This paper reports our practical experience of benchmarking a complex System Biology Web Service, and investigates the instability of its behaviour and the delays induced by the communication medium. We present the results of our statistical data analysis and the distributions, describing and predicting the response time instability typical of Service-Oriented Architectures (SOAs) built over the Internet. Our experiment has shown that the request processing time of the target e-science Web Service has a higher instability than the network round trip time. It was found that the request processing time can be represented better than the network round trip time using a particular theoretical distribution, moreover the probability distribution series of the round trip time have characteristics make it really difficult to describe them theoretically. The paper concludes with discussing the lessons learnt about the analysis techniques to be used in such experiments, the validity of the data, the main causes of uncertainty and possible remedial action.
AbstractThis paper reports our practical experience of benchmarking a complex System Biology Web Service, and investigates the instability of its behaviour and the delays induced by the communication medium. We present the results of our statistical data analysis and the distributions, describing and predicting the response time instability typical of Service-Oriented Architectures (SOAs) built over the Internet. Our experiment has shown that the request processing time of the target e-science Web Service has a higher instability than the network round trip time. It was found that the request processing time can be represented better than the network round trip time using a particular theoretical distribution, moreover the probability distribution series of the round trip time have characteristics make it really difficult to describe them theoretically. The paper concludes with discussing the lessons learnt about the analysis techniques to be used in such experiments, the validity of the data, the main causes of uncertainty and possible remedial action.
About the authorsAnatoliy Gorbenko graduated in computer science in 2000 and received the PhD degree from the National Aerospace University, Kharkiv, Ukraine in 2005. He is an Associate Professor at the Department of Computer Systems and Networks of the National Aerospace University in Kharkiv (Ukraine). There he co-coordinates the DESSERT (Dependable Systems, Services and Technologies) research group. His work focuses on system research ensuring dependability and fault tolerance in service-oriented architectures; on investigating system diversity, dependability assessment and exception handling, and on applying these results in real industrial applications. Dr. Gorbenko is a member of EASST (European Association of Software Science and Technology).
AbstractThis paper reports our practical experience of benchmarking a complex System Biology Web Service, and investigates the instability of its behaviour and the ...