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Stream workflow application such as online anomaly detection or online traffic monitoring, integrates multiple streaming big data applications into data analysis pipeline. This application can be highly dynamic in nature, where the data…
Our ability to manipulate the behavior of complex networks depends on the design of efficient control algorithms and, critically, on the availability of an accurate and tractable model of the network dynamics. While the design of control…
This review examined the current advancements in data-driven methods for analyzing flow and transport in porous media, which has various applications in energy, chemical engineering, environmental science, and beyond. Although there has…
Scientific workflows consist of thousands of highly parallelized tasks executed in a distributed environment involving many components. Automatic tracing and investigation of the components' and tasks' performance metrics, traces, and…
Dataflow devices represent an avenue towards saving the control and data movement overhead of Load-Store Architectures. Various dataflow accelerators have been proposed, but how to efficiently schedule applications on such devices remains…
This paper focuses on the use of knowledge possessed by designers. Data collection was based on observations (by the cognitive ergonomics researcher) and simultaneous verbalisations (by the designers) in empirical studies conducted in the…
Workflows are prevalent in today's computing infrastructures. The workflow model support various different domains, from machine learning to finance and from astronomy to chemistry. Different Quality-of-Service (QoS) requirements and other…
Physiological signals can potentially be applied as objective measures to understand the behavior and engagement of users interacting with information access systems. However, the signals are highly sensitive, and many controls are required…
As more applications are being moved to the Cloud thanks to serverless computing, it is increasingly necessary to support native life cycle execution of those applications in the data center. But existing systems either focus on…
Workflow management systems allow the users to develop complex applications at a higher level, by orchestrating functional components without handling the implementation details. Although a wide range of workflow engines are developed in…
We introduce the notion of a data-first design study which is triggered by the acquisition of real-world data instead of specific stakeholder analysis questions. We propose an adaptation of the design study methodology framework to provide…
Dynamical systems see widespread use in natural sciences like physics, biology, chemistry, as well as engineering disciplines such as circuit analysis, computational fluid dynamics, and control. For simple systems, the differential…
Competitive analysis of online algorithms has commonly been applied to understand the behaviour of real-time systems during overload conditions. While competitive analysis provides insight into the behaviour of certain algorithms, it is…
We study repeated task assignment as an instrument for providing effort incentives. Unlike traditional incentive instruments, assignment of a task both determines who produces and provides incentives, and incentives for one worker spill…
The workflow is a general notion representing the automated processes along with the flow of data. The automation ensures the processes being executed in the order. Therefore, this feature attracts users from various background to build the…
Many networked applications, e.g., in the domain of cyber-physical systems, require strict service guarantees, usually in the form of jitter and latency bounds, for time-triggered traffic flows. It is a notoriously hard problem to compute a…
With the advent of Grid and application technologies, scientists and engineers are building more and more complex applications to manage and process large data sets, and execute scientific experiments on distributed resources. Such…
The analysis of massive scientific data often happens in the form of workflows with interdependent tasks. When such a scientific workflow needs to be scheduled on a parallel or distributed system, one usually represents the workflow as a…
Capturing both the structural and temporal aspects of interactions is crucial for many real world datasets like contact between individuals. Using the link stream formalism to capture the dynamic of the systems, we tackle the issue of…
We give a tutorial for the study of dynamical systems on networks. We focus especially on "simple" situations that are tractable analytically, because they can be very insightful and provide useful springboards for the study of more…