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Optimizing Hadoop executions has attracted a lot of research contributions in particular in the domain of self-adaptive software systems. However, these research efforts are often hindered by the complexity of Hadoop operation and the difficulty to reproduce experimental evaluations that makes it hard to compare different approaches to one another. To address this limitation, we propose a research...
The importance of continuous delivery and the emergence of tools allowing to treat infrastructure configurations programmatically have revolutionized the way computing resources and software systems are managed. However, these tools keep lacking an explicit model representation of underlying resources making it difficult to introspect, verify or reconfigure the system in response to external events...
There is a trade-off between the number of concurrently running MapReduce jobs and their corresponding map and reduce tasks within a node in a Hadoop cluster. Leaving this trade-off statically configured to a single value can significantly reduce job response times leaving only sub optimal resource usage. To overcome this problem, we propose a feedback control loop based approach that dynamically...
The software engineering community has proposed numerous approaches for making software self-adaptive. These approaches take inspiration from machine learning and control theory, constructing software that monitors and modifies its own behavior to meet goals. Control theory, in particular, has received considerable attention as it represents a general methodology for creating adaptive systems. Control-theoretical...
Future software systems will be highly dynamic. We are already experiencing, for example, a world where Cyber-Physical Systems (CPSs) play a more and more crucial role. CPSs integrate computational, physical, and networking elements, they comprise a number of subsystems, or entities, that are connected and work together. The open and highly distributed nature of the resulting system gives rise to...
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