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  • 1.
    Ali-Eldin, Ahmed
    et al.
    Umeå University.
    Ilyushkin, Alexey
    Delft University of Technology, Delft, Netherlands.
    Ghit, Bogdan
    Delft University of Technology, Delft, Netherlands.
    Herbst, Nikolas Roman
    University of Würzburg, Würzburg, Germany.
    Papadopoulos, Alessandro
    Lund University, Lund, Sweden.
    Iosoup, Alexandru
    Delft University of Technology, Delft, Netherlands.
    Which Cloud Auto-Scaler Should I Use for my Application?: Benchmarking Auto-Scaling Algorithms2016In: Proceedings of the 7th ACM/SPEC on International Conference on Performance Engineering ICPE, Delft, Netherlands: ACM , 2016, p. 131-132Conference paper (Refereed)
  • 2.
    Angelopoulos, Konstantinos
    et al.
    University of Brighton.
    Papadopoulos, Alessandro
    Lund University.
    Souza, Vitor E. Silva
    Mylopoulos, John
    University of Toronto.
    Model Predictive Control for Software Systems with CobRA2016In: SEAMS '16 Proceedings of the 11th International Symposium on Software Engineering for Adaptive and Self-Managing Systems, Austin, Texas, United States: ACM , 2016, p. 35-46Conference paper (Refereed)
    Abstract [en]

    Self-adaptive software systems monitor their operation and adapt when their requirements fail due to unexpected phenomena in their environment. This paper examines the case where the environment changes dynamically over time and the chosen adaptation has to take into account such changes. In control theory, this type of adaptation is known as Model Predictive Control and comes with a well-developed theory and myriads of successful applications. The paper focuses on modelling the dynamic relationship between requirements and possible adaptations. It then proposes a controller that exploits this relationship to optimize the satisfaction of requirements relative to a cost-function. This is accomplished through a model-based framework for designing self-adaptive software systems that can guarantee a certain level of requirements satisfaction over time, by dynamically composing adaptation strategies when necessary. The proposed framework is illustrated and evaluated through a simulation of the Meeting-Scheduling System exemplar.

  • 3.
    Faragardi, Hamid Reza
    et al.
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Dehnavi, Saed
    University of Tehran, Iran.
    Kargahi, Mehdi
    Papadopoulos, Alessandro
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems. IS (Embedded Systems).
    Nolte, Thomas
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems. IS (Embedded Systems).
    A Time-Predictable Fog-Integrated Cloud Framework: One Step Forward in the Deployment of a Smart Factory2018In: CSI International Symposium on Real-Time and Embedded Systems and Technologies REST'18, 2018Conference paper (Refereed)
  • 4.
    Filieri, Antonio
    et al.
    Imperial College London, UK.
    Maggio, Martina
    Lund University, Sweden.
    Angelopoulos, Konstantinos
    University of Brighton, UK.
    D'Ippolito, Nicolas
    Gerostatopoulos, Ilias
    Hempel, Andreas
    Jamshidi, Pooyan
    Kalyvianaki, Evangelia
    Klein, Cristian
    Umeå University, Sweden.
    Krikava, Filip
    Misailovic, Sasa
    Papadopoulos, Alessandro
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Ray, Suprio
    Sharifloo, Amir M.
    Shevtsov, Stepan
    Ujma, Mateusz
    Vogel, Thomas
    Control Strategies for Self-Adaptive Software Systems2017In: ACM Transactions on Autonomous and Adaptive Systems, ISSN 1556-4665, E-ISSN 1556-4703, Vol. 11, no 4, article id 24Article in journal (Refereed)
    Abstract [en]

    The pervasiveness and growing complexity of software systems is challenging software engineering to de- sign systems that can adapt their behavior to withstand unpredictable, uncertain, and continuously chang- ing execution environments. Control theoretical adaptation mechanisms received a growing interest from the software engineering community in the last years for their mathematical grounding allowing formal guarantees on the behavior of the controlled systems. However, most of these mechanisms are tailored to specific applications and can hardly be generalized into broadly applicable software design and development processes. This paper discusses a reference control design process, from goal identification to the verification and validation of the controlled system. A taxonomy of the main control strategies is introduced, analyzing their applicability to software adaptation for both functional and non-functional goals. A brief extract on how to deal with uncertainty complements the discussion. Finally, the paper highlights a set of open challenges, both for the software engineering and the control theory research communities.

  • 5.
    Frasheri, Mirgita
    et al.
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Curuklu, Baran
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Ekström, Mikael
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Papadopoulos, Alessandro
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Adaptive Autonomy in a Search and Rescue ScenarioConference paper (Refereed)
  • 6.
    Gulisano, Vincenzo
    et al.
    Chalmers University of Technology, Göteborg, Sweden.
    Papadopoulos, Alessandro
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Nikolakopoulos, Yiannis
    Chalmers University of Technology, Göteborg, Sweden.
    Papatriantafilou, Marina
    Chalmers University of Technology, Göteborg, Sweden.
    Tsigas, Philippas
    Chalmers University of Technology, Göteborg, Sweden.
    Performance modeling of stream joins2017In: DEBS '17 Proceedings of the 11th ACM International Conference on Distributed and Event-based Systems, 2017, p. 191-202Conference paper (Refereed)
    Abstract [en]

    Streaming analysis is widely used in a variety of environments, from cloud computing infrastructures up to the network’s edge. In these contexts, accurate modeling of streaming operators’ performance enables fine-grained prediction of applications’ behavior without the need of costly monitoring. This is of utmost importance for computationally-expensive operators like stream joins, that observe throughput and latency very sensitive to rate-varying data streams, especially when deterministic processing is required. In this paper, we present a modeling framework for estimating the throughput and the latency of stream join processing. The model is presented in an incremental step-wise manner, starting from a centralized non-deterministic stream join and expanding up to a deterministic parallel stream join. The model describes how the dynamics of throughput and latency are influenced by the number of physical input streams, as well as by the amount of parallelism in the actual processing and the requirement for determinism. We present an experimental validation of the model with respect to the actual implementation. The proposed model can provide insights that are catalytic for understanding the behavior of stream joins against different system deployments, with special emphasis on the influences of determinism and parallelization.

  • 7.
    Ilyushkin, Alexey
    et al.
    Delft Univ Technol, Delft, Netherlands.
    Ali-Eldin, Ahmed
    Umeå Univ, Umeå, Sweden.
    Herbst, Nikolas
    Univ Wurzburg, Wurzburg, Germany.
    Bauer, Andre
    Univ Wurzburg, Wurzburg, Germany.
    Papadopoulos, Alessandro
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Epema, Dick
    Delft Univ Technol, Delft, Netherlands.
    Iosup, Alexandru
    Delft Univ Technol, Delft, Netherlands.
    An Experimental Performance Evaluation of Autoscalers for Complex Workflows2018In: ACM TRANSACTIONS ON MODELING AND PERFORMANCE EVALUATION OF COMPUTING SYSTEMS, ISSN 2376-3639, Vol. 3, no 2, article id UNSP 8Article in journal (Refereed)
    Abstract [en]

    Elasticity is one of the main features of cloud computing allowing customers to scale their resources based on the workload. Many autoscalers have been proposed in the past decade to decide on behalf of cloud customers when and how to provision resources to a cloud application based on the workload utilizing cloud elasticity features. However, in prior work, when a new policy is proposed, it is seldom compared to the state-of-the-art, and is often compared only to static provisioning using a predefined quality of service target. This reduces the ability of cloud customers and of cloud operators to choose and deploy an autoscaling policy, as there is seldom enough analysis on the performance of the autoscalers in different operating conditions and with different applications. In our work, we conduct an experimental performance evaluation of autoscaling policies, using as application model workflows, a popular formalism for automating resource management for applications with well-defined yet complex structures. We present a detailed comparative study of general state-of-the-art autoscaling policies, along with two new workflow-specific policies. To understand the performance differences between the seven policies, we conduct various experiments and compare their performance in both pairwise and group comparisons. We report both individual and aggregated metrics. As many workflows have deadline requirements on the tasks, we study the effect of autoscaling on workflow deadlines. Additionally, we look into the effect of autoscaling on the accounted and hourly based charged costs, and we evaluate performance variability caused by the autoscaler selection for each group of workflow sizes. Our results highlight the trade-offs between the suggested policies, how they can impact meeting the deadlines, and how they perform in different operating conditions, thus enabling a better understanding of the current state-of-the-art.

  • 8.
    Ilyushkin, Alexey
    et al.
    Delft University of Technology, Netherlands.
    Ali-Eldin, Ahmed
    Umeå University, Sweden.
    Herbst, Nikolas Roman
    University of Würzburg, Germany.
    Papadopoulos, Alessandro
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Ghit, Bogdan
    Delft University of Technology, Netherlands.
    Epema, Dick
    Delft University of Technology, Netherlands.
    Iosoup, Alexandru
    Delft University of Technology, Netherlands.
    An Experimental Performance Evaluation of Autoscaling Algorithms for Complex Workflows2016In: ACM Symposium on Cloud Computing 2016 SoCC 16, 2016Conference paper (Refereed)
  • 9.
    Ilyushkin, Alexey
    et al.
    Delft University of Technology, Netherlands.
    Ali-Eldin, Ahmed
    Umeå University, Sweden.
    Herbst, Nikolas Roman
    University of Würzburg, Germany.
    Papadopoulos, Alessandro
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Ghit, Bogdan
    Delft University of Technology, Netherlands.
    Epema, Dick
    Delft University of Technology, Netherlands.
    Iosoup, Alexandru
    Delft University of Technology, Netherlands.
    An Experimental Performance Evaluation of Autoscaling Algorithms for Complex Workflows2017In: ICPE '17 Proceedings of the 8th ACM/SPEC on International Conference on Performance Engineering, 2017, p. 75-86Conference paper (Refereed)
    Abstract [en]

    Simplifying the task of resource management and scheduling for customers, while still delivering complex Quality-of-Service (QoS), is key to cloud computing. Many autoscaling policies have been proposed in the past decade to decide on behalf of cloud customers when and how to provision resources to a cloud application utilizing cloud elasticity features. However, in prior work, when a new policy is proposed, it is seldom compared to the state-of-the-art, and is often compared only to static provisioning using a predefined QoS target. This reduces the ability of cloud customers and of cloud operators to choose and deploy an autoscaling policy. In our work, we conduct an experimentalperformance evaluation of autoscaling policies, using as application model workflows, a commonly used formalism for automating resource management for applications with well-defined yet complex structure. We present a detailed comparative study of general state-of-the-art autoscaling policies, along with two new workflow-specific policies. To understand the performance differences between the 7 policies, we conduct various forms of pairwise and group comparisons. We report both individual and aggregated metrics. Our results highlight the trade-offs between the suggested policies, and thus enable a better understanding of the current state-of-the-art.

  • 10.
    Lakew, Ewnetu Bayuh
    et al.
    Umeå University, Sweden.
    Papadopoulos, Alessandro
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Maggio, Martina
    Lund University, Sweden.
    Klein, Cristian
    Umeå University, Sweden.
    Elmroth, Erik
    Umeå University, Sweden.
    KPI-agnostic Control for Fine-Grained Vertical Elasticity2017In: 17th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing CCGrid 17, 2017, p. 589-598Conference paper (Refereed)
    Abstract [en]

    Applications hosted in the cloud have become indispensable in several contexts, with their performance often being key to business operation and their running costs needing to be minimized. To minimize running costs, most modern virtualization technologies such as Linux Containers, Xen, and KVM offer powerful resource control primitives for individual provisioning -- that enable adding or removing of fraction of cores and/or megabytes of memory with granularities of seconds. Despite the technology being ready, there is a lack of proper techniques for fine-grained resource allocation, because there is an inherent challenge in determining the correct composition of resources an application needs, with varying workload, to ensure deterministic performance. This paper presents a control-based approach for the management of multiple resources, accounting for the resource consumption, together with the application performance, enabling fine-grained vertical elasticity. The control strategy ensures that the application meets the target performance indicators, consuming as less resources as possible. We carried out an extensive set of experiments using different applications -- interactive with response-time requirements, as well as non-interactive with throughput desires -- by varying the workload mixes of each application over time. The results demonstrate that our solution precisely provides guaranteed performance while at the same time avoiding both resource over- and under-provisioning.

  • 11.
    Leva, Alberto
    et al.
    Politecnico di Milano, Italy.
    Papadopoulos, Alessandro
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Modelling and Control of Big Data Frameworks2017In: IFAC-PapersOnLine, Vol. 50, 2017, Vol. 50, p. 6110-6115, article id 1Conference paper (Refereed)
    Abstract [en]

    We present a model library conceived to design and assess critical components of big data frameworks, with a control-centric approach. The library adopts the object-oriented paradigm, using the Modelica language. Continuous-time and algorithmic models can be mixed, allowing to represent control code with high fidelity, and to reduce the simulation effort to the minimum required. We discuss the used modelling principles, describe the library, and show some design examples.

  • 12.
    Leva, Alberto
    et al.
    Politecnico di Milano.
    Terraneo, Federico
    Politecnico di Milano.
    Rinaldi, Luigi
    Politecnico di Milano.
    Papadopoulos, Alessandro
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems. Department of Automatic Control, Lund University, Lund, Sweden.
    Maggio, Martina
    Department of Automatic Control, Lund University, Lund, Sweden.
    High-Precision Low-Power Wireless Nodes' Synchronization via Decentralized Control2016In: IEEE Transactions on Control Systems Technology, ISSN 1063-6536, E-ISSN 1558-0865, Vol. 24, no 4, p. 1279-1293Article in journal (Refereed)
    Abstract [en]

    Abstract: Time synchronization is crucial for wireless sensor networks (WSNs), where operations often rely on time ordering of events. WSNs are deployed in different scenarios, and therefore their timing requirements are often related to the peculiar characteristics of the specific environment they have to act in. Synchronization is anyway always an issue: transactional applications need monotonicity of the nodes' clocks to avoid time reversal, ultralow power applications call for minimal overhead to allow for low-duty-cycle operation, applications facing extreme environments have to maintain the needed precision in the presence of unforeseen thermal drift, and so on. Specially, control applications on battery-powered devices, where timing is an issue and low-power operation is highly desired, benefit from synchronization. However, to date, the problem of synchronization has been differently faced depending on the application domain. This paper proposes a general solution to the problem of synchronization in WSNs, which seamlessly integrates with the radio stack. In addition, it guarantees monotonic and continuous node clocks with low overhead for the infrastructure. The solution is based on a decentralized control scheme that is stable and robust to thermal stress, without the need for temperature measurements. The control scheme is simulated and implemented on real WSN nodes. The efficiency of the scheme is evaluated with simulations and experiments, providing insights on the maximum synchronization error between nodes, on the communication overhead, and on the limited nodes' power consumption. The solution is also compared with state-of-the-art alternatives.

  • 13.
    Maggio, M.
    et al.
    Lund Univ, Lund, Sweden.
    Papadopoulos, Alessandro
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Filieri, A.
    Imperial Coll London, London, England.
    Hoffmann, H.
    Univ Chicago, Chicago, USA.
    Automated Control of Multiple Software Goals using Multiple Actuators2017In: ESEC/FSE 2017: PROCEEDINGS OF THE 2017 11TH JOINT MEETING ON FOUNDATIONS OF SOFTWARE ENGINEERING, 2017, p. 373-384Conference paper (Refereed)
    Abstract [en]

    Modern software should satisfy multiple goals simultaneously: it should provide predictable performance, be robust to failures, handle peak loads and deal seamlessly with unexpected conditions and changes in the execution environment. For this to happen, software designs should account for the possibility of runtime changes and provide formal guarantees of the software's behavior. Controltheory is one of the possible design drivers for runtime adaptation, but adopting control theoretic principles often requires additional, specialized knowledge. To overcome this limitation, automatedmethodologies have been proposed to extract the necessary information from experimental data and design a control system for runtime adaptation. These proposals, however, only process one goal at a time, creating a chain of controllers. In this paper, we propose and evaluate the first automated strategy that takes into account multiple goals without separating them into multiple control strategies. Avoiding the separation allows us to tackle a larger class of problems and provide stronger guarantees. We test our methodology's generality with three case studies that demonstrate its broad applicability in meeting performance, reliability, quality, security, and energy goals despite environmental or requirements changes.

  • 14.
    Maggio, Martina
    et al.
    Lund University, Sweden.
    Abdelzaher, Tarek
    University of Illinois at Urbana Champaign, USA.
    Esterle, Lukas
    Vienna University of Technology, Austria.
    Giese, Holger
    Hasso-Plattner-Institut fr Softwaresystemtechnik GmbH, Germany.
    Kephart, Jeffrey O.
    Thomas J. Watson Research Center, Hawthorne, NY, USA.
    Mengshoel, Ole
    Carnegie Mellon University, USA.
    Papadopoulos, Alessandro
    Lund University, Sweden.
    Robertsson, Anders
    Lund University, Sweden.
    Wolter, Katinka
    Freie Universität Berlin, Germany.
    Self-adaptation for Individual Self-aware Computing Systems2017In: Self-Aware Computing Systems / [ed] S. Kounev, J. O. Kephart, A. Milenkoski, and X. Zhu, Springer International Publishing , 2017, p. 375-399Chapter in book (Other academic)
    Abstract [en]

    This chapter discusses the role of self-awareness for adaptation at the individual level, when one single entity receives inputs both from itself or some of its components and from the external environment and uses the input to adjust to the current conditions. The chapter reviews the most widely used techniques for self-adaptation and identifies the role of self-awareness for each of the techniques and the metrics used to evaluate these techniques. Finally, we pave the way toward the following chapter, which discusses multiple entity adaptation, by introducing the interaction of different self-adaptation techniques at the level of the single individual.

  • 15.
    Maggio, Martina
    et al.
    Lund University, Sweden.
    Papadopoulos, Alessandro
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Filieri, Antonio
    Imperial College London, UK.
    Hoffmann, Henry
    University of Chicago, USA.
    Self-Adaptive Video Encoder: Comparison of Multiple Adaptation Strategies Made Simple2017In: 12th International Symposium on Software Engineering for Adaptive and Self-Managing Systems SEAMS 17, Buenos Aires, Argentina, 2017, p. 123-128, article id 7968140Conference paper (Refereed)
    Abstract [en]

    This paper presents an adaptive video encoder that can be used to compare the behavior of different adaptation strategies using multiple actuators to steer the encoder towards a global goal, composed of multiple conflicting objectives. A video camera produces frames that the encoder manipulates with the objective of matching some space requirement to fit a given communication channel. A second objective is to maintain a given similarity index between the manipulated frames and the original ones. To achieve the goal, the software can change three parameters: the quality of the encoding, the noise reduction filter radius and the sharpening filter radius. In most cases the objectives -- small encoded size and high quality -- conflict, since a larger frame would have a higher similarity index to its original counterpart. This makes the problem difficult from the control perspective and makes the case study appealing to compare different adaptation strategies.

  • 16.
    Moreno, Gabriel
    et al.
    Carnegie Mellon University, USA.
    Papadopoulos, Alessandro
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Angelopoulos, Konstantinos
    University of Brighton, UK.
    Camara Moreno, Javier
    Carnegie Mellon University, USA.
    Schmerl, Bradley
    Carnegie Mellon University, USA.
    Comparing Model-Based Predictive Approaches to Self-Adaptation: CobRA and PLA2017In: 12th International Symposium on Software Engineering for Adaptive and Self-Managing Systems SEAMS 17, 2017, p. 42-53, article id 7968131Conference paper (Refereed)
    Abstract [en]

    Modern software-intensive systems must often guarantee certain quality requirements under changing run-time conditions and high levels of uncertainty. Self-adaptation has proven to be an effective way to engineer systems that can address such challenges, but many of these approaches are purely reactive and adapt only after a failure has taken place. To overcome some of the limitations of reactive approaches (e.g., lagging behind environment changes and favoring short-term improvements), recent proactive self-adaptation mechanisms apply ideas from control theory, such as model predictive control (MPC), to improve adaptation. When selecting which MPC approach to apply, the improvement that can be obtained with each approach is scenario-dependent, and so guidance is needed to better understand how to choose an approach for a given situation. In this paper, we compare CobRA and PLA, two approaches that are inspired by MPC. CobRA is a requirements-based approach that applies control theory, whereas PLA is architecture-based and applies stochastic analysis. We compare the two approaches applied to RUBiS, a benchmark system for web and cloud application performance, discussing the required expertise needed to use both approaches and comparing their run-time performance with respect to different metrics.

  • 17.
    Mubeen, Saad
    et al.
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Abbaspour Asadollah, Sara
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Papadopoulos, Alessandro
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Ashjaei, Seyed Mohammad Hossein
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Pei-Breivold, Hongyu
    ABB Corporate Research, Sweden.
    Behnam, Moris
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems. IS (Embedded Systems).
    Management of Service Level Agreements for Cloud Services in IoT: A Systematic Mapping Study2017In: IEEE Access, E-ISSN 2169-3536, no 99Article in journal (Refereed)
    Abstract [en]

    Cloud computing and Internet of Things (IoT) are computing technologies that provide services to consumers and businesses, allowing organizations to become more agile and flexible. Therefore, ensuring Quality of Service (QoS) through Service Level Agreements (SLAs) for such cloud-based services is crucial for both the service providers and service consumers. As SLAs are critical for cloud deployments and wider adoption of cloud services, the management of SLAs in cloud and IoT has thus become an important and essential aspect. This paper investigates the existing research on the management of SLAs in IoT applications that are based on cloud services. For this purpose, a Systematic Mapping study (a well-defined method) is conducted to identify the published research results that are relevant to SLAs. The paper identifies 328 primary studies and categorizes them into seven main technical classifications: SLA management, SLA definition, SLA modeling, SLA negotiation, SLA monitoring, SLA violation and trustworthiness, and SLA evolution. The paper also summarizes the research types, research contributions, and demographic information in these studies. The evaluation of the results show that most of the approaches for managing SLAs are applied in academic or controlled experiments with limited industrial settings rather than in real industrial environments. Many studies focus on proposal models and methods to manage SLAs, and there is a lack of focus on the evolution perspective and a lack of adequate tool support to facilitate practitioners in their SLA management activities. Moreover, the scarce number of studies focusing on concrete metrics for qualitative or quantitative assessment of QoS in SLAs urges the need for in-depth research on metrics definition and measurements for SLAs.

  • 18.
    Papadopoulos, Alessandro
    et al.
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Abbaspour Asadollah, Sara
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Ashjaei, Seyed Mohammad Hossein
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems. Arcticus Systems AB, Järfälla, Sweden.
    Mubeen, Saad
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems. Arcticus Systems AB, Järfälla, Sweden.
    Pei Breivold, Hongyu
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems. ABB Corporate Research, Sweden.
    Behnam, Moris
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    SLAs for Industrial IoT: Mind the Gap2017In: The 4th International Symposium on Inter-cloud and IoT (ICI 2017) ICI'17, 2017, p. 75-78Conference paper (Refereed)
    Abstract [en]

    Cloud computing and Internet of Things (IoT) are computing technologies that provide services to consumers and businesses, allowing organizations to become more agile and flexible. The potential business values that cloud consumers can achieve depend a lot on the quality of service in the provided cloud services. Therefore, ensuring the quality of service through service-level agreements (SLA) for such cloud-based services is crucial for both the service providers and service consumers. As SLA is critical for cloud deployments and wider adoption of cloud services, the management of SLA in cloud and IoT has thus become an important and essential issue. In this paper we provide an understanding of the current status and maturity level of SLA management in industrial IoT and academic efforts in this field. We also conduct a preliminary survey of current research on SLA management in order to identify open challenges and gaps that need to be addressed in future research directions. In particular, we investigate how to provide useful SLA management support adapted to the maturity level and current industrial practices, and shorten the gap between academia and industry.

  • 19.
    Papadopoulos, Alessandro
    et al.
    Lund University.
    Ali-Eldin, Ahmed
    Umeå University.
    Årzén, Karl-Erik
    Lund University.
    Tordsson, Johan
    Umeå University.
    Elmroth, Erik
    Umeå University.
    PEAS: A Performance Evaluation Framework for Auto-Scaling Strategies in Cloud Applications2016In: ACM Trans. Model. Perform. Eval. Comput. Syst. TOMPECS, ISSN 2376-3639, Vol. 1, no 4, p. 1-31Article in journal (Refereed)
    Abstract [en]

    Numerous auto-scaling strategies have been proposed in the past few years for improving various Quality of Service (QoS) indicators of cloud applications, for example, response time and throughput, by adapting the amount of resources assigned to the application to meet the workload demand. However, the evaluation of a proposed auto-scaler is usually achieved through experiments under specific conditions and seldom includes extensive testing to account for uncertainties in the workloads and unexpected behaviors of the system. These tests by no means can provide guarantees about the behavior of the system in general conditions. In this article, we present a Performance Evaluation framework for Auto-Scaling (PEAS) strategies in the presence of uncertainties. The evaluation is formulated as a chance constrained optimization problem, which is solved using scenario theory. The adoption of such a technique allows one to give probabilistic guarantees of the obtainable performance. Six different auto-scaling strategies have been selected from the literature for extensive test evaluation and compared using the proposed framework. We build a discrete event simulator and parameterize it based on real experiments. Using the simulator, each auto-scaler’s performance is evaluated using 796 distinct real workload traces from projects hosted on the Wikimedia foundations’ servers, and their performance is compared using PEAS. The evaluation is carried out using different performance metrics, highlighting the flexibility of the framework, while providing probabilistic bounds on the evaluation and the performance of the algorithms. Our results highlight the problem of generalizing the conclusions of the original published studies and show that based on the evaluation criteria, a controller can be shown to be better than other controllers.

  • 20.
    Papadopoulos, Alessandro
    et al.
    Department of Automatic Control, Lund University, Lund, Sweden.
    Bascetta, Luca
    Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, Milano, Italy.
    Ferretti, Gianni
    Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, Milano, Italy.
    Generation of Human Walking Paths2016In: Autonomous Robots, ISSN 0929-5593, E-ISSN 1573-7527, Vol. 40, no 1, p. 59-75Article in journal (Refereed)
    Abstract [en]

    This work investigates the way humans plan their paths in a goal-directed motion, assuming that a person acts as an optimal controller that plans the path minimizing a certain (unknown) cost function. Taking this viewpoint, the problem can be formulated as an inverse optimal control one, i.e., starting from control and state trajectories one wants to figure out the cost function used by a person while planning the path. The so-obtained model can be used to support the design of safe human–robot interaction systems, as well as to plan human-like paths for humanoid robots. To test the envisaged ideas, a set of walking paths of different volunteers were recorded using a motion capture facility. The collected data were used to compare two solutions to the inverse optimal control problem coming from the literature to a novel one. The obtained results, ranked using the discrete Fréchet distance, show the effectiveness of the proposed approach.

  • 21.
    Papadopoulos, Alessandro
    et al.
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Bini, E.
    University of Turin, Turin, Italy.
    Baruah, S.
    Washington University, St. Louis, MO, United States.
    Burns, A.
    University of York, York, United Kingdom.
    AdaptMC: A control-theoretic approach for achieving resilience in mixed-criticality systems2018In: Leibniz International Proceedings in Informatics, LIPIcs, Schloss Dagstuhl- Leibniz-Zentrum fur Informatik GmbH, Dagstuhl Publishing , 2018Conference paper (Refereed)
    Abstract [en]

    A system is said to be resilient if slight deviations from expected behavior during run-time does not lead to catastrophic degradation of performance: minor deviations should result in no more than minor performance degradation. In mixed-criticality systems, such degradation should additionally be criticality-cognizant. The applicability of control theory is explored for the design of resilient run-time scheduling algorithms for mixed-criticality systems. Recent results in control theory have shown how appropriately designed controllers can provide guaranteed service to hardreal- time servers; this prior work is extended to allow for such guarantees to be made concurrently to multiple criticality-cognizant servers. The applicability of this approach is explored via several experimental simulations in a dual-criticality setting. These experiments demonstrate that our control-based run-time schedulers can be synthesized in such a manner that bounded deviations from expected behavior result in the high-criticality server suffering no performance degradation and the lower-criticality one, bounded performance degradation.

  • 22.
    Papadopoulos, Alessandro
    et al.
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Klein, Cristian
    Umeå University.
    Maggio, Martina
    Lund University.
    Dürango, Jonas
    Lund University.
    Dellkrantz, Manfred
    Lund University.
    Hernandez-Rodriguez, Francisco
    Umeå University.
    Elmroth, Erik
    Umeå University.
    Årzén, Karl-Erik
    Lund University.
    Control-Based Load-Balancing Techniques: Analysis and Performance Evaluation via a Randomized Optimization Approach2016In: Control Engineering Practice, ISSN 0967-0661, E-ISSN 1873-6939, Vol. 52, p. 24-34Article in journal (Refereed)
    Abstract [en]

    Cloud applications are often subject to unexpected events like flashcrowds and hardware failures. Users that expect a predictable behavior may abandon an unresponsive application when these events occur. Researchers and engineers addressed this problem on two separate fronts: first, they introduced replicas – copies of the application with the same functionality – for redundancy and scalability; second, they added a self-adaptive feature called brownout inside cloud applications to bound response times by modulating user experience. The presence of multiple replicas requires a dedicated component to direct incoming traffic: a load-balancer. Existing load-balancing strategies based on response times interfere with the response time controller developed for brownout-compliant applications. In fact, the brownout approach bounds response times using a control action. Hence, the response time, that was used to aid load-balancing decision, is not a good indicator of how well a replica is performing. To fix this issue, this paper reviews some proposal for brownout-aware load-balancing and provides a comprehensive experimental evaluation that compares them. To provide formal guarantees on the load-balancing performance, we use a randomized optimization approach and apply the scenario theory. We perform an extensive set of experiments on a real machine, extending the popular lighttpd web server and load-balancer, and obtaining a production-ready implementation. Experimental results show an improvement of the user experience over Shortest Queue First (SQF)—believed to be near-optimal in the non-adaptive case. The improved user experience is obtained preserving the response time predictability.

  • 23.
    Papadopoulos, Alessandro
    et al.
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Krzywda, Jakub
    Umea Univ, Dept Comp Sci, Umea, Sweden..
    Elmroth, Erik
    Umea Univ, Dept Comp Sci, Umea, Sweden..
    Maggio, Martina
    Lund Univ, Dept Automat Control, Lund, Sweden..
    Power-Aware Cloud Brownout: response time and power consumption control2018In: 2017 IEEE 56TH ANNUAL CONFERENCE ON DECISION AND CONTROL (CDC), 2018, p. 2686-2691Conference paper (Refereed)
    Abstract [en]

    Cloud computing infrastructures are powering most of the web hosting services that we use at all times. A recent failure in the Amazon cloud infrastructure made many of the website that we use on a hourly basis unavailable(1). This illustrates the importance of cloud applications being able to absorb peaks in workload, and at the same time to tune their power requirements to the power and energy capacity offered by the data center infrastructure. In this paper we combine an established technique for response time control - brownout - with power capping. We use cascaded control to take into account both the need for predictability in the response times (the inner loop), and the power cap (the outer loop). We execute tests on real machines to determine power usage and response times models and extend an existing simulator. We then evaluate the cascaded controller approach with a variety of workloads and both open-and closed-loop client models.

  • 24.
    Papadopoulos, Alessandro
    et al.
    Department of Automatic ControlLund UniversityLundSweden.
    Leva, Alberto
    Dipartimento di Elettronica, Informazione e BioingegneriaPolitecnico di MilanoMilanItaly.
    A model partitioning method based on dynamic decoupling for the efficient simulation of multibody systems2015In: Multibody System Dynamics MUBO, ISSN 1384-5640, Vol. 34, no 2, p. 163-190Article in journal (Refereed)
    Abstract [en]

    The presence of different time scales in a dynamic model significantly hampers the efficiency of its simulation. In multibody systems the fact is particularly relevant, as the mentioned time scales may be very different, due, for example, to the coexistence of mechanical components controled by electronic drive units, and may also appear in conjunction with significant nonlinearities. This paper proposes a systematic technique, based on the principles of dynamic decoupling, to partition a model based on the time scales that are relevant for the particular simulation studies to be performed and as transparently as possible for the user. In accordance with said purpose, peculiar to the technique is its neat separation into two parts: a structural analysis of the model, which is general with respect to any possible simulation scenario, and a subsequent decoupled integration, which can conversely be (easily) tailored to the study at hand. Also, since the technique does not aim at reducing but rather at partitioning the model, the state space and the physical interpretation of the dynamic variables are inherently preserved. Moreover, the proposed analysis allows us to define some novel indices relative to the separability of the system, thereby extending the idea of “stiffness” in a way that is particularly keen to its use for the improvement of simulation efficiency, be the envisaged integration scheme monolithic, parallel, or even based on cosimulation. Finally, thanks to the way the analysis phase is conceived, the technique is naturally applicable to both linear and nonlinear models. The paper contains a methodological presentation of the proposed technique, which is related to alternatives available in the literature so as to evidence the peculiarities just sketched, and some application examples illustrating the achieved advantages and motivating the major design choice from an operational viewpoint.

  • 25.
    Papadopoulos, Alessandro
    et al.
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Maggio, Martina
    Lund University, Sweden.
    Leva, Alberto
    Politecnico di Milano, Italy.
    Bini, Enrico
    Scuola Superiore Sant'Anna, Italy.
    Hard Real-Time Guarantees in Feedback-based Resource Reservations2017In: 38th IEEE Real-Time Systems Symposium (journal never presented on conference) RTSS 17, 2017Conference paper (Refereed)
  • 26.
    Papadopoulos, Alessandro
    et al.
    Lund University, Lund, Sweden.
    Maggio, Martina
    Lund University, Lund, Sweden.
    Leva, Alberto
    Politecnico di Milano, Milano, Italy.
    Bini, Enrico
    Scuola Superiore Sant’Anna, Pisa, Italy.
    Hard Real-Time Guarantees in Feedback-based Resource Reservations2015In: Real-Time Systems RTSJ, ISSN 0922-6443, Vol. 51, no 3, p. 221-246Article in journal (Refereed)
    Abstract [en]

    Resource reservation is a technique that allows isolating applications from interfering among each other. In the most classic setting, this method requires the periodic allocation of a given budget of resource over time. However, in reality, the actual budget allocation may deviate from its ideal value. Examples of causes of this deviation are: the presence of a system tick, the usage of shared resources, the self-blocking on I/O operations, etc. Since control techniques are an effective mean to deal with uncertainties and disturbances, unknown at design time but bounded, in this paper we propose to use feedback to achieve the target budget allocation, which may have deviated due to on-line events. The proposed scheme, called Self-Adaptive Server (SAS), is described and analyzed. We prove that the controller gain, which maximizes the resource delivered to the application, is (3-sqrt(5))/2. We also implemented the scheduler on a lightweight operating system for a microcontroller. Thanks to the extremely simple implementation, SAS servers are well suited for low-overhead resource isolation mechanisms with proved real-time guarantees.

  • 27.
    Papadopoulos, Alessandro
    et al.
    Lund University, Sweden.
    Maggio, Martina
    Lund University, Sweden.
    Terraneo, Federico
    Politecnico di Milano, Italy.
    Leva, Alberto
    Politecnico di Milano, Italy.
    A Dynamic Modelling Framework for Control-based Computing System Design2015In: Mathematical and Computer Modelling of Dynamical Systems, ISSN 1387-3954, E-ISSN 1744-5051, Vol. 21, no 3, p. 251-271Article in journal (Refereed)
    Abstract [en]

    This manuscript proposes a novel viewpoint on computing systems’ modelling. The classical approach is to consider fully functional systems and model them, aiming at closing some external loops to optimize their behaviour. On the contrary, we only model strictly physical phenomena, and realize the rest of the system as a set of controllers. Such an approach permits rigorous assessment of the obtained behaviour in mathematical terms, which is hardly possible with the heuristic design techniques, that were mainly adopted to date. The proposed approach is shown at work with three relevant case studies, so that a significant generality can be inferred from it.

  • 28.
    Papadopoulos, Alessandro
    et al.
    Politecnico di Milano, Italy.
    Prandini, Maria
    Politecnico di Milano, Italy.
    Model reduction of switched affine systems2016In: Automatica, ISSN 0005-1098, E-ISSN 1873-2836, Vol. 70, p. 57-65Article in journal (Refereed)
    Abstract [en]

    This paper addresses model reduction and extends balanced truncation to the class of switched affine systems with endogenous switching. The switched affine system is rewritten as a switched linear one with state resets that account for the affine terms. Balanced truncation can then be applied to each mode dynamics, independently. As a result, different reduced state vectors are associated with the different modes, and reset maps are here appropriately redefined so as to account and compensate for this mismatch, possibly preserving the continuity of the output. The overall behavior of the reduced switched system is determined by both the selected reduction per mode and the adopted reset maps. In this paper, we consider a stochastic setting and propose a randomized method for the selection of the reduced order. The performance of the proposed approach is illustrated through a multi-room temperature control example.

  • 29.
    Souza, A.
    et al.
    Department of Computing Science, Umea University, Sweden.
    Papadopoulos, Alessandro
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Tomas, L.
    Department of Computing Science, Umea University, Sweden.
    Gilbert, D.
    Red Hat Inc., United States.
    Tordsson, J.
    Department of Computing Science, Umea University, Sweden.
    Hybrid adaptive checkpointing for virtual machine fault tolerance2018In: Proceedings - 2018 IEEE International Conference on Cloud Engineering, IC2E 2018, Institute of Electrical and Electronics Engineers Inc. , 2018, p. 12-22Conference paper (Refereed)
    Abstract [en]

    Active Virtual Machine (VM) replication is an application independent and cost-efficient mechanism for high availability and fault tolerance, with several recently proposed implementations based on checkpointing. However, these methods may suffer from large impacts on application latency, excessive resource usage overheads, and/or unpredictable behavior for varying workloads. To address these problems, we propose a hybrid approach through a Proportional-Integral (PI) controller to dynamically switch between periodic and on-demand check-pointing. Our mechanism automatically selects the method that minimizes application downtime by adapting itself to changes in workload characteristics. The implementation is based on modifications to QEMU, LibVirt, and OpenStack, to seamlessly provide fault tolerant VM provisioning and to enable the controller to dynamically select the best checkpointing mode. Our evaluation is based on experiments with a video streaming application, an e-commerce benchmark, and a software development tool. The experiments demonstrate that our adaptive hybrid approach improves both application availability and resource usage compared to static selection of a checkpointing method, with application performance gains and neglectable overheads.

  • 30.
    Terraneo, F.
    et al.
    Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, Milano, Italy.
    Papadopoulos, Alessandro
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Leva, A.
    Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, Milano, Italy.
    Prandini, M.
    Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, Milano, Italy.
    FLOPSYNC-QACS: Quantization-aware clock synchronization for wireless sensor networks2017In: Journal of systems architecture, ISSN 1383-7621, E-ISSN 1873-6165, Vol. 80, p. 77-84Article in journal (Refereed)
    Abstract [en]

    Distributed real-time systems often rely on clock synchronization. However, the achievement of precise synchronization in Wireless Sensor Networks (WSNs) is hampered by competing design challenges, which finally causes many WSN hardware platforms to rely on low frequency clock crystal for local timebase provision. Although this solution is inexpensive and with a remarkably low energy consumption, it limits the resolution at which time can be measured. The FLOPSYNC synchronization scheme was then introduced to compensate for possible quartz crystal imperfections. The main limitation of FLOPSYNC is that it does not account for the effects of quantization. In this paper we propose a switched control variant of the base FLOPSYNC scheme to address quantization explicitly in the compensator design, providing clock synchronization in cost-sensitive WSN node platforms with a minimal additional overhead. Experimental evidence is given that the approach reaches a synchronization error of at most 1 clock tick in a real WSN.

  • 31.
    Terraneo, Federico
    et al.
    Politecnico di Milano, Italy.
    Papadopoulos, Alessandro
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Leva, Alberto
    Politecnico di Milano, Italy.
    Prandini, Maria
    Politecnico di Milano, Italy.
    FLOPSYNC-QACS: Quantization- Aware Clock Synchronization for Wireless Sensor Networks2016In: IEEE 4th International Workshop on Real-Time Computing and Distributed systems in Emerging Applications REACTION'16, 2016Conference paper (Refereed)
    Abstract [en]

    The development of distributed real-time systems often relies on clock synchronization. However, achieving pre- cise synchronization in the field of Wireless Sensor Networks (WSNs) is hampered by competing design challenges, such as energy consumption and cost constraints, e.g., in Internet of Things applications. For these reasons many WSN hardware platforms rely on a low frequency clock crystal to provide the local timebase. Although this solution is inexpensive and allows for a remarkably low energy consumption, it limits the resolution at which time can be measured. The FLOPSYNC synchronization scheme provides low-energy synchronization that takes into account the quartz crystal imperfections. The main limitation of the approach are the effects of quantization. In this paper we propose a clock synchronization scheme that explicitly takes into account quantization effects caused by low frequency clock crystal, thus addressing the clock syn- chronization issue in cost-sensitive WSN node platforms. The solution adopts switched control for minimizing the effect of quantization, with minimal overhead. We provide experimental evidence that the approach manages to reach a synchronization error of at most 1 clock tick in a real WSN.

  • 32.
    Tärneberg, William
    et al.
    Lund University, Sweden.
    Papadopoulos, Alessandro
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Mehta, Amardeep
    Umeå University, Sweden.
    Tordsson, Johan
    Umeå University, Sweden.
    Kihl, Maria
    Lund University, Sweden.
    Distributed Approach to the Holistic Resource Management of a Mobile Cloud Network2017In: Proceedings - 2017 IEEE 1st International Conference on Fog and Edge Computing, ICFEC 2017, 2017, p. 51-60, article id 8014359Conference paper (Refereed)
    Abstract [en]

    The Mobile Cloud Network is an emerging cost and capacity heterogeneous distributed cloud topological paradigm that aims to remedy the application performance constraints imposed by centralised cloud infrastructures. A centralised cloud infrastructure and the adjoining Telecom network will struggle to accommodate the exploding amount of traffic generated by forthcoming highly interactive applications. Cost effectively managing a Mobile Cloud Network computing infrastructure while meeting individual application’s performance goals is nontrivial and is at the core of our contribution. Due to the scale of a Mobile Cloud Network, a centralised approach is infeasible. Therefore, in this paper a distributed algorithm that addresses these challenges is presented. The presented approach works towards meeting individual application’s performance objectives, constricting system-wide operational cost, and mitigating resource usage skewness. The presented distributed algorithm does so by iteratively and independently acting on the objectives of each component with a common heuristic objective function. Systematic evaluations reveal that the presented algorithm quickly converges and performs near optimal in terms of system-wide operational cost and application performance, and significantly outperforms similar na¨ıve and random methods.

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