scholarly journals Concepts and Models of Environment in Self-Adaptive Systems: A Systematic Literature Review

2021 ◽  
Author(s):  
Yong-Jun Shin ◽  
Joon-Young Bae ◽  
Doo-Hwan Bae
Keyword(s):  
Literature Review ◽  
Systematic Literature Review ◽  
Adaptive Systems ◽  
Research Community ◽  
Current Understanding ◽  
Runtime Environment ◽  
Important Concern ◽  
Runtime Environments ◽  
Self Adaptive

The runtime environment is an important concern for self-adaptive systems (SASs). Although researchers have proposed many approaches for developing SASs that address the issue of uncertain runtime environments, the understanding of these environments varies depending on the objectives, perspectives, and assumptions of the research. Thus, the current understanding of the environment in SAS development is ambiguous and abstract. To make this understanding more concrete, we describe the landscape in this area through a systematic literature review (SLR). We examined 128 primary studies and 14 unique environment models. We investigated concepts of the environment depicted in the primary studies and the proposed environment models based on their ability to aid in understanding. This illustrates the characteristics of the SAS environment, the associated emerging environmental uncertainties, and what is expressed in the existing environment models. This paper makes explicit the implicit understanding about the environment made by the SAS research community and organizes and visualizes them.

scholarly journals Applying Machine Learning in Self-adaptive Systems

2021 ◽  
Vol 15 (3) ◽  
pp. 1-37
Author(s):  
Omid Gheibi ◽  
Danny Weyns ◽  
Federico Quin
Keyword(s):  
Machine Learning ◽  
Literature Review ◽  
Systematic Literature Review ◽  
Adaptive Systems ◽  
Machine Learning Techniques ◽  
Future Research ◽  
Large Sets ◽  
Learning Techniques ◽  
Self Adaptation ◽  
Self Adaptive

Recently, we have been witnessing a rapid increase in the use of machine learning techniques in self-adaptive systems. Machine learning has been used for a variety of reasons, ranging from learning a model of the environment of a system during operation to filtering large sets of possible configurations before analyzing them. While a body of work on the use of machine learning in self-adaptive systems exists, there is currently no systematic overview of this area. Such an overview is important for researchers to understand the state of the art and direct future research efforts. This article reports the results of a systematic literature review that aims at providing such an overview. We focus on self-adaptive systems that are based on a traditional Monitor-Analyze-Plan-Execute (MAPE)-based feedback loop. The research questions are centered on the problems that motivate the use of machine learning in self-adaptive systems, the key engineering aspects of learning in self-adaptation, and open challenges in this area. The search resulted in 6,709 papers, of which 109 were retained for data collection. Analysis of the collected data shows that machine learning is mostly used for updating adaptation rules and policies to improve system qualities, and managing resources to better balance qualities and resources. These problems are primarily solved using supervised and interactive learning with classification, regression, and reinforcement learning as the dominant methods. Surprisingly, unsupervised learning that naturally fits automation is only applied in a small number of studies. Key open challenges in this area include the performance of learning, managing the effects of learning, and dealing with more complex types of goals. From the insights derived from this systematic literature review, we outline an initial design process for applying machine learning in self-adaptive systems that are based on MAPE feedback loops.

scholarly journals REACT-ION: A Model-based Runtime Environment for Situation-aware Adaptations

2020 ◽  
Vol 15 (4) ◽  
pp. 1-29
Author(s):  
Martin Pfannemüller ◽  
Martin Breitbach ◽  
Markus Weckesser ◽  
Christian Becker ◽  
Bradley Schmerl ◽  
...  
Keyword(s):  
Situation Awareness ◽  
Communication Systems ◽  
Adaptive Systems ◽  
Development Effort ◽  
Context Management ◽  
Model Based ◽  
Runtime Environment ◽  
Adaptive Capabilities ◽  
And Coping ◽  
Self Adaptive

Trends such as the Internet of Things lead to a growing number of networked devices and to a variety of communication systems. Adding self-adaptive capabilities to these communication systems is one approach to reducing administrative effort and coping with changing execution contexts. Existing frameworks can help reducing development effort but are neither tailored toward the use in communication systems nor easily usable without knowledge in self-adaptive systems development. Accordingly, in previous work, we proposed REACT, a reusable, model-based runtime environment to complement communication systems with adaptive behavior. REACT addresses heterogeneity and distribution aspects of such systems and reduces development effort. In this article, we propose REACT-ION—an extension of REACT for situation awareness. REACT-ION offers a context management module that is able to acquire, store, disseminate, and reason on context data. The context management module is the basis for (i) proactive adaptation with REACT-ION and (ii) self-improvement of the underlying feedback loop. REACT-ION can be used to optimize adaptation decisions at runtime based on the current situation. Therefore, it can cope with uncertainty and situations that were not foreseeable at design time. We show and evaluate in two case studies how REACT-ION’s situation awareness enables proactive adaptation and self-improvement.

A systematic literature review of the SBSE research community in Spain

2020 ◽  
Vol 9 (2) ◽  
pp. 113-128
Author(s):  
Aurora Ramírez ◽  
Pedro Delgado-Pérez ◽  
Javier Ferrer ◽  
José Raúl Romero ◽  
Inmaculada Medina-Bulo ◽  
...  
Keyword(s):  
Literature Review ◽  
Systematic Literature Review ◽  
Research Community

scholarly journals Gangs and social media: A systematic literature review and an identification of future challenges, risks and recommendations

2021 ◽  
pp. 146144482199449
Author(s):  
Ariadna Fernández-Planells ◽  
Enrique Orduña-Malea ◽  
Carles Feixa Pàmpols
Keyword(s):  
Social Media ◽  
Literature Review ◽  
Systematic Literature Review ◽  
Structural Characteristics ◽  
Evaluation Model ◽  
Research Community ◽  
Communicative Practices ◽  
Future Challenges ◽  
Media Research ◽  
Use Of Social Media

Gang literature increasingly reflects the importance of social media in gang lifestyle, as gang members adopt new communicative practices. Yet, because of the multifaceted nature of online gang activity and the diversity of methodologies employed, a general overview of research outcomes is not easily achieved. This article seeks to remedy this by analysing academic studies of gang use of social media. A systematic literature review was conducted in Scopus and Google Scholar databases, which led to the identification of 73 publications. We then undertook a content analysis of each publication using an exhaustive evaluation model, comprising 20 variables and 71 categories. A bibliometric analysis was also performed to determine the structural characteristics of the research community that generates these publications. Our results point to an emerging universe of publications with different themes, methods, samples and ethical protocols. The challenges, risks and recommendations for future social media research with youth street groups are identified.

scholarly journals A different lens: Changing perspectives using Photo-Elicitation Interviews

2015 ◽  
Vol 23 ◽  
pp. 111 ◽  
Author(s):  
Daniela Torre ◽  
Joseph Murphy
Keyword(s):  
Literature Review ◽  
Systematic Literature Review ◽  
Research Community ◽  
Research Topic ◽  
Photo Elicitation ◽  
School Staff ◽  
School Communities ◽  
Key Features ◽  
School Practitioners ◽  
School Stakeholders

The purpose of this systematic literature review is to document how scholars in various fields have used Photo-Elicitation Interview (PEI), explain the benefits and obstacles to using this method, and explain how and why education researchers should use PEI. The key features of PEI are that a researcher or participant takes pictures about a research topic that are then used to elicit dialogue during an interview. The results of our review suggest that education scholars and school practitioners can use PEI methods to better understand school communities and the children, parents, and school staff who inhabit them. Utilizing this technique, the research community will be better positioned to speak on behalf of school stakeholders when contributing to policy discussions and when seeking solutions to improving schools.

scholarly journals Blockchain dan Kecerdasan Buatan dalam Pertanian : Studi Literatur

2021 ◽  
Vol 8 (1) ◽  
pp. 177
Author(s):  
Fajar Delli Wihartiko ◽  
Sri Nurdiati ◽  
Agus Buono ◽  
Edi Santosa
Keyword(s):  
Artificial Intelligence ◽  
Text Mining ◽  
Literature Review ◽  
Systematic Literature Review ◽  
Research Community ◽  
Future Research ◽  
Literature Study ◽  
Blockchain Technology ◽  
Artificial Intelligence Technology ◽  
Number Of Publications

<p class="Abstrak">Dewasa ini teknologi <em>blockchain</em> dan kecerdasan buatan (<em>artificial intelligence</em>/AI) telah diimplementasikan dalam bidang pertanian. Teknologi <em>blockchain</em> menjanjikan keamanan dan peningkatan kepercayaan untuk pengguna. Teknologi kecerdasan buatan menjanjikan berbagai kemudahan bagi pengguna. Perpaduan kedua teknologi tersebut dapat meningkatan kepercayaan terhadap sistem kecerdasan buatan (<em>blockchain for</em> AI) atau dapat juga digunakan untuk meningkatkan kinerja sistem<em> blockchain </em>(AI <em>for</em> <em>blockchain</em>). Tujuan penelitian ini mengulas kedua teknologi tersebut dalam studi literatur serta memberikan tantangan riset ke depan terkait implementasinya di bidang pertanian.  Metodologi yang digunakan adalah <em>Systematic Literature Review </em>(SLR) dan <em>text mining</em>. <em>Text mining </em>digunakan untuk memberikan deskripsi riset yang ada berdasarkan kata-kata di setiap artikel terpilih. SLR digunakan untuk memberikan ulasan yang komprehensif terkait riset <em>Blockchain </em>dan kecerdasan Buatan dalam pertanian. Hasil penelitian menunjukan bahwa terdapat 10 % penelitian terkait penerapan <em>blockchain </em>dan AI dalam pertanian. Riset tersebut memiliki potensi besar untuk berkembang terlihat dari peningkatan jumlah publikasi dalam 2 tahun terakhir. Kontribusi penelitian ini meliputi posisi riset terkini dan usulan riset ke depan dengan mempertimbangkan kondisi pertanian Indonesia. Posisi riset tersebut didominasi komunitas peneliti dari negara-negara di Asia seperti India (33%), Pakistan (33%), China (14%) dan Korea (14%). Originalitas penelitian ini terletak pada studi literatur dari integrasi teknologi <em>blockchain </em>dan kecerdasan buatan dalam bidang pertanian menggunakan SLR dan <em>text mining.</em></p><p class="Abstrak"> </p><p class="Abstrak"><em><strong>Abstract</strong></em></p><p class="Abstrak"><em>Artificial intelligence and blockchain technology are being developed and implemented in Agriculture. Blockchain technology promises security and trust for users. Moreover, artificial intelligence technology promises convenience for users. The combination of these two technologies will increase trust in artificial intelligence systems. Besides, this combination can also increase security on the blockchain system through the application of artificial intelligence. This paper summarizes the application of both technologies and reviews them in a systematic literature review, presents a description of articles based on text mining, and provides future research challenges related to the implementation of blockchain and artificial intelligence in agriculture. The methodologies used are Systematic Literature Review (SLR) and text mining. Text mining is used to describe a description of existing research based on the words in each selected article. SLR is used to provide a comprehensive review of Blockchain research and Artificial intelligence in agriculture. The results showed that there were 10% of research related to the application of blockchain and AI in agriculture. This research has great potential for growth as seen from the increase in the number of publications in the last 2 years. The contribution of this research includes the latest research positions and future research proposals taking into account the conditions of Indonesian agriculture. </em><em>The research position is dominated by the research community from countries in Asia such as India (33%), Pakistan (33%), China (14%) and Korea (14%). The originality of this research is a literature study on the integration of blockchain and artificial intelligence in agriculture using SLR and text mining.</em></p><p class="Abstrak"><em><strong><br /></strong></em></p>

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