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385
IBL for Replica Selection in Data-Intensive Grid Applications
, 2004
"... In many scientific applications, Grid technologies and infrastructures facilitate distributed resource sharing and coordination in dynamic, heterogeneous multi-institutional environments. Replication of data can help enable high-throughput file transfer and scalable resource storage in scientific Gr ..."
Abstract
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Cited by 2 (0 self)
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Grid applications that involve large data transfers. The selection of a replica can, however, significantly influence the efficiency of a replication scheme. Many current approaches assume that a significant amount of data is available, such as network status information, log files of historical Grid
Three Light-Weight Execution Engines in Java for Web Data-Intensive Applications
, 1998
"... ambrosiamit.edu,philippe.bonnetedyade.fr, stephecontext.mit.edugrusereumiacs.umd.edu 1 ..."
Abstract
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ambrosiamit.edu,philippe.bonnetedyade.fr, stephecontext.mit.edugrusereumiacs.umd.edu 1
GLIDE: A Grid-based Lightweight Infrastructure for Data-intensive Environments
- European Grid Conference
, 2005
"... Abstract. The promise of the grid is that it will enable public access and sharing of immense amounts of computational and data resources among dynamic coalitions of individuals and institutions. However, the current grid solutions make several limiting assumptions that curtail their widespread adop ..."
Abstract
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Cited by 8 (5 self)
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support to grid users (e.g., scientists). To address these limitations, we present GLIDE, a prototype light-weight, data-intensive middleware infrastructure that enables access to the robust data and computational power of the grid on DREAM platforms. We illustrate GLIDE on an example file sharing
Flashback: A Lightweight Extension for Rollback and Deterministic Replay for Software Debugging
- In USENIX Annual Technical Conference, General Track
, 2004
"... Unfortunately, finding software bugs is a very challenging task because many bugs are hard to reproduce. While debugging a program, it would be very useful to rollback a crashed program to a previous execution point and deterministically re-execute the "buggy " code region. However ..."
Abstract
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Cited by 155 (7 self)
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-grained rollback and replay to help debug software. Flashback uses shadow processes to efficiently roll back in-memory state of a process, and logs a process ' interactions with the system to support deterministic replay. Both shadow processes and logging of system calls are implemented in a lightweight
Topology-aware resource allocation for data-intensive workloads
- SIGCOMM CCR
, 2011
"... This paper proposes an architecture for optimized resource allocation in Infrastructure-as-a-Service (IaaS)-based cloud systems. Current IaaS systems are usually unaware of the hosted application’s requirements and therefore allocate resources independently of its needs, which can significantly impa ..."
Abstract
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Cited by 16 (2 self)
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impact performance for distributed data-intensive applications. To address this resource allocation problem, we propose an architecture that adopts a “what if ” methodology to guide allocation decisions taken by the IaaS. The architecture uses a prediction engine with a lightweight simulator to estimate
Deferred lightweight indexing for log-structured keyvalue stores
- In IEEE/ACM 15th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing, CCGrid 2015, Shenzhen Guandong
, 2015
"... The recent shift towards write-intensive workload on big data (e.g., financial trading, social user-generated data streams) has pushed the proliferation of log-structured key-value stores, represented by Google’s BigTable [1], Apache HBase [2] and Cassandra [3]. While providing key-based data access ..."
Abstract
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Cited by 1 (1 self)
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The recent shift towards write-intensive workload on big data (e.g., financial trading, social user-generated data streams) has pushed the proliferation of log-structured key-value stores, represented by Google’s BigTable [1], Apache HBase [2] and Cassandra [3]. While providing key-based data
Lightweight Indexing of Observational Data in Log-Structured Storage
"... Huge amounts of data are being generated by sensing devices every day, recording the status of objects and the environment. Such observational data is widely used in scientific research. As the capabilities of sensors keep improving, the data produced are drastically expanding in precision and quant ..."
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and quantity, making it a write-intensive domain. Log-structured storage is capable of providing high write throughput, and hence is a natural choice for managing large-scale observational data. In this paper, we propose an approach to indexing and queryingobservationaldatainlog-structuredstorage. Based on key
Simultaneous Scheduling of Replication and Computation for Data-Intensive Applications on the Grid
, 2005
"... One of the first motivations of using grids comes from applications managing large data sets like for example in High Energy Physic or Life Sciences. To improve the global throughput of software environments, replicas are usually put at wisely selected sites. Moreover, computation requests have to ..."
Abstract
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Cited by 13 (1 self)
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One of the first motivations of using grids comes from applications managing large data sets like for example in High Energy Physic or Life Sciences. To improve the global throughput of software environments, replicas are usually put at wisely selected sites. Moreover, computation requests have
2GLIDE: A Grid-based Light-weight Infrastructure for Data-intensive Environments
"... Abstract. The promise of the grid is that it will enable public access and shar-ing of immense amounts of computational and data resources among dynamic coalitions of individuals and institutions. However, the current grid solutions make several limiting assumptions that curtail their widespread ado ..."
Abstract
- Add to MetaCart
design sup-port to grid users (e.g., scientists). To address these limitations, we present GLIDE, a prototype light-weight, data-intensive middleware infrastructure that enables access to the robust data and computational power of the grid on DREAM platforms. We illustrate GLIDE on an example file
Fine-Grained Profiling for Data-Intensive Workflows † Table 3: Comparison of trace log size Data
"... ParaTrac is a user-level profiler using file system and process tracing techniques for data-intensive workflow applications. ParaTrac enables users to quickly understand the detailed I/O characteristics from entire application to specific processes or files, it also automatically exploits fine-grain ..."
Abstract
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Cited by 6 (0 self)
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ParaTrac is a user-level profiler using file system and process tracing techniques for data-intensive workflow applications. ParaTrac enables users to quickly understand the detailed I/O characteristics from entire application to specific processes or files, it also automatically exploits fine
Results 1 - 10
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385