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Because data collection in HPC systems happens on the nodes and is easily related to the job running on the node, tools presenting the data and subsequent analyses to the user generally present them at the job level. Our position is that this is the wrong level of abstraction and thus limits the value of the analyses, often dissuading users from using any of the offered tools. In this paper we present...
The combination of fast online anomaly detection and offline learning is a vital element of operations in large-scale datacenters and utility clouds. Given ever-increasing datacenter sizes coupled with the complexities of systems software, applications, and workload patterns, such anomaly detection must operate continuous and real-time at runtime. Further, detection should function for both hardware...
Decision guidance models are a means for design space exploration and documentation. In this paper, we present decision guidance models for microservice monitoring. The selection of a monitoring system is an essential part of each microservice architecture due to the high level of dynamic structure and behavior of such a system. We present decision guidance models for generation of monitoring data,...
Trends in industrial automation systems are placing more importance on using streams of digitized data to perform various automation functions in real-time, e.g., power, process, and factory automation. To ensure high reliability and availability, individual devices or (sub-)systems thereof need to be tested with respect to their expected real-time behavior in the system context at various stages...
Coupled application workflows composed of applications implemented using task-based models present new coupling and data exchange challenges, due to the asynchronous interaction and coupling behaviors between tasks of the component applications. In this paper, we present an adaptive data placement approach that addresses these challenges by dynamically adjusting to the asynchronous coupling patterns...
The maturity of hardware virtualization has motivated Communication Service Providers (CSPs) to apply thisparadigm to network services. Virtual Network Functions (VNFs)result from this trend and raise new dependability challengesrelated to network softwarisation that are still not thoroughlyexplored. This paper describes a new approach to detect ServiceLevel Agreements (SLAs) violations and preliminary...
Companies are increasingly incorporating commercial Business Process Management Systems (BPMSs) as mechanisms to automate their daily procedures. These BPMSs manage the information related to the instances that flow through the model (business data), and recover the information concerning the process performance (Process Performance Indicators). Process Performance Indicators (PPIs) tend to be used...
Modern science is often conducted on large scale, distributed, heterogeneous and high-performance computing infrastructures. Increasingly, the scale and complexity of both the applications and the underlying execution platforms have been growing. Scientific workflows have emerged as a flexible representation to declaratively express complex applications with data andcontrol dependences. However, it...
Power consumption is a big challenge in chip design. Decisions taken in early design phases have large impact on the power consumption. Generally, simulation-based Design Space Exploration (DSE) is computationally costly for large problems due the size of design space. Simulate the possible scenarios in a distributed fashion can decrease the time to find efficient solutions. In this paper we describe...
As scientific simulation applications evolve on the path towards exascale, a new model of scientific inquiry is required where concurrently with the running simulation, online analytics operate on the data it produces. By avoiding offline data storage except when absoluately necessary, it enables speeding up the scientific discovery process by providing rapid insights into the simulated science phenomena...
Scientific workflows (swf) are commonly used to model and execute large-scale scientific experiments. From the scientist's perspective the workflow execution is like black boxes. The scientist submits the workflow and at the end, the result or a notification about failed completion is returned. Concerning long running experiments or when workflows are in experimental phase it may not be acceptable...
Monitoring is an essential part of smart home technology, and monitoring data are applied to optimize a number of different goals. However, the monitoring component is uneasy to implement by hard coding, and it is time consuming and error prone. In this paper, we propose an approach for generation of monitoring component. We first extend a meta-modeling language with data source specification that...
Digital home refers to the use of computer and information technology to control home appliances and features. Management applications of home devices are building based on runtime information of the devices. The runtime model can be built using data from monitoring tools and analysis tools for specific platform. In order to construct runtime model from data provided from both monitoring tools and...
In distributed business process support environments, process interference from multiple stakeholders may cause erroneous process outcomes. Existing solutions to detect and correct interference at runtime employ formal verification and the automatic generation of intervention processes at runtime. However, these solutions are limited in their generality: they cannot cope with interference that occurs...
Many SOA applications are now migrating to cloud servers, due to cloud's low cost provision, elasticity for growth, and better availability. Although cloud service providers have implemented reliable management system for their infrastructure, hybrid cloud users often lack easy monitoring and diagnosis facilities to discover the root cause of end-to-end QoS violations. However, the cause must be identified...
Correctness checking of HDL-model behavior is an integral part of runtime verification of hardware. As a rule, it is based on comparing of HDL-model behavior and reference model behavior, developed in high-level programming languages. Being verified, both models are stimulated with the same input sequence; their output traces are caught and matched. Due to the abstractness of the reference model,...
Increasingly severe I/O bottlenecks on High-End Computing machines are prompting scientists to process simulation output data online while simulations are running and before storing data on disk. There are several options to place data analytics along the I/O path: on compute nodes, on separate nodes dedicated to analytics, or after data is stored on persistent storage. Since different placements...
Autonomous computing has two main objectives: (i) making systems aware about their state and their environment and (ii) making them able to automatically actualize their behavior according to any relevant internal or external event. This paper describes a novel and dynamic approach to assist software developers and designers in building autonomous systems. Our approach offers a dynamic platform to...
In order to meet the requirements of the system running environments simulation for virtual machines' performance optimization and anomaly detection, an extensible tool named Characteristic Scenarios Simulator for Virtual Machine was developed base on the summarization and analysis of characteristic scenarios of virtual machines' running. The simulator takes an Analyser-Manager-Worker core architecture...
In modern cloud computing systems, hundreds and even thousands of cloud servers are interconnected by multi-layer networks. In such large-scale and complex systems, failures are common. Proactive failure management is a crucial technology to characterize system behaviors and forecast failure dynamics in the cloud. To make failure predictions, we need to monitor the system execution and collect health-related...
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