949 research outputs found
mRUBiS: An Exemplar for Model-Based Architectural Self-Healing and Self-Optimization
Self-adaptive software systems are often structured into an adaptation engine
that manages an adaptable software by operating on a runtime model that
represents the architecture of the software (model-based architectural
self-adaptation). Despite the popularity of such approaches, existing exemplars
provide application programming interfaces but no runtime model to develop
adaptation engines. Consequently, there does not exist any exemplar that
supports developing, evaluating, and comparing model-based self-adaptation off
the shelf. Therefore, we present mRUBiS, an extensible exemplar for model-based
architectural self-healing and self-optimization. mRUBiS simulates the
adaptable software and therefore provides and maintains an architectural
runtime model of the software, which can be directly used by adaptation engines
to realize and perform self-adaptation. Particularly, mRUBiS supports injecting
issues into the model, which should be handled by self-adaptation, and
validating the model to assess the self-adaptation. Finally, mRUBiS allows
developers to explore variants of adaptation engines (e.g., event-driven
self-adaptation) and to evaluate the effectiveness, efficiency, and scalability
of the engines
Adaptive Time- and Process-Aware Information Systems
For the digitized enterprise the proper handling of the temporal aspects of its business processes is vital. Delivery times, appointments and deadlines must be met, processing times and durations be monitored, and optimization objectives shall be pursued. However, contemporary Process-Aware Information Systems (PAISs)--the go-to solution for the computer-aided support of business processes—still lack a sophisticated support of the time perspective. Hence, there is a high demand for a more profound support of temporal aspects in PAISs. Accordingly, both the specification and the operational support of temporal aspects constitute fundamental challenges for the further development and dissemination of PAISs. The aim of this thesis is to propose a framework for supporting the time perspective of business processes in PAISs. As PAISs enable the design, execution and evolution of business processes, the designated framework must support these three fundamental phases of the process life cycle.
The ATAPIS framework proposed by this thesis essentially comprises three major com-ponents.
First, a universal and comprehensive set of time patterns is provided. Respective time patterns represent temporal concepts commonly found in business processes and are based on empirical evidence. In particular, they provide a universal and comprehensive set of notions for describing temporal aspects in business processes. Moreover, a precise formal semantics for each of the time patterns is provided based on an in-depth analysis of a large set of real-world use cases. Respective formal semantics enable the proper integration of the time patterns into PAISs. In turn, the latter will allow for the specification of time-aware process schemas.
Second, a generic framework for implementing the time patterns based on their formal semantics is developed. The framework and its techniques enable the verification of time-aware process schemas regarding their temporal consistency, i. e., their ability to be successfully executed without violating any of their temporal constraints. Subsequently, the framework is extended to consider advanced aspects like the contingent nature of activity durations and alternative execution paths as well. Moreover, an algorithm as well as techniques for executing and monitoring time-aware process instances in PAISs is provided. Based on the presented concepts, it becomes possible to ensure that a time-aware process instance may be executed without violating any of its temporal constraints.
Third, a set of change operations for dynamically modifying time-aware process instances during run time is suggested. Respective change operations ensure that a modified time-aware process instance remains temporally consistent after the respective modification. Moreover, to reduce the complexity involved when applying multiple change operations a sophisticated approximation-based technique is presented. Overall, the developed change operations allow providing the flexibility required by business processes in practice.
Altogether, the ATAPIS framework provides fundamental concepts, techniques and algorithms for integrating the time perspective into PAISs. As beauty of this framework the specification, execution and evolution of business processes is supported by an integrated approach
Fusion of Model-free Reinforcement Learning with Microgrid Control: Review and Vision
Challenges and opportunities coexist in microgrids as a result of emerging
large-scale distributed energy resources (DERs) and advanced control
techniques. In this paper, a comprehensive review of microgrid control is
presented with its fusion of model-free reinforcement learning (MFRL). A
high-level research map of microgrid control is developed from six distinct
perspectives, followed by bottom-level modularized control blocks illustrating
the configurations of grid-following (GFL) and grid-forming (GFM) inverters.
Then, mainstream MFRL algorithms are introduced with an explanation of how MFRL
can be integrated into the existing control framework. Next, the application
guideline of MFRL is summarized with a discussion of three fusing approaches,
i.e., model identification and parameter tuning, supplementary signal
generation, and controller substitution, with the existing control framework.
Finally, the fundamental challenges associated with adopting MFRL in microgrid
control and corresponding insights for addressing these concerns are fully
discussed.Comment: 14 pages, 4 figures, published on IEEE Transaction on Smart Grid 2022
Nov 15. See:
https://ieeexplore-ieee-org.utk.idm.oclc.org/stamp/stamp.jsp?arnumber=995140
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