We present DiPerF, a distributed performance-testing framework, aimed at simplifying and automating service performance evaluation. DiPerF coordinates a pool of machines that test a target service, collects and aggregates performance metrics, and generates performance statistics. The aggregate data collected provide information on service throughput, on service ‘fairness’ when serving multiple clients concurrently, and on the impact of network latency on service performance. Furthermore, using this data, it is possible to build predictive models that estimate a service performance given the service load. We have tested DiPerF on 100+ machines on two testbeds, Grid3 and PlanetLab, and explored the performance of job submission services (pre-...
Due to the imperative need to reduce the management costs, operators multiplex several concurrent ap...
Performance Testing is one of the crucial parts of any software cycle process. In today’s world, the...
Analyzing the scalability and quality of service of large scale distributed systems, such as cloud b...
The Object Management Group’s (OMG) Data Distribution Ser-vice (DDS) provides many configurable poli...
One of the primary tools for performance analysis of multi-tier systems are standardized benchmarks....
International audiencePredicting distributed application performance is a constant challenge to rese...
Grid workflows are executed on diverse resources whose interactions are highly complicated and hardl...
Abstract—One of the primary tools for performance analysis of multi-tier systems are standardized be...
The successful development and deployment of large-scale Inter-net services depend critically on per...
Performance testing in distributed environments is challenging. Specifically, the identification of ...
Accurate performance testing of heterogeneous distributed systems, such as those created using GRID ...
In this dissertation, we describe a methodology to develop analytic performance models for client-se...
Diagnosing performance problems in modern datacenters and distributed systems is challenging, as the...
International audience--In the search of new architecture for distributed computing, peer-to-peer is...
A performance prediction framework is described in which predictive data generated by the PACE toolk...
Due to the imperative need to reduce the management costs, operators multiplex several concurrent ap...
Performance Testing is one of the crucial parts of any software cycle process. In today’s world, the...
Analyzing the scalability and quality of service of large scale distributed systems, such as cloud b...
The Object Management Group’s (OMG) Data Distribution Ser-vice (DDS) provides many configurable poli...
One of the primary tools for performance analysis of multi-tier systems are standardized benchmarks....
International audiencePredicting distributed application performance is a constant challenge to rese...
Grid workflows are executed on diverse resources whose interactions are highly complicated and hardl...
Abstract—One of the primary tools for performance analysis of multi-tier systems are standardized be...
The successful development and deployment of large-scale Inter-net services depend critically on per...
Performance testing in distributed environments is challenging. Specifically, the identification of ...
Accurate performance testing of heterogeneous distributed systems, such as those created using GRID ...
In this dissertation, we describe a methodology to develop analytic performance models for client-se...
Diagnosing performance problems in modern datacenters and distributed systems is challenging, as the...
International audience--In the search of new architecture for distributed computing, peer-to-peer is...
A performance prediction framework is described in which predictive data generated by the PACE toolk...
Due to the imperative need to reduce the management costs, operators multiplex several concurrent ap...
Performance Testing is one of the crucial parts of any software cycle process. In today’s world, the...
Analyzing the scalability and quality of service of large scale distributed systems, such as cloud b...