6,379 research outputs found
Microservice Transition and its Granularity Problem: A Systematic Mapping Study
Microservices have gained wide recognition and acceptance in software
industries as an emerging architectural style for autonomic, scalable, and more
reliable computing. The transition to microservices has been highly motivated
by the need for better alignment of technical design decisions with improving
value potentials of architectures. Despite microservices' popularity, research
still lacks disciplined understanding of transition and consensus on the
principles and activities underlying "micro-ing" architectures. In this paper,
we report on a systematic mapping study that consolidates various views,
approaches and activities that commonly assist in the transition to
microservices. The study aims to provide a better understanding of the
transition; it also contributes a working definition of the transition and
technical activities underlying it. We term the transition and technical
activities leading to microservice architectures as microservitization. We then
shed light on a fundamental problem of microservitization: microservice
granularity and reasoning about its adaptation as first-class entities. This
study reviews state-of-the-art and -practice related to reasoning about
microservice granularity; it reviews modelling approaches, aspects considered,
guidelines and processes used to reason about microservice granularity. This
study identifies opportunities for future research and development related to
reasoning about microservice granularity.Comment: 36 pages including references, 6 figures, and 3 table
Towards goal-based autonomic networking
The ability to quickly deploy and efficiently manage services is critical to the telecommunications industry. Currently, services are designed and managed by different teams with expertise over a wide range of concerns, from high-level business to low level network aspects. Not only is this approach expensive in terms
of time and resources, but it also has problems to scale up to new outsourcing and/or multi-vendor models, where subsystems and teams belong to different organizations. We endorse the idea, upheld among others in the autonomic computing community, that the network and system components involved in the provision of a service must be crafted to facilitate their management. Furthermore, they should help bridge the gap between network and business concerns. In this paper, we sketch an approach based on
early work on the hierarchical organization of autonomic entities that possibly belong to different organizations. An autonomic entity governs over other autonomic entities by defining their goals. Thus, it is up to each autonomic entity to decide its line of actions in order to fulfill its goals, and the governing entity needs not know about the internals of its subordinates. We illustrate the approach with a simple but still rich example of a telecom service
Modelling and analyzing adaptive self-assembling strategies with Maude
Building adaptive systems with predictable emergent behavior is a challenging task and it is becoming a critical need. The research community has accepted the challenge by introducing approaches of various nature: from software architectures, to programming paradigms, to analysis techniques. We recently proposed a conceptual framework for adaptation centered around the role of control data. In this paper we show that it can be naturally realized in a reflective logical language like Maude by using the Reflective Russian Dolls model. Moreover, we exploit this model to specify, validate and analyse a prominent example of adaptive system: robot swarms equipped with self-assembly strategies. The analysis exploits the statistical model checker PVeStA
A Taxonomy of Data Grids for Distributed Data Sharing, Management and Processing
Data Grids have been adopted as the platform for scientific communities that
need to share, access, transport, process and manage large data collections
distributed worldwide. They combine high-end computing technologies with
high-performance networking and wide-area storage management techniques. In
this paper, we discuss the key concepts behind Data Grids and compare them with
other data sharing and distribution paradigms such as content delivery
networks, peer-to-peer networks and distributed databases. We then provide
comprehensive taxonomies that cover various aspects of architecture, data
transportation, data replication and resource allocation and scheduling.
Finally, we map the proposed taxonomy to various Data Grid systems not only to
validate the taxonomy but also to identify areas for future exploration.
Through this taxonomy, we aim to categorise existing systems to better
understand their goals and their methodology. This would help evaluate their
applicability for solving similar problems. This taxonomy also provides a "gap
analysis" of this area through which researchers can potentially identify new
issues for investigation. Finally, we hope that the proposed taxonomy and
mapping also helps to provide an easy way for new practitioners to understand
this complex area of research.Comment: 46 pages, 16 figures, Technical Repor
Towards adaptive multi-robot systems: self-organization and self-adaptation
Dieser Beitrag ist mit Zustimmung des Rechteinhabers aufgrund einer (DFG geförderten) Allianz- bzw. Nationallizenz frei zugänglich.This publication is with permission of the rights owner freely accessible due to an Alliance licence and a national licence (funded by the DFG, German Research Foundation) respectively.The development of complex systems ensembles that operate in uncertain environments is a major challenge. The reason for this is that system designers are not able to fully specify the system during specification and development and before it is being deployed. Natural swarm systems enjoy similar characteristics, yet, being self-adaptive and being able to self-organize, these systems show beneficial emergent behaviour. Similar concepts can be extremely helpful for artificial systems, especially when it comes to multi-robot scenarios, which require such solution in order to be applicable to highly uncertain real world application. In this article, we present a comprehensive overview over state-of-the-art solutions in emergent systems, self-organization, self-adaptation, and robotics. We discuss these approaches in the light of a framework for multi-robot systems and identify similarities, differences missing links and open gaps that have to be addressed in order to make this framework possible
Modeling adaptation with a tuple-based coordination language
In recent years, it has been argued that systems and applications, in order to deal with their increasing complexity, should be able to adapt their behavior according to new requirements or environment conditions. In this paper, we present a preliminary investigation aiming at studying how coordination languages and formal methods can contribute to a better understanding, implementation and usage of the mechanisms and techniques for adaptation currently proposed in the literature. Our study relies on the formal coordination language Klaim as a common framework for modeling some adaptation techniques, namely the MAPE-K loop, aspect- and context-oriented programming
Autonomic care platform for optimizing query performance
Background: As the amount of information in electronic health care systems increases, data operations get more complicated and time-consuming. Intensive Care platforms require a timely processing of data retrievals to guarantee the continuous display of recent data of patients. Physicians and nurses rely on this data for their decision making. Manual optimization of query executions has become difficult to handle due to the increased amount of queries across multiple sources. Hence, a more automated management is necessary to increase the performance of database queries. The autonomic computing paradigm promises an approach in which the system adapts itself and acts as self-managing entity, thereby limiting human interventions and taking actions. Despite the usage of autonomic control loops in network and software systems, this approach has not been applied so far for health information systems.
Methods: We extend the COSARA architecture, an infection surveillance and antibiotic management service platform for the Intensive Care Unit (ICU), with self-managed components to increase the performance of data retrievals. We used real-life ICU COSARA queries to analyse slow performance and measure the impact of optimizations. Each day more than 2 million COSARA queries are executed. Three control loops, which monitor the executions and take action, have been proposed: reactive, deliberative and reflective control loops. We focus on improvements of the execution time of microbiology queries directly related to the visual displays of patients' data on the bedside screens.
Results: The results show that autonomic control loops are beneficial for the optimizations in the data executions in the ICU. The application of reactive control loop results in a reduction of 8.61% of the average execution time of microbiology results. The combined application of the reactive and deliberative control loop results in an average query time reduction of 10.92% and the combination of reactive, deliberative and reflective control loops provides a reduction of 13.04%.
Conclusions: We found that by controlled reduction of queries' executions the performance for the end-user can be improved. The implementation of autonomic control loops in an existing health platform, COSARA, has a positive effect on the timely data visualization for the physician and nurse
Modelling and analyzing adaptive self-assembling strategies with Maude
Building adaptive systems with predictable emergent behavior is a challenging task and it is becoming a critical need. The research community has accepted the challenge by introducing approaches of various nature: from software architectures, to programming paradigms, to analysis techniques. We recently proposed a conceptual framework for adaptation centered around the role of control data. In this paper we show that it can be naturally realized in a reflective logical language like Maude by using the Reflective Russian Dolls model. Moreover, we exploit this model to specify, validate and analyse a prominent example of adaptive system: robot swarms equipped with self-assembly strategies. The analysis exploits the statistical model checker PVeStA
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