Adaptive Partitioning and Scheduling for Enhancing WWW Application Performance

Andresen, Daniel; Yang, Tao; Ibarra, Óscar H.; Eğecioǧlu, Ömer

doi:10.1006/jpdc.1998.1423

Cited by 12 publications

(8 citation statements)

References 13 publications

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“…Several distributed load balancing models were proposed in the literature: the gradient model [23], [25], [28], sender or receiver-initiated diffusion [35], [31], [4], the hierarchical balancing model [35], and others. Practical implementations of such models vary based on the resources considered for scheduling: CPU [10], [12], [18], [20], [22], memory [1], [33], [37], [36], or combinations of I/O, CPU and memory [3], [2], [11]. Of particular interest for us are load balancing systems used for distributed Internet services.…”

Section: Related Workmentioning

confidence: 99%

“…We exploit the intertask parallelism in a manner roughly similar with the SWEB project [3], [2], but we enhance their model with more scheduling points and intratask parallelism. On the other hand, the exploitation of intratask parallelism in the distributed Q/A system is roughly similar to the Piranha project [10].…”

Section: Related Workmentioning

confidence: 99%

“…Of particular interest for us are load balancing systems used for distributed Internet services. Attempts were made to improve the performance of by now ubiquitous search engines and digital library interfaces [3], [2] using distributed processing techniques, in order to sustain very high loads.…”

Section: Related Workmentioning

confidence: 99%

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Performance analysis of a distributed question/answering system

Surdeanu

Moldovan

Harabagiu

2002

IEEE Trans. Parallel Distrib. Syst.

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AbstractÐThe problem of question/answering (Q/A) is to find answers to open-domain questions by searching large collections of documents. Unlike information retrieval systems very common today in the form of Internet search engines, Q/A systems do not retrieve documents, but instead provide short, relevant answers located in small fragments of text. This enhanced functionality comes with a price: Q/A systems are significantly slower and require more hardware resources than information retrieval systems. This paper proposes a distributed Q/A architecture that enhances the system throughput through the exploitation of interquestion parallelism and dynamic load balancing and reduces the individual question response time through the exploitation of intraquestion parallelism. Inter and intraquestion parallelism are both exploited using several scheduling points: one before the Q/A task is started and two embedded in the Q/A task. An analytical performance model is introduced. The model analyzes both the interquestion parallelism overhead generated by the migration of questions and the intraquestion parallelism overhead generated by the partitioning of the Q/A task. The analytical model indicates that both question migration and partitioning are required for a high-performance system: Intraquestion parallelism leads to significant speedup of individual questions, but it is practical up to about 90 processors, depending on the system parameters. The exploitation of intertask parallelism provides a scalable way to improve the system throughput. The distributed Q/A system has been implemented on a network of 16 Pentium III computers. The experimental results indicate that, at high system load, the dynamic load balancing strategy proposed in this paper outperforms two other traditional approaches. At low system load, the distributed Q/A system reduces question response times through task partitioning, with factors close to the ones indicated by the analytical model.

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Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

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Performance analysis of a distributed question/answering system

Surdeanu

Moldovan

Harabagiu

2002

IEEE Trans. Parallel Distrib. Syst.

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“…Existing work has focused primarily on resource discovery and scheduling [4,17,10,28] among workstations [3,1,19,22,23,9]. The work reported herein extends the target domain for GTOMO by targeting both parallel supercomputers and interactive resources simultaneously.…”

Section: Related Workmentioning

confidence: 99%

“…Section 6 concludes the paper and discusses future work. 1 In practice, queue times may range from seconds to days.…”

Section: Introductionmentioning

confidence: 99%