Pub Date : 2001-08-07DOI: 10.1109/HPDC.2001.945217
Michael Karo, Christopher Dwan, John L. Freeman, E. Retzel, J. Weissman, M. Livny
The science of bioinformatics provides researchers with the tools necessary to unravel the mysteries of life and evolution, discover cures for disease, and control the evolution of living organisms. To assist researchers in managing the growing data processing and management demands associated with bioinformatics, we have created a production system that draws upon Grid based technologies to control several aspects of the process. We briefly discuss system architecture, results, and future directions of the project.
{"title":"Applying Grid technologies to bioinformatics","authors":"Michael Karo, Christopher Dwan, John L. Freeman, E. Retzel, J. Weissman, M. Livny","doi":"10.1109/HPDC.2001.945217","DOIUrl":"https://doi.org/10.1109/HPDC.2001.945217","url":null,"abstract":"The science of bioinformatics provides researchers with the tools necessary to unravel the mysteries of life and evolution, discover cures for disease, and control the evolution of living organisms. To assist researchers in managing the growing data processing and management demands associated with bioinformatics, we have created a production system that draws upon Grid based technologies to control several aspects of the process. We briefly discuss system architecture, results, and future directions of the project.","PeriodicalId":304683,"journal":{"name":"Proceedings 10th IEEE International Symposium on High Performance Distributed Computing","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2001-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129220925","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 : 2001-08-07DOI: 10.1109/HPDC.2001.945185
D. Royo, L. D. D. Cerio, N. Kapadia, J. Fortes
This paper describes a novel, pipelined resource management architecture for computational grids. The design is based on two key realizations. One is that resource management involves a sequence of tasks that is best handled by a pipeline. As shown in the paper, this approach results in a scalable architecture for decentralized scheduling. The other realization is that static aggregation of resources for improved scheduling is inadequate in wide-area computing environments because the needs of users and jobs change with both, location and time. The described architecture addresses this problem by dynamically aggregating resources in a manner that continuously optimizes system response. This is accomplished by way of an active yellow pages directory that allows aggregation constraints to be (re)defined on the fly. An initial prototype of the active yellow pages service has been deployed in the PUNCH network computing environment. Experiences with the production PUNCH system and preliminary results from controlled experiments indicate that the active yellow pages service performs well.
{"title":"Active yellow pages: a pipelined resource management architecture for wide-area network computing","authors":"D. Royo, L. D. D. Cerio, N. Kapadia, J. Fortes","doi":"10.1109/HPDC.2001.945185","DOIUrl":"https://doi.org/10.1109/HPDC.2001.945185","url":null,"abstract":"This paper describes a novel, pipelined resource management architecture for computational grids. The design is based on two key realizations. One is that resource management involves a sequence of tasks that is best handled by a pipeline. As shown in the paper, this approach results in a scalable architecture for decentralized scheduling. The other realization is that static aggregation of resources for improved scheduling is inadequate in wide-area computing environments because the needs of users and jobs change with both, location and time. The described architecture addresses this problem by dynamically aggregating resources in a manner that continuously optimizes system response. This is accomplished by way of an active yellow pages directory that allows aggregation constraints to be (re)defined on the fly. An initial prototype of the active yellow pages service has been deployed in the PUNCH network computing environment. Experiences with the production PUNCH system and preliminary results from controlled experiments indicate that the active yellow pages service performs well.","PeriodicalId":304683,"journal":{"name":"Proceedings 10th IEEE International Symposium on High Performance Distributed Computing","volume":"336 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2001-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123933709","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 : 2001-08-07DOI: 10.1109/HPDC.2001.945198
Francisco Matias Cuenca-Acuna, Thu D. Nguyen
Considers the use of cooperative caching to manage the memories of cluster-based servers. Over the last several years, a number of researchers have proposed content-aware servers that implement locality-conscious request distribution to address this memory management problem. During this development, it has become conventional wisdom that cooperative caching cannot match the performance of these servers. Unfortunately, while content-aware servers provide very high performance, their request distribution algorithms are typically bound to specific applications. The advantage of building distributed servers on top of a block-based cooperative caching layer is the generality of such a layer; it can be used as a building block for diverse services, ranging from file systems to web servers. In this paper, we reexamine the question of whether a server built on top of a generic block-based cooperative caching algorithm can perform competitively with content-aware servers. Specifically, we compare the performance of a cooperative caching-based Web server against L2S, a highly optimized locality- and load-conscious server. Our results show that, by modifying the replacement policy of traditional cooperative caching algorithms, we can achieve much of the performance provided by locality-conscious servers. Our modification increases network communication to reduce disk accesses, a reasonable trade-off considering the current trend of relative performance between LANs and disks.
{"title":"Cooperative caching middleware for cluster-based servers","authors":"Francisco Matias Cuenca-Acuna, Thu D. Nguyen","doi":"10.1109/HPDC.2001.945198","DOIUrl":"https://doi.org/10.1109/HPDC.2001.945198","url":null,"abstract":"Considers the use of cooperative caching to manage the memories of cluster-based servers. Over the last several years, a number of researchers have proposed content-aware servers that implement locality-conscious request distribution to address this memory management problem. During this development, it has become conventional wisdom that cooperative caching cannot match the performance of these servers. Unfortunately, while content-aware servers provide very high performance, their request distribution algorithms are typically bound to specific applications. The advantage of building distributed servers on top of a block-based cooperative caching layer is the generality of such a layer; it can be used as a building block for diverse services, ranging from file systems to web servers. In this paper, we reexamine the question of whether a server built on top of a generic block-based cooperative caching algorithm can perform competitively with content-aware servers. Specifically, we compare the performance of a cooperative caching-based Web server against L2S, a highly optimized locality- and load-conscious server. Our results show that, by modifying the replacement policy of traditional cooperative caching algorithms, we can achieve much of the performance provided by locality-conscious servers. Our modification increases network communication to reduce disk accesses, a reasonable trade-off considering the current trend of relative performance between LANs and disks.","PeriodicalId":304683,"journal":{"name":"Proceedings 10th IEEE International Symposium on High Performance Distributed Computing","volume":"95 6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2001-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125982395","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 : 2001-08-07DOI: 10.1109/HPDC.2001.945212
B. Toonen, David Ashton, E. Lusk, Ian T Foster, W. Gropp, E. Gabriel, R. Butler, N. Karonis
A variety of projects worldwide are developing what we call "heterogeneous MPI". These MPI implementations are designed to operate on multiple computers, perhaps of different types, ranging in complexity from a set of desktop workstations to several supercomputers connected via a wide area network. These considerations led us to investigate the feasibility of defining a common API that could be used within MPI implementations to access process startup, initialization, monitoring, and control functions provided by an underlying process management system. If various MPI implementations coded to that API, one could then develop multiple "process management" modules that could be reused within different MPI implementations, thus allowing partitioning of effort between different development groups. In pursuit of this goal, we have designed such an API, which we call BNR. The major goals of the BNR interface are outlined.
{"title":"Interfacing parallel jobs to process managers","authors":"B. Toonen, David Ashton, E. Lusk, Ian T Foster, W. Gropp, E. Gabriel, R. Butler, N. Karonis","doi":"10.1109/HPDC.2001.945212","DOIUrl":"https://doi.org/10.1109/HPDC.2001.945212","url":null,"abstract":"A variety of projects worldwide are developing what we call \"heterogeneous MPI\". These MPI implementations are designed to operate on multiple computers, perhaps of different types, ranging in complexity from a set of desktop workstations to several supercomputers connected via a wide area network. These considerations led us to investigate the feasibility of defining a common API that could be used within MPI implementations to access process startup, initialization, monitoring, and control functions provided by an underlying process management system. If various MPI implementations coded to that API, one could then develop multiple \"process management\" modules that could be reused within different MPI implementations, thus allowing partitioning of effort between different development groups. In pursuit of this goal, we have designed such an API, which we call BNR. The major goals of the BNR interface are outlined.","PeriodicalId":304683,"journal":{"name":"Proceedings 10th IEEE International Symposium on High Performance Distributed Computing","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2001-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114799175","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 : 2001-08-07DOI: 10.1109/HPDC.2001.945218
D. M. Swany, R. Wolski
The Logistical Session Layer is a system to enable enhanced functionality to distributed programming systems. The term Logistical refers to the fact that we enhance the traditional client-server model to allow for intermediate systems which are neither. This system generalizes the notion of caches but represents a cleaner architecture in that it explicitly declares itself to be a session layer protocol.
{"title":"The Logistical Session Layer","authors":"D. M. Swany, R. Wolski","doi":"10.1109/HPDC.2001.945218","DOIUrl":"https://doi.org/10.1109/HPDC.2001.945218","url":null,"abstract":"The Logistical Session Layer is a system to enable enhanced functionality to distributed programming systems. The term Logistical refers to the fact that we enhance the traditional client-server model to allow for intermediate systems which are neither. This system generalizes the notion of caches but represents a cleaner architecture in that it explicitly declares itself to be a session layer protocol.","PeriodicalId":304683,"journal":{"name":"Proceedings 10th IEEE International Symposium on High Performance Distributed Computing","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2001-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121991656","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 : 2001-08-07DOI: 10.1109/HPDC.2001.945171
Ada Gavrilovska, K. Schwan, Van Oleson
This paper presents a software architecture for continuously mirroring streaming data received by one node of a cluster-based server to other cluster nodes. The intent is to distribute the load on the server generated by the data's processing and distribution to many clients. This is particularly important when the server not only processes streaming data, but also performs additional processing tasks that heavily depend on current application state. One such task is the preparation of suitable initialization state for thin clients, so that such clients can understand future data events being streamed to them. In particular, when large numbers of thin clients must be initialized at the same time, initialization must be performed without jeopardizing the quality of service offered to regular clients continuing to receive data streams. The mirroring framework presented and evaluated has several novel aspects. First, by performing mirroring at the middleware level, application semantics may be used to reduce mirroring traffic, including filtering events based on their content, by coalescing certain events, or by simply varying mirroring rates according to current application needs concerning the consistencies of mirrored vs. original data. Second, we present an adaptive algorithm that varies mirror consistency and thereby, mirroring overheads in response to changes in clients' request behavior. Third, our framework not only mirrors events, but it can also mirror the new states computed from incoming events, thus enabling dynamic tradeoffs in the communication vs. computation loads imposed on the server node receiving events and on its mirror nodes.
{"title":"Adaptable mirroring in cluster servers","authors":"Ada Gavrilovska, K. Schwan, Van Oleson","doi":"10.1109/HPDC.2001.945171","DOIUrl":"https://doi.org/10.1109/HPDC.2001.945171","url":null,"abstract":"This paper presents a software architecture for continuously mirroring streaming data received by one node of a cluster-based server to other cluster nodes. The intent is to distribute the load on the server generated by the data's processing and distribution to many clients. This is particularly important when the server not only processes streaming data, but also performs additional processing tasks that heavily depend on current application state. One such task is the preparation of suitable initialization state for thin clients, so that such clients can understand future data events being streamed to them. In particular, when large numbers of thin clients must be initialized at the same time, initialization must be performed without jeopardizing the quality of service offered to regular clients continuing to receive data streams. The mirroring framework presented and evaluated has several novel aspects. First, by performing mirroring at the middleware level, application semantics may be used to reduce mirroring traffic, including filtering events based on their content, by coalescing certain events, or by simply varying mirroring rates according to current application needs concerning the consistencies of mirrored vs. original data. Second, we present an adaptive algorithm that varies mirror consistency and thereby, mirroring overheads in response to changes in clients' request behavior. Third, our framework not only mirrors events, but it can also mirror the new states computed from incoming events, thus enabling dynamic tradeoffs in the communication vs. computation loads imposed on the server node receiving events and on its mirror nodes.","PeriodicalId":304683,"journal":{"name":"Proceedings 10th IEEE International Symposium on High Performance Distributed Computing","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2001-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128396498","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 : 2001-08-07DOI: 10.1109/HPDC.2001.945208
A. Takefusa, S. Matsuoka, H. Casanova, F. Berman
The Computational Grid is a promising platform for the deployment of various high-performance computing applications. A number of projects have addressed the idea of software as a service on the network. These systems usually implement client-server architectures with many servers running on distributed Grid resources and have commonly been referred to as network-enabled servers (NES). An important question is that of scheduling in this multi-client multi-server scenario. Note that in this context most requests are computationally intensive as they are generated by high-performance computing applications. The Bricks simulation framework has been developed and extensively used to evaluate scheduling strategies for NES systems. The authors first present recent developments and extensions to the Bricks simulation models. They discuss a deadline scheduling strategy that is appropriate for the multi-client multi-server case, and augment it with "Load Correction" and "Fallback" mechanisms which could improve the performance of the algorithm. We then give Bricks simulation results. The results show that future NES systems should use deadline scheduling with multiple fallbacks and it is possible to allow users to make a trade-off between failure-rate and cost by adjusting the level of conservatism of deadline scheduling algorithms.
{"title":"A study of deadline scheduling for client-server systems on the Computational Grid","authors":"A. Takefusa, S. Matsuoka, H. Casanova, F. Berman","doi":"10.1109/HPDC.2001.945208","DOIUrl":"https://doi.org/10.1109/HPDC.2001.945208","url":null,"abstract":"The Computational Grid is a promising platform for the deployment of various high-performance computing applications. A number of projects have addressed the idea of software as a service on the network. These systems usually implement client-server architectures with many servers running on distributed Grid resources and have commonly been referred to as network-enabled servers (NES). An important question is that of scheduling in this multi-client multi-server scenario. Note that in this context most requests are computationally intensive as they are generated by high-performance computing applications. The Bricks simulation framework has been developed and extensively used to evaluate scheduling strategies for NES systems. The authors first present recent developments and extensions to the Bricks simulation models. They discuss a deadline scheduling strategy that is appropriate for the multi-client multi-server case, and augment it with \"Load Correction\" and \"Fallback\" mechanisms which could improve the performance of the algorithm. We then give Bricks simulation results. The results show that future NES systems should use deadline scheduling with multiple fallbacks and it is possible to allow users to make a trade-off between failure-rate and cost by adjusting the level of conservatism of deadline scheduling algorithms.","PeriodicalId":304683,"journal":{"name":"Proceedings 10th IEEE International Symposium on High Performance Distributed Computing","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2001-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130507772","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 : 2001-08-07DOI: 10.1109/HPDC.2001.945174
Vijay Mann, M. Parashar
The growth of the Internet and the advent of the computational "Grid" have made it possible to develop and deploy advanced computational collaboratories. These systems build on high-end computational resources and communication technologies underlying the Grid, and provide seamless and collaborative access to particular resources, services or applications. Integrating these "focused" collaboratories presents significant challenges. Key among these is the design and development of robust middleware support that addresses scalability, service discovery, security and access control, and interaction and collaboration management for consistent access. The authors first investigate the architecture of such a middleware that enables global (Web-based) access to collaboratories. They then present the design and implementation of a middleware substrate that enables a peer-to-peer integration of and global (collaborative) access to geographically distributed instances of the DISCOVER computational collaboratory for interaction and steering.
{"title":"Middleware support for global access to integrated computational collaboratories","authors":"Vijay Mann, M. Parashar","doi":"10.1109/HPDC.2001.945174","DOIUrl":"https://doi.org/10.1109/HPDC.2001.945174","url":null,"abstract":"The growth of the Internet and the advent of the computational \"Grid\" have made it possible to develop and deploy advanced computational collaboratories. These systems build on high-end computational resources and communication technologies underlying the Grid, and provide seamless and collaborative access to particular resources, services or applications. Integrating these \"focused\" collaboratories presents significant challenges. Key among these is the design and development of robust middleware support that addresses scalability, service discovery, security and access control, and interaction and collaboration management for consistent access. The authors first investigate the architecture of such a middleware that enables global (Web-based) access to collaboratories. They then present the design and implementation of a middleware substrate that enables a peer-to-peer integration of and global (collaborative) access to geographically distributed instances of the DISCOVER computational collaboratory for interaction and steering.","PeriodicalId":304683,"journal":{"name":"Proceedings 10th IEEE International Symposium on High Performance Distributed Computing","volume":"14 4","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2001-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114009986","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 : 2001-08-07DOI: 10.1109/HPDC.2001.945195
C. Krintz, B. Calder
Internet computing is facilitated by a remote execution methodology in which programs transfer to a destination for execution. Since the transfer time can substantially degrade the performance of remotely executed (mobile) programs, file compression is used to reduce the amount of data that is transferred. Compression techniques however, must trade off compression ratio for decompression time, due to the algorithmic complexity of the former, since the latter is performed at run-time in this environment. In this paper, we define the total delay as the time for both the transfer and the decompression of a compressed file. To minimize the total delay, a mobile program should be compressed in the best format for minimizing the delay. Since both the transfer time and the decompression time are dependent upon the current underlying resource performance, selection of the "best" format varies and no one compression format minimizes the total delay for all resource performance characteristics. We present a system called Dynamic Compression Format Selection (DCFS) for the automatic and dynamic selection of competitive compression formats based on the predicted values of future resource performance. Our results show that DCFS reduces the total delay imposed by the compressed transfer of Java archives (.jar files) by 52% on average for the networks, compression techniques and benchmarks studied.
{"title":"Reducing delay with dynamic selection of compression formats","authors":"C. Krintz, B. Calder","doi":"10.1109/HPDC.2001.945195","DOIUrl":"https://doi.org/10.1109/HPDC.2001.945195","url":null,"abstract":"Internet computing is facilitated by a remote execution methodology in which programs transfer to a destination for execution. Since the transfer time can substantially degrade the performance of remotely executed (mobile) programs, file compression is used to reduce the amount of data that is transferred. Compression techniques however, must trade off compression ratio for decompression time, due to the algorithmic complexity of the former, since the latter is performed at run-time in this environment. In this paper, we define the total delay as the time for both the transfer and the decompression of a compressed file. To minimize the total delay, a mobile program should be compressed in the best format for minimizing the delay. Since both the transfer time and the decompression time are dependent upon the current underlying resource performance, selection of the \"best\" format varies and no one compression format minimizes the total delay for all resource performance characteristics. We present a system called Dynamic Compression Format Selection (DCFS) for the automatic and dynamic selection of competitive compression formats based on the predicted values of future resource performance. Our results show that DCFS reduces the total delay imposed by the compressed transfer of Java archives (.jar files) by 52% on average for the networks, compression techniques and benchmarks studied.","PeriodicalId":304683,"journal":{"name":"Proceedings 10th IEEE International Symposium on High Performance Distributed Computing","volume":"463 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2001-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127005707","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 : 2001-08-07DOI: 10.1109/HPDC.2001.945183
Yi Cui, K. Nahrstedt
Building and dynamically configuring component-based systems is an important topic in distributed systems and ubiquitous computing. However, the systematic and automatic configuration management remains a challenging problem for the following reasons: (1) QoS-enforced service delivery demands to maximize the system performance out of the best configuration, (2) dynamically varied resource availability in the distributed environment makes it desirable to achieve the optimized system resource consumption. We present a graph-based dependency management model to address the above problems. Our model integrates the management of inter-component functional dependency, including consistency checking and automatic system configuration, as well as QoS-aware resource dependency management. Based on the model, we present a pruning-based configuration selection algorithm, which is able to consistently optimize the system resource consumption, while preserving the QoS level in a heteregeneous environment. Our initial simulation results prove the soundness of our model and algorithm.
{"title":"QoS-aware dependency management for component-based systems","authors":"Yi Cui, K. Nahrstedt","doi":"10.1109/HPDC.2001.945183","DOIUrl":"https://doi.org/10.1109/HPDC.2001.945183","url":null,"abstract":"Building and dynamically configuring component-based systems is an important topic in distributed systems and ubiquitous computing. However, the systematic and automatic configuration management remains a challenging problem for the following reasons: (1) QoS-enforced service delivery demands to maximize the system performance out of the best configuration, (2) dynamically varied resource availability in the distributed environment makes it desirable to achieve the optimized system resource consumption. We present a graph-based dependency management model to address the above problems. Our model integrates the management of inter-component functional dependency, including consistency checking and automatic system configuration, as well as QoS-aware resource dependency management. Based on the model, we present a pruning-based configuration selection algorithm, which is able to consistently optimize the system resource consumption, while preserving the QoS level in a heteregeneous environment. Our initial simulation results prove the soundness of our model and algorithm.","PeriodicalId":304683,"journal":{"name":"Proceedings 10th IEEE International Symposium on High Performance Distributed Computing","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2001-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125070798","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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