Recent efforts to federate computation and communication resources across organizational boundaries face a challenge in establishing the policies by which one organization's users can access resources in other organizations. This paper describes an approach to defining, communicating, analyzing, and enforcing resource allocation policies in this new setting. Our approach was designed to address the needs of Planet Lab, but we demonstrate through a range of examples that it is general enough to accommodate a diverse collection of computing facilities. Our policy engine is implemented in a specific tool chain, called {tt sfatables}, that is patterned after the {tt iptables} mechanism used to define packet processing policies for network traffic. The interface to our policy engine thus uses the familiar paradigm of a {tt firewall} and provides a flexible interface for resource owners to specify access policies for their resources. Our implementation makes it possible to precisely document policies, query, and analyze them.
{"title":"sfatables: A Firewall-like Policy Engine for Federated Systems","authors":"S. Bhatia, A. Bavier, L. Peterson, Soner Sevinc","doi":"10.1109/ICDCS.2011.58","DOIUrl":"https://doi.org/10.1109/ICDCS.2011.58","url":null,"abstract":"Recent efforts to federate computation and communication resources across organizational boundaries face a challenge in establishing the policies by which one organization's users can access resources in other organizations. This paper describes an approach to defining, communicating, analyzing, and enforcing resource allocation policies in this new setting. Our approach was designed to address the needs of Planet Lab, but we demonstrate through a range of examples that it is general enough to accommodate a diverse collection of computing facilities. Our policy engine is implemented in a specific tool chain, called {tt sfatables}, that is patterned after the {tt iptables} mechanism used to define packet processing policies for network traffic. The interface to our policy engine thus uses the familiar paradigm of a {tt firewall} and provides a flexible interface for resource owners to specify access policies for their resources. Our implementation makes it possible to precisely document policies, query, and analyze them.","PeriodicalId":6300,"journal":{"name":"2012 IEEE 32nd International Conference on Distributed Computing Systems","volume":"3 2 1","pages":"467-476"},"PeriodicalIF":0.0,"publicationDate":"2011-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77476398","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}
Most existing research in disk power management has focused on exploiting idle periods of disks. Both hardware power-saving mechanisms (such as spin-down disks and multi-speed disks) and complementary software strategies (such as code and data layout transformations to increase the length of idle periods) have been explored. However, while hardware power-saving mechanisms cannot handle short idle periods of high-performance parallel applications, prior code/data reorganization strategies typically require extensive code modifications. In this paper, we propose and evaluate a compiler-directed data access (I/O call) scheduling framework for saving disk energy, which groups as many data requests as possible in a shorter period, thus creating longer disk idle periods for improving the effectiveness of hardware power-saving mechanisms. As compared to prior software based efforts, it requires no code or data restructuring. We evaluate our approach using six application programs in a cluster-based simulation environment. The experimental results show that it improves the effectiveness of both spin-down disks and multi-speed disks with doubled power savings on average.
{"title":"Software-Directed Data Access Scheduling for Reducing Disk Energy Consumption","authors":"Yuanrui Zhang, Jun Liu, M. Kandemir","doi":"10.1145/1996130.1996175","DOIUrl":"https://doi.org/10.1145/1996130.1996175","url":null,"abstract":"Most existing research in disk power management has focused on exploiting idle periods of disks. Both hardware power-saving mechanisms (such as spin-down disks and multi-speed disks) and complementary software strategies (such as code and data layout transformations to increase the length of idle periods) have been explored. However, while hardware power-saving mechanisms cannot handle short idle periods of high-performance parallel applications, prior code/data reorganization strategies typically require extensive code modifications. In this paper, we propose and evaluate a compiler-directed data access (I/O call) scheduling framework for saving disk energy, which groups as many data requests as possible in a shorter period, thus creating longer disk idle periods for improving the effectiveness of hardware power-saving mechanisms. As compared to prior software based efforts, it requires no code or data restructuring. We evaluate our approach using six application programs in a cluster-based simulation environment. The experimental results show that it improves the effectiveness of both spin-down disks and multi-speed disks with doubled power savings on average.","PeriodicalId":6300,"journal":{"name":"2012 IEEE 32nd International Conference on Distributed Computing Systems","volume":"17 1","pages":"596-605"},"PeriodicalIF":0.0,"publicationDate":"2011-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86005351","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}
The emergence of applications producing continuous high-frequency data streams has brought forth a large body of research in the area of distributed stream processing. In presence of high volumes of data, efforts have primarily concentrated on providing approximate aggregate or top-k type results. Scalable solutions for providing answers to window join queries in distributed stream processing systems have received limited attention to date. We provide a solution for the window join in a distributed stream processing system which features reduced inter-node communications achieved through automatic throughput handling based on resource availability. Our approach is based on incrementally updated discrete Fourier transforms (DFTs). Furthermore, we provide formulae for computing DFT compression factors in order to achieve information reduction. We perform WAN-based prototype experiments to ascertain the viability and establish the effectiveness of our method. Our experimental results reveal that our method scales in terms of throughput and error rates, achieving sub-linear message complexity in domains that exhibit a geographic skew in the joining attributes.
{"title":"Approximate Data Stream Joins in Distributed Systems","authors":"V. Kriakov, A. Delis, G. Kollios","doi":"10.1109/ICDCS.2007.104","DOIUrl":"https://doi.org/10.1109/ICDCS.2007.104","url":null,"abstract":"The emergence of applications producing continuous high-frequency data streams has brought forth a large body of research in the area of distributed stream processing. In presence of high volumes of data, efforts have primarily concentrated on providing approximate aggregate or top-k type results. Scalable solutions for providing answers to window join queries in distributed stream processing systems have received limited attention to date. We provide a solution for the window join in a distributed stream processing system which features reduced inter-node communications achieved through automatic throughput handling based on resource availability. Our approach is based on incrementally updated discrete Fourier transforms (DFTs). Furthermore, we provide formulae for computing DFT compression factors in order to achieve information reduction. We perform WAN-based prototype experiments to ascertain the viability and establish the effectiveness of our method. Our experimental results reveal that our method scales in terms of throughput and error rates, achieving sub-linear message complexity in domains that exhibit a geographic skew in the joining attributes.","PeriodicalId":6300,"journal":{"name":"2012 IEEE 32nd International Conference on Distributed Computing Systems","volume":"4 1","pages":"5"},"PeriodicalIF":0.0,"publicationDate":"2007-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76021237","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}
Summary form only given. Grid computing is increasingly being viewed as the next phase of distributed computing. Built on pervasive Internet standards, grid computing enables organizations to share computing and information resources across department and organizational boundaries in a secure, highly efficient manner. Grid computing originates in eScience and its early development was driven to a large extent by the requirements of large-scale computing and efficient sharing of huge datasets. eBusiness requirements led to the adoption of emerging Web services technologies - initially developed for distributed business application integration. Therefore grid computing can be applied to enterprise computing within and across organizations and pave the way for utility computing. I present major Grid computing projects for both eScience and eBusiness in Japan (including NaReGI and Business Grid) and several key Grid products and applications (including CyberGRIP and Resource Coordinator both developed by Fujitsu). The Global Grid Forum (GGF) is leading the standardization of grid computing. In particular, GGF has developed the Open Grid Services Architecture (OGSA) and is working throughout the industry to champion this "architectural blueprint" and the associated specifications that will enable the pervasive adoption of grid computing for eBusiness and eScience worldwide
{"title":"eScience Meets eBusiness: Blueprint for Next Generation Grid Computing","authors":"Hiromu Hayashi","doi":"10.1109/ICDCS.2005.33","DOIUrl":"https://doi.org/10.1109/ICDCS.2005.33","url":null,"abstract":"Summary form only given. Grid computing is increasingly being viewed as the next phase of distributed computing. Built on pervasive Internet standards, grid computing enables organizations to share computing and information resources across department and organizational boundaries in a secure, highly efficient manner. Grid computing originates in eScience and its early development was driven to a large extent by the requirements of large-scale computing and efficient sharing of huge datasets. eBusiness requirements led to the adoption of emerging Web services technologies - initially developed for distributed business application integration. Therefore grid computing can be applied to enterprise computing within and across organizations and pave the way for utility computing. I present major Grid computing projects for both eScience and eBusiness in Japan (including NaReGI and Business Grid) and several key Grid products and applications (including CyberGRIP and Resource Coordinator both developed by Fujitsu). The Global Grid Forum (GGF) is leading the standardization of grid computing. In particular, GGF has developed the Open Grid Services Architecture (OGSA) and is working throughout the industry to champion this \"architectural blueprint\" and the associated specifications that will enable the pervasive adoption of grid computing for eBusiness and eScience worldwide","PeriodicalId":6300,"journal":{"name":"2012 IEEE 32nd International Conference on Distributed Computing Systems","volume":"16 1","pages":"529"},"PeriodicalIF":0.0,"publicationDate":"2005-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73551715","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}
Summary form only given. Networks of intelligent sensors that are distributed through the physical world will revolutionize practices in the life sciences, civil engineering, manufacturing, security, agriculture, ubiquitous computing, and many other areas. They also present an opportunity and a need to explore distributed algorithms that are wedded to the noisy, localized, time varying physical world. Bandwidth, storage, and energy limitations make in-network processing essential - within the node and among collections of nodes. The algorithms should be resource efficient, but also deal with noise, uncertainty and dynamically changing connectivity. A broad research community has been exploring these issues in the context of TinyOS and the Berkeley motes. This talk will highlight novel distributed algorithms coming out of these efforts and discuss issues in making such networks robust and programmable
{"title":"Distributed Computation in the Physical World","authors":"D. Culler","doi":"10.1109/ICDCS.2005.25","DOIUrl":"https://doi.org/10.1109/ICDCS.2005.25","url":null,"abstract":"Summary form only given. Networks of intelligent sensors that are distributed through the physical world will revolutionize practices in the life sciences, civil engineering, manufacturing, security, agriculture, ubiquitous computing, and many other areas. They also present an opportunity and a need to explore distributed algorithms that are wedded to the noisy, localized, time varying physical world. Bandwidth, storage, and energy limitations make in-network processing essential - within the node and among collections of nodes. The algorithms should be resource efficient, but also deal with noise, uncertainty and dynamically changing connectivity. A broad research community has been exploring these issues in the context of TinyOS and the Berkeley motes. This talk will highlight novel distributed algorithms coming out of these efforts and discuss issues in making such networks robust and programmable","PeriodicalId":6300,"journal":{"name":"2012 IEEE 32nd International Conference on Distributed Computing Systems","volume":"33 1","pages":"3"},"PeriodicalIF":0.0,"publicationDate":"2005-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80594784","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}
Pub Date : 1999-05-31DOI: 10.1109/ICDCS.1999.776538
J. Jönsson
The application of optimal search strategies to scheduling for distributed real-time systems is, in general, plagued by an inherent computational complexity. This has effectively prevented the integration of strategies such as branch-and-bound (B&B) in scheduling frameworks and tools used in practice today. To show that optimal scheduling is, in fact, a viable alternative for many real-time scheduling scenarios, we propose an approach that can reduce the average search complexity to levels comparable with that of a polynomial-time heuristic. Our approach is based on making intelligent choices in the selection of strategies for search tree vertex traversal and task deadline assignment. More specifically, we conjecture that effective complexity reduction is achieved by (i) traversing vertices in the search tree in a depth-first fashion and (ii) assigning local task deadlines that are non-overlapping fractions of the application end-to-end deadline. Through an extensive experimental study, we find that our approach contribute to reducing the average search complexity by several orders of magnitude for a frequently-used class of distributed real-time applications.
{"title":"Effective complexity reduction for optimal scheduling of distributed real-time applications","authors":"J. Jönsson","doi":"10.1109/ICDCS.1999.776538","DOIUrl":"https://doi.org/10.1109/ICDCS.1999.776538","url":null,"abstract":"The application of optimal search strategies to scheduling for distributed real-time systems is, in general, plagued by an inherent computational complexity. This has effectively prevented the integration of strategies such as branch-and-bound (B&B) in scheduling frameworks and tools used in practice today. To show that optimal scheduling is, in fact, a viable alternative for many real-time scheduling scenarios, we propose an approach that can reduce the average search complexity to levels comparable with that of a polynomial-time heuristic. Our approach is based on making intelligent choices in the selection of strategies for search tree vertex traversal and task deadline assignment. More specifically, we conjecture that effective complexity reduction is achieved by (i) traversing vertices in the search tree in a depth-first fashion and (ii) assigning local task deadlines that are non-overlapping fractions of the application end-to-end deadline. Through an extensive experimental study, we find that our approach contribute to reducing the average search complexity by several orders of magnitude for a frequently-used class of distributed real-time applications.","PeriodicalId":6300,"journal":{"name":"2012 IEEE 32nd International Conference on Distributed Computing Systems","volume":"64 1 1","pages":"360-369"},"PeriodicalIF":0.0,"publicationDate":"1999-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87744524","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}
Pub Date : 1997-01-01DOI: 10.1109/ICDCS.1997.597851
I. Rhee, S. Y. Cheung, P. Hutto, V. Sunderam
{"title":"Group Communication Support for Distributed Multimedia and CSCW Systems","authors":"I. Rhee, S. Y. Cheung, P. Hutto, V. Sunderam","doi":"10.1109/ICDCS.1997.597851","DOIUrl":"https://doi.org/10.1109/ICDCS.1997.597851","url":null,"abstract":"","PeriodicalId":6300,"journal":{"name":"2012 IEEE 32nd International Conference on Distributed Computing Systems","volume":"66 1","pages":"43-50"},"PeriodicalIF":0.0,"publicationDate":"1997-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91226269","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}
Pub Date : 1996-01-01DOI: 10.1109/ICDCS.1996.508018
Yew-Huey Liu, P. Dantzig, C. Wu, J. Challenger, L. Ni
{"title":"A Distributed Scalable Web Server and Its Program Visualization in Multiple Platforms","authors":"Yew-Huey Liu, P. Dantzig, C. Wu, J. Challenger, L. Ni","doi":"10.1109/ICDCS.1996.508018","DOIUrl":"https://doi.org/10.1109/ICDCS.1996.508018","url":null,"abstract":"","PeriodicalId":6300,"journal":{"name":"2012 IEEE 32nd International Conference on Distributed Computing Systems","volume":"10 1","pages":"665-672"},"PeriodicalIF":0.0,"publicationDate":"1996-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88898596","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}
Pub Date : 1995-05-30DOI: 10.1109/ICDCS.1995.500018
A. Mok, C. Heitmeyer, K. Jeffay, Michael B. Jones, C. D. Locke, R. Rajkumar
Summary form only given, as follows. Static models are not appropriate for next-generation distributed real-time applications that are likely to be adaptive in nature, (for example, to provide a high degree of fault tolerance). During the last few years, the real-time systems community has started to counter this criticism by extending traditional work to cover newer application domains, The central problem remains, however, that the concept of adaptivity is often domain-specific and sometimes ill-defined in the context of bringing distributed real-time systems concept into better focus. Accordingly, be it resolved that future distributed embedded and real-time applications will be adaptive and that meanings, challenges and research paradigms await discovery. The charge to the panel is to defend (or to dismiss as fluff) the above resolution.
{"title":"Future Distributed Embedded and Real-Time Applications Will Be Adaptive: Meanings, Challenges and Research Paradigms (Panel)","authors":"A. Mok, C. Heitmeyer, K. Jeffay, Michael B. Jones, C. D. Locke, R. Rajkumar","doi":"10.1109/ICDCS.1995.500018","DOIUrl":"https://doi.org/10.1109/ICDCS.1995.500018","url":null,"abstract":"Summary form only given, as follows. Static models are not appropriate for next-generation distributed real-time applications that are likely to be adaptive in nature, (for example, to provide a high degree of fault tolerance). During the last few years, the real-time systems community has started to counter this criticism by extending traditional work to cover newer application domains, The central problem remains, however, that the concept of adaptivity is often domain-specific and sometimes ill-defined in the context of bringing distributed real-time systems concept into better focus. Accordingly, be it resolved that future distributed embedded and real-time applications will be adaptive and that meanings, challenges and research paradigms await discovery. The charge to the panel is to defend (or to dismiss as fluff) the above resolution.","PeriodicalId":6300,"journal":{"name":"2012 IEEE 32nd International Conference on Distributed Computing Systems","volume":"26 1","pages":"182-184"},"PeriodicalIF":0.0,"publicationDate":"1995-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86053733","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}
Pub Date : 1995-01-01DOI: 10.1109/ICDCS.1995.10001
Tom Rodden, Paul Dourish, L. Fahlén, Chris Greenhalgh, A. Prakash, John Riedl
{"title":"Computer Supported Cooperative Work: New Challenges or Old Problems (Panel)","authors":"Tom Rodden, Paul Dourish, L. Fahlén, Chris Greenhalgh, A. Prakash, John Riedl","doi":"10.1109/ICDCS.1995.10001","DOIUrl":"https://doi.org/10.1109/ICDCS.1995.10001","url":null,"abstract":"","PeriodicalId":6300,"journal":{"name":"2012 IEEE 32nd International Conference on Distributed Computing Systems","volume":"64 1","pages":"180-181"},"PeriodicalIF":0.0,"publicationDate":"1995-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77942964","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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