Samuel Kounev

University of Wuerzburg | JMU · Department of Computer Science

A core selling point of application containers is their fast start times compared to other virtualization approaches like virtual machines. Predictable and fast container start times are crucial for improving and guaranteeing the performance of containerized cloud, serverless, and edge applications. While previous work has investigated container st...

Autoscaling has been one of the most active research areas since the beginning of the cloud computing era. Nearly all previously proposed approaches focus on decision-making based on averaged monitoring values of many service instances at fixed points in time. This limits responsiveness and can lead to service level objective (SLO) violations when...

Autoscalers are indispensable parts of modern cloud deployments and determine the service quality and cost of a cloud application in dynamic workloads. The configuration of an autoscaler strongly influences its performance and is also one of the biggest challenges and showstoppers for the practical applicability of many research autoscalers. Many p...

Container orchestration frameworks play a critical role in modern cloud computing paradigms such as cloud-native or serverless computing. They significantly impact the quality and cost of service deployment as they manage many performance-critical tasks such as container provisioning, scheduling, scaling, and networking. Consequently, a comprehensi...

In warehouses, order picking is known to be the most labor-intensive and costly task in which the employees account for a large part of the warehouse performance. Hence, many approaches exist, that optimize the order picking process based on diverse economic criteria. However, most of these approaches focus on a single economic objective at once an...

In today’s world, circumstances, processes, and requirements for software systems are becoming increasingly complex. In order to operate properly in such dynamic environments, software systems must adapt to these changes, which has led to the research area of Self-Adaptive Systems (SAS). Platooning is one example of adaptive systems in Intelligent...

Goal This paper presents an immersive Virtual Reality (VR) system to analyze and train Executive Functions (EFs) of soccer players. EFs are important cognitive functions for athletes. They are a relevant quality that distinguishes amateurs from professionals. Method The system is based on immersive technology, hence, the user interacts naturally a...

In the last decades, the classical Vehicle Routing Problem (VRP), i.e., assigning a set of orders to vehicles and planning their routes has been intensively researched. As only the assignment of order to vehicles and their routes is already an NP-complete problem, the application of these algorithms in practice often fails to take into account the...

Objectives: This study aims to improve early detection of cardiac surgery-associated acute kidney injury using artificial intelligence-based algorithms. Methods: Data from consecutive patients undergoing cardiac surgery between 2008 and 2018 in our institution served as the source for artificial intelligence-based modeling. Cardiac surgery-assoc...

Context Recent developments in modern IT systems including internet of things, edge/fog computing, or cyber–physical systems support intelligent and seamless interaction between users and systems. This requires a reaction to changes in their environment or the system. Adaptive systems provide mechanisms for these reactions. Objective To implement...

Performance regression testing is a foundation of modern DevOps processes and pipelines. Thus, the detection of change points, i.e., updates or commits that cause a significant change in the performance of the software, is of special importance. Typically, validating potential change points relies on humans, which is a considerable bottleneck and c...

Autoscaling is a task of major importance in the cloud computing domain as it directly affects both operating costs and customer experience. Although there has been active research in this area for over ten years now, there is still a significant gap between the proposed methods in the literature and the deployed autoscalers in practice. Hence, man...

Context While in serverless computing, application resource management and operational concerns are generally delegated to the cloud provider, ensuring that serverless applications meet their performance requirements is still a responsibility of the developers. Performance testing is a commonly used performance assessment practice; however, it trad...

The representation of the surrounding world emerges through integration of sensory information and actions. We present a novel neural model which implements non-local, parallel information processing on a neocolumnar architecture with lateral interconnections. Information is integrated into a holographic wave interference pattern. We compare the si...

A key feature for Internet of Things (IoT) is to control what content is available to each user. To handle this access management, encryption schemes can be used. Due to the diverse usage of encryption schemes, there are various realizations of 1-to-1, 1-to-n, and n-to-n schemes in the literature. This multitude of encryption methods with a wide va...

Efficient and dependable communication is a highly relevant aspect for Internet of Things (IoT) systems in which tiny sensors, actuators, wearables, or other smart devices exchange messages. Various publish/subscribe protocols address the challenges of communication in IoT systems. The selection process of a suitable protocol should consider the co...

In warehouses, order picking is known to be the most labor-intensive and costly task in which the employees account for a large part of the warehouse performance. Hence, many approaches exist, that optimize the order picking process based on diverse economic criteria. However, most of these approaches focus on a single economic objective at once an...

In today's world, circumstances, processes, and requirements for software systems are becoming increasingly complex. In order to operate properly in such dynamic environments, software systems must adapt to these changes, which has led to the research area of Self-Adaptive Systems (SAS). Platooning is one example of adaptive systems in Intelligent...

In the last decades, the classical Vehicle Routing Problem (VRP), i.e., assigning a set of orders to vehicles and planning their routes has been intensively researched. As only the assignment of order to vehicles and their routes is already an NP-complete problem, the application of these algorithms in practice often fails to take into account the...

Quantum Computing threatens security of today's systems. Confidence in today's security technologies largely relies on Public Key Cryptography (PKC), which depends on computational difficulty of mathematical problems that cannot be solved efficiently using any technology available today. This will, however, change once a sufficiently capable quantu...

In the next few years, both the number of IoT devices and the performance of quantum computers will increase. Both technologies pose a challenge to our current crypto-strategies. Therefore, post-quantum n-ton communication encryption is a crucial field of research. Here, the development of new schemes and the analysis, and comparison of existing sc...

Serverless functions are an emerging cloud computing paradigm that is being rapidly adopted by both industry and academia. In this cloud computing model, the provider opaquely handles resource management tasks such as resource provisioning, deployment, and auto-scaling. The only resource management task that developers are still in charge of is sel...

In the recent past, platooning evolved into an attractive cooperative driving technology, broadly discussed in research and practice. Vehicles in platoons use cooperative adaptive cruise control to drive at close distances to each other. Platooning (i) increases the capacity of the street by a factor of 2; (ii) reduces the fuel consumption and emis...

Context. While in serverless computing, application resource management and operational concerns are generally delegated to the cloud provider, ensuring that serverless applications meet their performance requirements is still a responsibility of the developers. Performance testing is a commonly used performance assessment practice; however, it tra...

Despite the increased sensor-based data collection in Industry 4.0, the practical use of this data is still in its infancy. In contrast, academic literature provides several approaches to detect machine failures but, in most cases, relies on simulations and vast amounts of training data. Since it is often not practical to collect such amounts of da...

Resource demands are crucial parameters for modeling and predicting the performance of software systems. Currently, resource demand estimators are usually executed once for system analysis. However, the monitored system, as well as the resource demand itself, are subject to constant change in runtime environments. These changes additionally impact...

Predictive planning of maintenance windows reduces the risk of unwanted production or operational downtimes and helps to keep machines, vessels, or any system in optimal condition. The quality of such a data-driven model for the prediction of remaining useful lifetime is largely determined by the data used to train it. Training data with qualitativ...

In many areas of decision making, forecasting is an essential pillar. Consequently, there are many different forecasting methods. According to the "No-Free-Lunch Theorem", there is no single forecasting method that performs best for all time series. In other words, each method has its advantages and disadvantages depending on the specific use case....

IoT devices often communicate over wireless or cellular networks with varying connection quality. These fluctuations are caused, among others, by the free-space path loss (FSPL), buildings, topological obstacles, weather, and mobility of the receiver. Varying signal quality affects bandwidth, transmission delays, packet loss, and jitter. Mobile IoT...

Today’s data centers face continuous changes, including deployed services, growing complexity, and increasing performance requirements. Customers expect not only round-the-clock availability of the hosted services but also high responsiveness. Besides optimizing software architectures and deployments, networks have to be adapted to handle the chang...

The demand for passenger and freight transportation has grown sharply over the last decades and will triple by 2050. This also dramatically impacts the environment as traffic is one of the primary sources of CO2 emission. Platooning, which is defined as driving automated vehicles in convoys with minimal inter-vehicle distance enabled by vehicular c...

Tor is a widely used anonymization network. Traffic is routed over different relay nodes to conceal the communication partner. The Tor Load Balancing Mechanism (TLBM) is responsible for assigning traffic to relays. However, up to this point, there are no agreed-upon quality and security metrics for evaluating the quality of the TLBM. In practice, m...

The growth of cloud services leads to more and more data centers that are increasingly larger and consume considerable amounts of power. To increase energy efficiency, both the actual server equipment and the software must become more energy efficient. Software has a major impact on hardware utilization levels, and subsequently, the energy efficien...

Correctly configuring a distributed database management system (DBMS) deployed in a cloud environment for maximizing performance poses many challenges to operators. Even if the entire configuration spectrum could be measured directly, which is often infeasible due to the multitude of parameters, single measurements are subject to random variations...

Serverless functions are a cloud computing paradigm that reduces operational overheads for developers, because the cloud provider takes care of resource management tasks such as resource provisioning, deployment, and auto-scaling. The only resource management task that developers are still in charge of is resource sizing, that is, selecting how muc...

Aim: To characterize the impact of the German strategy for containment of Coronavirus SARS-CoV-2 (social distancing and lockdown) on the training, other habitual physical activity, and sleep in highly trained kayakers and canoeists. Method: During the 4 weeks immediately prior to and following the beginning of the German government's strategy for c...

Tor is a widely used anonymization network. Traffic is routed over different relay nodes to conceal the communication partners. However, if a single relay handles too much traffic, de-anonymization attacks are possible. The Tor Load Balancing Mechanism (TLBM) is responsible for balanced and secure load distribution. It must verify that relays canno...

The complexity of managing the capacities of large IT infrastructures is constantly increasing as more network devices are connected. This task can no longer be performed manually , so the system must be monitored at runtime and estimations of future conditions must be made automatically. However, since using a single forecasting method typically p...

This chapter introduces the foundations of experimental design. Starting with the case of one factor, the analysis of variance technique from statistics is introduced, followed by the method of contrasts for comparing subsets of alternatives. The analysis of variance technique is then generalized to two factors that can be varied independently, and...

In this chapter, we survey, systematize, and evaluate different approaches to the statistical estimation of resource demands based on easy-to-measure system-level and application-level metrics. We consider resource demands in the context of computing systems; however, the methods we present are also applicable to other types of systems. We focus on...

In this chapter, we briefly review the basics of probability and statistics while establishing the statistical notation needed for understanding some of the chapters in the book. The chapter is not intended as an introduction to probability and statistics, but rather as a quick refresher assuming that the reader is already familiar with the basic c...

In this chapter, we start by looking at some basic quantitative relationships, which can be used to evaluate a system’s performance based on measured or known data, a process known as operational analysis. In the second part, we provide a brief introduction to the basic notation and principles of queueing theory. While queueing theory has been appl...

This book serves as both a textbook and handbook on the benchmarking of systems and components used as building blocks of modern information and communication technology applications. It provides theoretical and practical foundations as well as an in-depth exploration of modern benchmarks and benchmark development. The book is divided into two part...

In this chapter, we provide an overview of established benchmarks for evaluating the performance of virtualization platforms. We focus on the SPEC VIRT series of industry-standard benchmarks released by SPEC (SPEC VIRT_SC 2010, SPEC VIRT_SC 2013, and SPEC VIRT Datacenter 2020) while also considering the VMmark benchmark released by VMware.

This chapter introduces statistical approaches for quantifying the variability and precision of measurements. The chapter starts by introducing the most common indices of dispersion for quantifying the variability, followed by defining basic concepts such as accuracy, precision, and resolution of measurements, as well as the distinction between sys...

In this chapter, we present a set of intuitively understandable metrics for characterizing the elasticity of a cloud platform including ways to aggregate them. The focus is on IaaS clouds; however, the presented approach can also be applied in the context of other types of cloud platforms. The metrics support evaluating both the accuracy and the ti...

This chapter presents an overview and retrospective on the emergence, development, and evolution of one of the industry’s most popular standard benchmarks for computing systems, the SPEC CPU benchmark suite by the Standard Performance Evaluation Corporation. For the newest version, CPU2017, we provide details on the benchmark architecture, workload...