His primary scientific interests are in Distributed computing, Workload, Cloud computing, Resource and Real-time computing. His study in Distributed computing is interdisciplinary in nature, drawing from both Scalability, Resource allocation, Quality of service, Benchmark and Server. His research integrates issues of Performance prediction, Reliability engineering and Software development process in his study of Scalability.
His Workload research is multidisciplinary, incorporating elements of Intrusion detection system, Service level objective and Data science. His Hypervisor study in the realm of Cloud computing interacts with subjects such as Benchmarking. His Real-time computing research is multidisciplinary, incorporating perspectives in Software architecture, Software system, Java and Unified Modeling Language.
His scientific interests lie mostly in Distributed computing, Cloud computing, Scalability, Workload and Virtualization. His Distributed computing research incorporates elements of Real-time computing, Benchmark, Performance prediction, Server and Component. As part of the same scientific family, Samuel Kounev usually focuses on Performance prediction, concentrating on Software system and intersecting with Software engineering.
Samuel Kounev has included themes like Software, Resource, Service and Provisioning in his Cloud computing study. His Scalability research is multidisciplinary, relying on both Queueing petri nets, Queueing theory, Software architecture and Petri net. His Virtualization research incorporates themes from Virtual machine and Shared resource.
His main research concerns Cloud computing, Benchmark, Benchmarking, Distributed computing and Software. His Cloud computing study combines topics in areas such as Computer security, Reliability engineering and Function. His work focuses on many connections between Reliability engineering and other disciplines, such as Application performance management, that overlap with his field of interest in Performance prediction.
The concepts of his Benchmark study are interwoven with issues in Spec# and Encryption. Samuel Kounev combines Distributed computing and Elasticity in his studies. His Process research integrates issues from Systems design, Software engineering, Dependability and Component-based software engineering.
The scientist’s investigation covers issues in Machine learning, Artificial intelligence, Cloud computing, Time series and Task. His work deals with themes such as Optimizing compiler, Spec#, Software and Benchmark, which intersect with Cloud computing. His Time series research includes elements of Property and Feature extraction.
His work on Task analysis as part of general Task research is frequently linked to Feature engineering, Computing systems, Existential quantification and Trial and error, bridging the gap between disciplines. Samuel Kounev undertakes interdisciplinary study in the fields of Computing systems and Overhead through his works. His studies in Overhead integrate themes in fields like S.M.A.R.T., Hard disk drive failure, Reliability engineering and Data analysis.
This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.
Elasticity in Cloud Computing: What It Is, and What It Is Not.
Nikolas Roman Herbst;Samuel Kounev;Ralf H. Reussner.
international conference on autonomic computing (2013)
Performance Modeling and Evaluation of Distributed Component-Based Systems Using Queueing Petri Nets
IEEE Transactions on Software Engineering (2006)
Self-adaptive workload classification and forecasting for proactive resource provisioning
Nikolas Roman Herbst;Nikolaus Huber;Samuel Kounev;Erich Amrehn.
Concurrency and Computation: Practice and Experience (2014)
EVALUATING AND MODELING VIRTUALIZATION PERFORMANCE OVERHEAD FOR CLOUD ENVIRONMENTS
Nikolaus Huber;Marcel von Quast;Michael Hauck;Samuel Kounev.
international conference on cloud computing and services science (2011)
Evaluating Computer Intrusion Detection Systems: A Survey of Common Practices
Aleksandar Milenkoski;Marco Vieira;Samuel Kounev;Alberto Avritzer.
ACM Computing Surveys (2015)
ARCHITECTURAL CONCERNS IN MULTI-TENANT SaaS APPLICATIONS
Rouven Krebs;Christof Momm;Samuel Kounev.
international conference on cloud computing and services science (2012)
SimQPN: a tool and methodology for analyzing queueing Petri net models by means of simulation
Samuel Kounev;Alejandro Buchmann.
Performance Evaluation (2006)
Performance modelling of distributed e-business applications using Queuing Petri Nets
S. Kounev;A. Buchmann.
international symposium on performance analysis of systems and software (2003)
Metrics and techniques for quantifying performance isolation in cloud environments
Rouven Krebs;Christof Momm;Samuel Kounev.
Science of Computer Programming (2014)
Performance modeling and evaluation of large-scale J2EE applications
Samuel Kounev;Alejandro P. Buchmann.
Int. CMG Conference (2003)
Profile was last updated on December 6th, 2021.
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