Technical Report: A Trace-Based Performance Study of Autoscaling Workloads of Workflows in Datacenters

To improve customer experience, datacenter operators offer support for simplifying application and resource management. For example, running workloads of workflows on behalf of customers is desirable, but requires increasingly more sophisticated autoscaling policies, that is, policies that dynamically provision resources for the customer. Although selecting and tuning autoscaling policies is a challenging task for datacenter operators, so far relatively few studies investigate the performance of autoscaling for workloads of workflows. Complementing previous knowledge, in this work we propose the first comprehensive performance study in the field. Using trace-based simulation, we compare state-of-the-art autoscaling policies across multiple application domains, workload arrival patterns (e.g., burstiness), and system utilization levels. We further investigate the interplay between autoscaling and regular allocation policies, and the complexity cost of autoscaling. Our quantitative study focuses not only on traditional performance metrics and on state-of-the-art elasticity metrics, but also on time- and memory-related autoscaling-complexity metrics. Our main results give strong and quantitative evidence about previously unreported operational behavior, for example, that autoscaling policies perform differently across application domains and by how much they differ.Comment: Technical Report for the CCGrid 2018 submission "A Trace-Based Performance Study of Autoscaling Workloads of Workflows in Datacenters

The OpenDC Microservice Simulator: Design, Implementation, and Experimentation

Microservices is an architectural style that structures an application as a collection of loosely coupled services, making it easy for developers to build and scale their applications. The microservices architecture approach differs from the traditional monolithic style of treating software development as a single entity. Microservice architecture is becoming more and more adapted. However, microservice systems can be complex due to dependencies between the microservices, resulting in unpredictable performance at a large scale. Simulation is a cheap and fast way to investigate the performance of microservices in more detail. This study aims to build a microservices simulator for evaluating and comparing microservices based applications. The microservices reference architecture is designed. The architecture is used as the basis for a simulator. The simulator implementation uses statistical models to generate the workload. The compelling features added to the simulator include concurrent execution of microservices, configurable request depth, three load-balancing policies and four request execution order policies. This paper contains two experiments to show the simulator usage. The first experiment covers request execution order policies at the microservice instance. The second experiment compares load balancing policies across microservice instances.Comment: Bachelor's thesi

HPS-HDS:High Performance Scheduling for Heterogeneous Distributed Systems

Heterogeneous Distributed Systems (HDS) are often characterized by a variety of resources that may or may not be coupled with specific platforms or environments. Such type of systems are Cluster Computing, Grid Computing, Peer-to-Peer Computing, Cloud Computing and Ubiquitous Computing all involving elements of heterogeneity, having a large variety of tools and software to manage them. As computing and data storage needs grow exponentially in HDS, increasing the size of data centers brings important diseconomies of scale. In this context, major solutions for scalability, mobility, reliability, fault tolerance and security are required to achieve high performance. More, HDS are highly dynamic in its structure, because the user requests must be respected as an agreement rule (SLA) and ensure QoS, so new algorithm for events and tasks scheduling and new methods for resource management should be designed to increase the performance of such systems. In this special issues, the accepted papers address the advance on scheduling algorithms, energy-aware models, self-organizing resource management, data-aware service allocation, Big Data management and processing, performance analysis and optimization

An analysis of social gaming networks in online and face to face bridge communities

Online social games are Internet-based games that use the social networks formed by players to extend in-game functionality. For example, gamers participating in the BBO Fans community combine online bridge play with social networking. Despite an increase in the popularity of online social gaming—currently, there exist over one million online bridge players—, and of decades of research on social networks, the activity characteristics and the community structure of online social gaming remain relatively unknown. In this work we investigate and contrast these aspects for two bridge communities, BBO Fans (online) and Locomotiva (face to face). We propose the use of playing relationships instead of traditional social relationships such as friends and friends-of-friends. Using long-term, large-scale data we have collected from both the online and face to face bridge communities, we analyze user behavior, social network structure, and playing style in bridge communities. We find many similar characteristics in the two studied communities, but we also find more variation in the activity levels and fewer stable partnerships for the face to face bridge community