78 research outputs found

    GEO-REPLICATION IN A REVIEW OF LATENCY AND COST-EFFECTIVENESS

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    Replication is a data distribution technique for synchronization between databases so that data remains consistent. Replication can overcome data loss problems and perform system recovery quickly if a problem occurs on one of the servers. One of the problems is when a natural disaster occurs at the server location. As a result, if you do not have data replication in different locations, it will cause the system to not run and possibly lose data. Then, geo-replication can reduce latency because the distance between the client and the data center is much closer. The application of geo-replication in general replicates data in all data centers. As a result, the cost of implementation is high because it requires a lot of resources. Because of the various advantages and disadvantages in its application, it is necessary to group geo-replication techniques to make it easier for researchers and technicians to adjust as needed. Therefore, this paper surveys the articles on Geo-replication techniques to implement cost-effectiveness and latency. The articles surveyed included a method for selecting replication sites, a method for reducing round trip time, a method according to data type, and selecting a leader to determine which server node to use. The results of the article survey show that implementing geo-replication for cost-effectiveness is more suitable for use in systems where all users do not need to access all data. Meanwhile, low latency is more suitable for systems used by various types of users. This paper can utilize the techniques that have been reviewed to overcome the problem of cost-effectiveness and latency in implementing Geo-replication

    Techniques intelligentes pour la gestion de la cohérence des Big data dans le cloud

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    Cette thèse aborde le problème de cohérence des données de Bigdata dans le cloud. En effet, nos recherches portent sur l’étude de différentes approches de cohérence adaptative dans le cloud et la proposition d’une nouvelle approche pour l’environnement Edge computing. La gestion de la cohérence a des conséquences majeures pour les systèmes de stockage distribués. Les modèles de cohérence forte nécessitent une synchronisation après chaque mise à jour, ce qui affecte considérablement les performances et la disponibilité du système. À l’inverse, les modèles à faible cohérence offrent de meilleures performances ainsi qu’une meilleure disponibilité des données. Cependant, ces derniers modèles peuvent tolérer trop d’incohérences temporaires sous certaines conditions. Par conséquent, une stratégie de cohérence adaptative est nécessaire pour ajuster, pendant l’exécution, le niveau de cohérence en fonction de la criticité des requêtes ou des données. Cette thèse apporte deux contributions. Dans la première contribution, une analyse comparative des approches de cohérence adaptative existantes est effectuée selon un ensemble de critères de comparaison définis. Ce type de synthèse fournit à l’utilisateur/chercheur une analyse comparative des performances des approches existantes. De plus, il clarifie la pertinence de ces approches pour les systèmes cloud candidats. Dans la seconde contribution, nous proposons MinidoteACE, un nouveau système adaptatif de cohérence qui est une version améliorée de Minidote, un système de cohérence causale pour les applications Edge. Contrairement à Minidote qui ne fournit que la cohérence causale, notre modèle permet aux applications d’exécuter également des requêtes avec des garanties de cohérence plus fortes. Des évaluations expérimentales montrent que le débit ne diminue que de 3,5 % à 10 % lors du remplacement d’une opération causale par une opération forte. Cependant, la latence de mise à jour augmente considérablement pour les opérations fortes jusqu’à trois fois pour une charge de travail où le taux des opérations de mise à jour est de 25 %

    Women in Artificial intelligence (AI)

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    This Special Issue, entitled "Women in Artificial Intelligence" includes 17 papers from leading women scientists. The papers cover a broad scope of research areas within Artificial Intelligence, including machine learning, perception, reasoning or planning, among others. The papers have applications to relevant fields, such as human health, finance, or education. It is worth noting that the Issue includes three papers that deal with different aspects of gender bias in Artificial Intelligence. All the papers have a woman as the first author. We can proudly say that these women are from countries worldwide, such as France, Czech Republic, United Kingdom, Australia, Bangladesh, Yemen, Romania, India, Cuba, Bangladesh and Spain. In conclusion, apart from its intrinsic scientific value as a Special Issue, combining interesting research works, this Special Issue intends to increase the invisibility of women in AI, showing where they are, what they do, and how they contribute to developments in Artificial Intelligence from their different places, positions, research branches and application fields. We planned to issue this book on the on Ada Lovelace Day (11/10/2022), a date internationally dedicated to the first computer programmer, a woman who had to fight the gender difficulties of her times, in the XIX century. We also thank the publisher for making this possible, thus allowing for this book to become a part of the international activities dedicated to celebrating the value of women in ICT all over the world. With this book, we want to pay homage to all the women that contributed over the years to the field of AI

    IV Міжнародний науковий конгрес "Society of Ambient Intelligence - 2021" (ISCSAI 2021). Кривий Ріг, Україна, 12-16 квітня 2021 року

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    IV Міжнародний науковий конгрес "Society of Ambient Intelligence - 2021" (ISCSAI 2021). Кривий Ріг, Україна, 12-16 квітня 2021 року - матеріали.IV International Scientific Congress “Society of Ambient Intelligence – 2021” (ISCSAI 2021). Kryvyi Rih, Ukraine, April 12-16, 2021 - proceedings

    Interpreting Code Enforcement Complaint by Complaint: A Hermeneutic Phenomenological Experience in Document Analysis

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    The current hermeneutic phenomenological study was completed to provide direction for the content analysis of code enforcement complaint documents by municipal code enforcement agencies. This hermeneutic interpretive research was conducted using qualitative content analysis of greater than 500 code enforcement complaint documents submitted to a municipal code enforcement agency over 12 months. The phenomenological research was guided by the following research questions: 1.What indicators are identified by content analysis in a complaint document received from the community of shareholders of a municipal code enforcement agency? 2. What manner of delivery of a complaint document is most frequently exercised by the shareholders of a municipal code enforcement agency? 3. What may the frequency of violations recognized in complaint documents inform a municipal government of a community and its needs? 4. How may a municipal government advance the results of a content analysis of code enforcement complaint documents towards promoting improvements in a community? The theories of symbolic interactionism and Actor-Network Theory (ANT) were used within the methodological paradigms of hermeneutics and phenomenology to understand the function and experience of a complaint document within the code enforcement system and its shareholders. The findings of this research identify how the content analysis of code enforcement complaints can reveal and prioritize the needs, threats, and trends that impact a community and lead to municipal programs that focus on those community issues with collaborative conflict resolution programs that can improve the sense of community for its shareholders, its government and the field of conflict resolution
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