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Uncertainty explicit assessment of off-the-shelf software: A Bayesian approach
Assessment of software COTS components is an essential part of component-based software development. Poorly chosen components may lead to solutions of low quality and that are difficult to maintain. The assessment may be based on incomplete knowledge about the COTS component itself and other aspects (e.g. vendor’s credentials, etc.), which may affect the decision of selecting COTS component(s). We argue in favor of assessment methods in which uncertainty is explicitly represented (‘uncertainty explicit’ methods) using probability distributions. We provide details of a Bayesian model, which can be used to capture the uncertainties in the simultaneous assessment of two attributes, thus, also capturing the dependencies that might exist between them. We also provide empirical data from the use of this method for the assessment of off-the-shelf database servers which illustrate the advantages of ‘uncertainty explicit’ methods over conventional methods of COTS component assessment which assume that at the end of the assessment the values of the attributes become known with certainty
Middleware-based Database Replication: The Gaps between Theory and Practice
The need for high availability and performance in data management systems has
been fueling a long running interest in database replication from both academia
and industry. However, academic groups often attack replication problems in
isolation, overlooking the need for completeness in their solutions, while
commercial teams take a holistic approach that often misses opportunities for
fundamental innovation. This has created over time a gap between academic
research and industrial practice.
This paper aims to characterize the gap along three axes: performance,
availability, and administration. We build on our own experience developing and
deploying replication systems in commercial and academic settings, as well as
on a large body of prior related work. We sift through representative examples
from the last decade of open-source, academic, and commercial database
replication systems and combine this material with case studies from real
systems deployed at Fortune 500 customers. We propose two agendas, one for
academic research and one for industrial R&D, which we believe can bridge the
gap within 5-10 years. This way, we hope to both motivate and help researchers
in making the theory and practice of middleware-based database replication more
relevant to each other.Comment: 14 pages. Appears in Proc. ACM SIGMOD International Conference on
Management of Data, Vancouver, Canada, June 200
Run Time Approximation of Non-blocking Service Rates for Streaming Systems
Stream processing is a compute paradigm that promises safe and efficient
parallelism. Modern big-data problems are often well suited for stream
processing's throughput-oriented nature. Realization of efficient stream
processing requires monitoring and optimization of multiple communications
links. Most techniques to optimize these links use queueing network models or
network flow models, which require some idea of the actual execution rate of
each independent compute kernel within the system. What we want to know is how
fast can each kernel process data independent of other communicating kernels.
This is known as the "service rate" of the kernel within the queueing
literature. Current approaches to divining service rates are static. Modern
workloads, however, are often dynamic. Shared cloud systems also present
applications with highly dynamic execution environments (multiple users,
hardware migration, etc.). It is therefore desirable to continuously re-tune an
application during run time (online) in response to changing conditions. Our
approach enables online service rate monitoring under most conditions,
obviating the need for reliance on steady state predictions for what are
probably non-steady state phenomena. First, some of the difficulties associated
with online service rate determination are examined. Second, the algorithm to
approximate the online non-blocking service rate is described. Lastly, the
algorithm is implemented within the open source RaftLib framework for
validation using a simple microbenchmark as well as two full streaming
applications.Comment: technical repor
Performance Testing of Distributed Component Architectures
Performance characteristics, such as response time, throughput andscalability, are key quality attributes of distributed applications. Current practice,however, rarely applies systematic techniques to evaluate performance characteristics.We argue that evaluation of performance is particularly crucial in early developmentstages, when important architectural choices are made. At first glance, thiscontradicts the use of testing techniques, which are usually applied towards the endof a project. In this chapter, we assume that many distributed systems are builtwith middleware technologies, such as the Java 2 Enterprise Edition (J2EE) or theCommon Object Request Broker Architecture (CORBA). These provide servicesand facilities whose implementations are available when architectures are defined.We also note that it is the middleware functionality, such as transaction and persistenceservices, remote communication primitives and threading policy primitives,that dominates distributed system performance. Drawing on these observations, thischapter presents a novel approach to performance testing of distributed applications.We propose to derive application-specific test cases from architecture designs so thatthe performance of a distributed application can be tested based on the middlewaresoftware at early stages of a development process. We report empirical results thatsupport the viability of the approach
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