data and many visualization algorithms. EnVision addresses both sources of complexity. Its design is predicated on two key insights. First, though the number of data file formats is unbounded, the structure of any one can be described using a small number of parameters. Second, the set of visualization algorithms applicable to a given type of data is small, and the subset used within a specific scientific discipline is smaller. EnVision utilizes domain-specific knowledge and user-directed semi-automation to dramatically simplify data importation and visualization algorithm selection. Its web-based interface facilitates access to remote hardware resources and provides a collaborative visualization environment.
{"title":"EnVision: A Web-Based Tool for Scientific Visualization","authors":"Gregory P. Johnson, S. Mock, Brandt M. Westing, Gregory S. Johnson","doi":"10.1109/CCGRID.2009.80","DOIUrl":"https://doi.org/10.1109/CCGRID.2009.80","url":null,"abstract":"Scientific visualization is the process of transforming raw numeric data into a visual form, and is a key element of computational science. While many tools exist, they are unnecessarily difficult to use. This complexity increases time to insight and inhibits casual inquiry. The complexity derives from the need to support arbitrarily formatted data and many visualization algorithms. EnVision addresses both sources of complexity. Its design is predicated on two key insights. First, though the number of data file formats is unbounded, the structure of any one can be described using a small number of parameters. Second, the set of visualization algorithms applicable to a given type of data is small, and the subset used within a specific scientific discipline is smaller. EnVision utilizes domain-specific knowledge and user-directed semi-automation to dramatically simplify data importation and visualization algorithm selection. Its web-based interface facilitates access to remote hardware resources and provides a collaborative visualization environment.","PeriodicalId":118263,"journal":{"name":"2009 9th IEEE/ACM International Symposium on Cluster Computing and the Grid","volume":"62 3-4","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-05-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131496677","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}
In a cluster of multiple processors or cpu-cores, many processes may run on each compute node. Each process tends to issue contiguous I/O requests for snapshot, checkpointing or so, however, if large number of processes enter the I/O phase at the same time, the requests from the same process may be interrupted by the requests of other processes. Then, the I/O nodes receive these requests as non-contiguous way. This interleaved access pattern causes performance degradation in parallel file systems. In order to overcome the problem, we have designed the Gather-Arrange-Scatter (GAS) I/O architecture, for optimizing the parallel write performance. The GAS is an architecture for capturing write operations, buffering them in the memory, and scheduling them to reduce I/O cost at I/O nodes. The scheduling is done per compute node, and the requests are sent to the remote disks in parallel. In this paper, after introducing the GAS architecture in detail, its efficiency and scalability are evaluated using the NAS Parallel Benchmark BTIO. GAS is 5.2%faster than ROMIO collective I/O on PVFS2 in BTIO with 16 nodes/64 processes, and 34.9% faster than MPI noncollective I/O in the same configuration.
{"title":"Improving Parallel Write by Node-Level Request Scheduling","authors":"Kazuki Ohta, Hiroya Matsuba, Y. Ishikawa","doi":"10.1109/CCGRID.2009.71","DOIUrl":"https://doi.org/10.1109/CCGRID.2009.71","url":null,"abstract":"In a cluster of multiple processors or cpu-cores, many processes may run on each compute node. Each process tends to issue contiguous I/O requests for snapshot, checkpointing or so, however, if large number of processes enter the I/O phase at the same time, the requests from the same process may be interrupted by the requests of other processes. Then, the I/O nodes receive these requests as non-contiguous way. This interleaved access pattern causes performance degradation in parallel file systems. In order to overcome the problem, we have designed the Gather-Arrange-Scatter (GAS) I/O architecture, for optimizing the parallel write performance. The GAS is an architecture for capturing write operations, buffering them in the memory, and scheduling them to reduce I/O cost at I/O nodes. The scheduling is done per compute node, and the requests are sent to the remote disks in parallel. In this paper, after introducing the GAS architecture in detail, its efficiency and scalability are evaluated using the NAS Parallel Benchmark BTIO. GAS is 5.2%faster than ROMIO collective I/O on PVFS2 in BTIO with 16 nodes/64 processes, and 34.9% faster than MPI noncollective I/O in the same configuration.","PeriodicalId":118263,"journal":{"name":"2009 9th IEEE/ACM International Symposium on Cluster Computing and the Grid","volume":"58 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-05-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124637169","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}
Interactive distributed visualization is an emerging technology with numerous applications. However, many of the present approaches of interactive distributed visualization are based on the traditional polygonal processing graphics pipeline. Our research is centred on investigating an alternative method using Image-Based Rendering (IBR) which uses (multiple) images of the scene instead of a 3D geometrical representation. A key advantage to the use of IBR techniques is that the bandwidth required is independent of scene complexity and is therefore predictable given knowledge of the desired final image resolution. In this paper, we describe our IBR based interactive distributed visualization platform involving Light Field rendering and present results which indicate the scalability of our approach to accommodate multiple collaborative users. To our knowledge this is the first system to demonstrate deployment of interactive Light Field rendering to large numbers of distributed users.
{"title":"Distributed Collaborative Visualization Using Light Field Rendering","authors":"Asma Al-Saidi, N. J. Avis, I. Grimstead, O. Rana","doi":"10.1109/CCGRID.2009.79","DOIUrl":"https://doi.org/10.1109/CCGRID.2009.79","url":null,"abstract":"Interactive distributed visualization is an emerging technology with numerous applications. However, many of the present approaches of interactive distributed visualization are based on the traditional polygonal processing graphics pipeline. Our research is centred on investigating an alternative method using Image-Based Rendering (IBR) which uses (multiple) images of the scene instead of a 3D geometrical representation. A key advantage to the use of IBR techniques is that the bandwidth required is independent of scene complexity and is therefore predictable given knowledge of the desired final image resolution. In this paper, we describe our IBR based interactive distributed visualization platform involving Light Field rendering and present results which indicate the scalability of our approach to accommodate multiple collaborative users. To our knowledge this is the first system to demonstrate deployment of interactive Light Field rendering to large numbers of distributed users.","PeriodicalId":118263,"journal":{"name":"2009 9th IEEE/ACM International Symposium on Cluster Computing and the Grid","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-05-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124775648","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}
Rubing Duan, F. Nadeem, Jie Wang, Yun Zhang, R. Prodan, T. Fahringer
Grid schedulers require individual activity performance predictions to map workflow activities on different Grid sites. The effectiveness of the scheduling systems is hampered by inaccurate predictions due to the inability of existing predictors to effectively model the dynamic and heterogeneous nature of Grid resources, or the wide range of problem sizes and runtime arguments. To address this deficiency, we propose a hybrid Bayesian-neural network approach to dynamically model and predict the execution time of activities in real workflow applications. Bayesian network is used for a high-level representation of activities performance probability distribution against different factors affecting the performance. The important attributes are dynamically selected by the Bayesian network and fed into a radial basis function neural network to make further predictions. Our approach is generic to any type of scientific applications, and flexible to import expert knowledge to further improve accuracies. Experimental results for activities from three realworld workflow applications are presented to show effectivenessof our approach.
{"title":"A Hybrid Intelligent Method for Performance Modeling and Prediction of Workflow Activities in Grids","authors":"Rubing Duan, F. Nadeem, Jie Wang, Yun Zhang, R. Prodan, T. Fahringer","doi":"10.1109/CCGRID.2009.58","DOIUrl":"https://doi.org/10.1109/CCGRID.2009.58","url":null,"abstract":"Grid schedulers require individual activity performance predictions to map workflow activities on different Grid sites. The effectiveness of the scheduling systems is hampered by inaccurate predictions due to the inability of existing predictors to effectively model the dynamic and heterogeneous nature of Grid resources, or the wide range of problem sizes and runtime arguments. To address this deficiency, we propose a hybrid Bayesian-neural network approach to dynamically model and predict the execution time of activities in real workflow applications. Bayesian network is used for a high-level representation of activities performance probability distribution against different factors affecting the performance. The important attributes are dynamically selected by the Bayesian network and fed into a radial basis function neural network to make further predictions. Our approach is generic to any type of scientific applications, and flexible to import expert knowledge to further improve accuracies. Experimental results for activities from three realworld workflow applications are presented to show effectivenessof our approach.","PeriodicalId":118263,"journal":{"name":"2009 9th IEEE/ACM International Symposium on Cluster Computing and the Grid","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-05-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124849728","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}
P. Chen, Jyh-Biau Chang, Yi-Chang Zhuang, C. Shieh, Tyng-Yeu Liang
Grid data sharing systems usually provide a data-intensive application with either a pre-staging mechanism or an on-demand access mechanism to access shared data. Pre-staging systems simultaneously download an entire shared file from multiple data sources even when only a tiny file fragment is required. Such systems consume unnecessary data transmission time and storage space. On-demand access systems, on the other hand, download only the required fragments from a single data source. Such systems unfortunately do not fully exploit available network bandwidth. This paper presents a data sharing system, designated as the On-Demand data Co-Allocation (ODCA). ODCA facilitates an unmodified legacy applications to transparently access shared data by using native I/O system calls. ODCA transfers only the necessary fragments on user demand, thereby reducing data transmission time, avoiding wasted network bandwidth and wasted storage space. Moreover, ODCA reduces data waiting time by downloading the file fragments from multiple data sources. Experimental results show ODCA successfully reduces turnaround time in data-intensive applications.
{"title":"Memory-Mapped File Approach for On-Demand Data Co-allocation on Grids","authors":"P. Chen, Jyh-Biau Chang, Yi-Chang Zhuang, C. Shieh, Tyng-Yeu Liang","doi":"10.1109/CCGRID.2009.22","DOIUrl":"https://doi.org/10.1109/CCGRID.2009.22","url":null,"abstract":"Grid data sharing systems usually provide a data-intensive application with either a pre-staging mechanism or an on-demand access mechanism to access shared data. Pre-staging systems simultaneously download an entire shared file from multiple data sources even when only a tiny file fragment is required. Such systems consume unnecessary data transmission time and storage space. On-demand access systems, on the other hand, download only the required fragments from a single data source. Such systems unfortunately do not fully exploit available network bandwidth. This paper presents a data sharing system, designated as the On-Demand data Co-Allocation (ODCA). ODCA facilitates an unmodified legacy applications to transparently access shared data by using native I/O system calls. ODCA transfers only the necessary fragments on user demand, thereby reducing data transmission time, avoiding wasted network bandwidth and wasted storage space. Moreover, ODCA reduces data waiting time by downloading the file fragments from multiple data sources. Experimental results show ODCA successfully reduces turnaround time in data-intensive applications.","PeriodicalId":118263,"journal":{"name":"2009 9th IEEE/ACM International Symposium on Cluster Computing and the Grid","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-05-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131972267","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}
A. Barker, Jano van Hemert, R. Baldock, M. Atkinson
Within the context of the EU Design Study Developmental Gene Expression Map, we identify a set of challenges when facilitating collaborative research on early human embryo development. These challenges bring forth requirements, for which we have identified solutions and technology. We summarise our solutions and demonstrate how they integrate to form an e-infrastructure to support collaborative research in this area of developmental biology.
{"title":"An E-infrastructure to Support Collaborative Embryo Research","authors":"A. Barker, Jano van Hemert, R. Baldock, M. Atkinson","doi":"10.1109/CCGRID.2009.78","DOIUrl":"https://doi.org/10.1109/CCGRID.2009.78","url":null,"abstract":"Within the context of the EU Design Study Developmental Gene Expression Map, we identify a set of challenges when facilitating collaborative research on early human embryo development. These challenges bring forth requirements, for which we have identified solutions and technology. We summarise our solutions and demonstrate how they integrate to form an e-infrastructure to support collaborative research in this area of developmental biology.","PeriodicalId":118263,"journal":{"name":"2009 9th IEEE/ACM International Symposium on Cluster Computing and the Grid","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-05-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127850928","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}
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