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Mapping Filtering Streaming Applications With Communication Costs
, 2009
"... In this paper, we explore the problem of mapping filtering streaming applications on largescale homogeneous platforms, with a particular emphasis on communication models and their impact. Filtering application are streaming applications where each node also has a selectivity which either increases ..."
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In this paper, we explore the problem of mapping filtering streaming applications on largescale homogeneous platforms, with a particular emphasis on communication models and their impact. Filtering application are streaming applications where each node also has a selectivity which either increases or decreases the size of its input data set. This selectivity makes the problem of scheduling these applications more challenging than the more studied problem of scheduling “nonfiltering ” streaming workflows. We identify three significant realistic communication models. For each of them, we address the complexity of the following important problems: 1. Given an execution graph, how can one compute the period and latency? A solution to this problem is an operation list which provides the timesteps at which each computation and each communication occurs in the system. 2. Given a filtering workflow problem, how can one compute the schedule that minimizes the period or latency? A solution to this problem requires generating both the execution graph and the associated operation list. Altogether, with three models, two problems and two objectives, we present 12 complexity results, thereby providing solid theoretical foundations for the study of filtering streaming applications. Key words: query optimization, web service, streaming application, workflow, communication model, period, latency, complexity results. 0 1
Filter placement on a pipelined architecture
 IN: INTERNATIONAL SYMPOSIUM ON PARALLEL AND DISTRIBUTED PROCESSING
, 2009
"... In this paper, we explore the problem of mapping filtering query services on chains of heterogeneous processors. Two important optimization criteria should be considered in such a framework. The period, which is the inverse of the throughput, measures the rate at which data sets can enter the system ..."
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Cited by 2 (1 self)
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In this paper, we explore the problem of mapping filtering query services on chains of heterogeneous processors. Two important optimization criteria should be considered in such a framework. The period, which is the inverse of the throughput, measures the rate at which data sets can enter the system. The latency measures the response time of the system in order to process one single data set entirely. We provide a comprehensive set of complexity results for period and latency optimization problems, with proportional or arbitrary computation costs, and without or with communication costs. We present polynomial algorithms for problems whose dependence graph is a linear chain (hence a fixed ordering of the filtering services). For independent services, the problems are all NPcomplete except latency minimization with proportional computation costs, which was shown polynomial in [6].
On the Complexity of Mapping Pipelined Filtering Services on Heterogeneous Platforms
, 2008
"... In this paper, we explore the problem of mapping filtering services on largescale heterogeneous platforms. Two important optimization criteria should be considered in such a framework. The period, which is the inverse of the throughput, measures the rate at which data sets can enter the system. The ..."
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Cited by 1 (1 self)
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In this paper, we explore the problem of mapping filtering services on largescale heterogeneous platforms. Two important optimization criteria should be considered in such a framework. The period, which is the inverse of the throughput, measures the rate at which data sets can enter the system. The latency measures the response time of the system in order to process one single data set entirely. Both criteria are antagonistic. For homogeneous platforms, the complexity of period minimization is already known [1]; we derive an algorithm to solve the latency minimization problem in the general case with service precedence constraints; for independent services we also show that the bicriteria problem (latency minimization without exceeding a prescribed value for the period) is of polynomial complexity. However, when adding heterogeneity to the platform, we prove that minimizing the period or the latency becomes NPhard, and that these problems cannot be approximated by any constant factor (unless P=NP). The latter results hold true even for independent services. We provide an integer linear program to solve both problems in the heterogeneous case with independent services. For period minimization on heterogeneous platforms, we design some efficient polynomial time heuristics and we assess their relative and absolute performance through a set of experiments. For small problem instances, the results are very close to the optimal solution returned by the integer linear program.