An Agent Based Trust Mechanism for Selection of an Effective Data Center

2021 ◽  
Author(s):  
Shivani Jaswal ◽  
Manisha Malhotra
Keyword(s):  
Data Center ◽  
Trust Mechanism ◽  
Agent Based ◽  
Selection Of

scholarly journals Modeling colicin operons as genetic arms in plasmid-genome conflicts

2021 ◽  
Author(s):  
Pavithra Anantharaman Sudhakari ◽  
Bhaskar Chandra Mohan Ramisetty
Keyword(s):  
Negative Selection ◽  
Bacterial Genome ◽  
Evolutionary Perspective ◽  
Bacterial Genomes ◽  
Sequence Analyses ◽  
Agent Based ◽  
Physiological Relevance ◽  
Maintenance Systems ◽  
Selection Of ◽  
Lethal Genes

Plasmids are acellular propagating entities that depend, as molecular parasites, on bacteria for propagation. The conflict between the bacterial genome and the parasitic plasmids allows the emergence of genetic arms such as Colicin (Col) operons. Endonuclease Col operons encode three proteins; an endonuclease colicin (cleaves nucleic acids), an immunity protein (inactivates its cognate colicin), and lysis protein (aids in colicin release via host cell lysis). Col operons are efficient plasmid-maintenance systems; (i) the plasmid cured cells are killed by the colicins; (ii) damaged cells lyse and releases the colicins that eliminate the competitors; and (iii) the released plasmids invade new bacteria. Surprisingly, some bacterial genomes have Col operons. The eco-evolutionary drive and physiological relevance of genomic Col operons are unknown. We investigated plasmidic and genomic Col operons using sequence analyses from an eco-evolutionary perspective. We found 1,248 genomic and plasmidic colicins across 30 bacterial genera. Although 51% of the genomes harbor colicins, the majority of the genomic colicins lacked a functional lysis gene, suggesting the negative selection of lethal genes. The immunity gene of the Col operon protects the cured host thereby eliminating the metabolic burden due to plasmid. We show mutual exclusivity of col operons on genomes and plasmids. We propose anti-addiction hypothesis for genomic colicins. Using a stochastic agent-based model, we show that the genomic colicins confer an advantage to the host genome in terms of immunity to the toxin and elimination of plasmid burden. Col operons are genetic arms that regulate the ecological interplay of bacterial genomes and plasmids.

Editorial

2018 ◽  
pp. 1-4
Author(s):  
Daniele Checci ◽  
Janet Gornick
Keyword(s):  
Income Distribution ◽  
Data Center ◽  
Research Community ◽  
Final Outcome ◽  
Special Issue ◽  
National Data ◽  
Blind Review ◽  
The University ◽  
Selection Of ◽  
Cross National

The articles included in this special issue of the Journal of Income Distribution are a selection of papers originally presented at the first LIS-LWS Users Conference, hosted by LIS, the cross-national data center in Luxembourg. The conference took place at the University of Luxembourg in Belval, Luxembourg, on April 27- 28, 2017. The submitted papers underwent a process of blind review, and this collection of five articles is the final outcome. Taken as a whole, these articles constitute an interesting overview of the ways in which the research community uses the LIS-LWS Databases, which provide researchers access to microdata on income and wealth, respectively.

Agent-Based Process Sequencing Using Search Algorithms

2006 ◽  
Author(s):  
Dusan N. Sormaz
Keyword(s):  
Search Algorithms ◽  
Optimal Process ◽  
Agent Based ◽  
Process Sequencing ◽  
Whole Process ◽  
Domain Space ◽  
Sequencing Algorithm ◽  
Use Of Resources ◽  
Context Specific ◽  
Selection Of

Process sequencing represents one of very important tasks in the process planning. The order of tasks and the use of resources are determined by sequencing, and therefore the decision carries the burden of finally optimizing the whole process plan of the part. This paper proposes a flexible, agent-based framework for process sequencing which allows for realtime selection of the sequencing algorithm, dependent on the stage of the product development. The framework has been developed around a tool called space searcher which provides for application of space search algorithms in various domain. Space searcher receives a sequencing agent which provides the sequencing algorithm and executes a space search in order to generate context-specific optimal process sequence. Several process sequencing algorithms (and corresponding agents for space searcher) are described in detail. The application of those algorithms is illustrated on few examples.

scholarly journals Sustainable Location Selection of Data Centers: Developing a Multi-Criteria Set-Covering Decision-Making Methodology

2020 ◽  
Vol 19 (03) ◽  
pp. 741-773
Author(s):  
Siamak Kheybari ◽  
Mansoor Davoodi Monfared ◽  
Hadis Farazmand ◽  
Jafar Rezaei
Keyword(s):  
Data Center ◽  
Data Centers ◽  
Social Economic ◽  
Set Covering ◽  
Online Questionnaire ◽  
Location Selection ◽  
Sustainability Criteria ◽  
Proposed Model ◽  
Covering Model ◽  
Selection Of

In this paper, a multi-criteria set-covering methodology is proposed to select suitable locations for a set of data centers. First, a framework of criteria, with social, economic and environmental dimensions, is presented. The framework is used to calculate the suitability of potential data center locations in Iran. To that end, a sample of specialists in Iran was asked to take part in an online questionnaire, based on best–worst method (BWM), to determine the weight of the criteria included in the proposed framework, after which a number of potential locations are evaluated on the basis of the criteria. The proposed model is evaluated under a number of settings. Using the proposed multi-criteria set-covering model, not only the utility of candidate places is evaluated by sustainability criteria but also all service applicants are covered by at least one data center with a specific coverage radius.

scholarly journals Toward the Applicability of Statistics: A Representational View

2019 ◽  
Vol 23 (1) ◽  
pp. 113-129
Author(s):  
Mahdi Ashoori ◽  
S. Mahmoud Taheri
Keyword(s):  
Statistical Modeling ◽  
Statistical Models ◽  
Statistical Estimation ◽  
Target System ◽  
Statistical Research ◽  
Agent Based ◽  
Positive Representation ◽  
Methodology Of Science ◽  
Selection Of

The problem of understanding how statistical inference is, and can be, applied in  empirical sciences is important for the methodology of science. It is the objective of this paper  to gain a better understanding of the role of statistical methods in scientific modeling. The  important question of whether the applicability reduces to the representational properties  of statistical models is discussed. It will be shown that while the answer to this question  is positive, representation in statistical models is not purely structural. In spite of the fact  that representation in statistical models is based on the structural similarities between the  statistical model and the empirical systems under study, these relationships are shown to be  appropriate for representing relations in the target system by agent function, too. A second  aspect of the paper involves the claim that agent-based components of statistical modeling  are: a) interpretation of random variables, b) selection of the goal of statistical research, and  c) selection of estimator properties. To justify these claims, a preliminary discussion will be  presented on the role of statistics in modeling, as in regression and other structural models.  This role will be explored and realized using a structural viewpoint. Also the role of statistical  estimation in statistical modeling is discussed to explain the representational role of models  and the inferential role of the agent in modeling. 

scholarly journals Second-order agent-based models of emergent behaviour of Dictyostelium discoideum and their inspiration for swarm robotics

2020 ◽  
Vol 25 (4) ◽  
pp. 656-665
Author(s):  
Mohammad Parhizkar ◽  
Giovanna Di Marzo Serugendo ◽  
Jahn Nitschke ◽  
Louis Hellequin ◽  
Assane Wade ◽  
...  
Keyword(s):  
Dictyostelium Discoideum ◽  
Swarm Robotics ◽  
Second Order ◽  
Transition Phase ◽  
Agent Based Models ◽  
Agent Based ◽  
Emergent Behaviour ◽  
The Impact ◽  
The Relationship ◽  
Selection Of

Abstract By studying and modelling the behaviour of Dictyostelium discoideum, we aim at deriving mechanisms useful for engineering collective artificial intelligence systems. This paper discusses a selection of agent-based models reproducing second-order behaviour of Dictyostelium discoideum, occurring during the migration phase; their corresponding biological illustrations; and how we used them as an inspiration for transposing this behaviour into swarms of Kilobots. For the models, we focus on: (1) the transition phase from first- to second-order emergent behaviour; (2) slugs’ uniform distribution around a light source; and (3) the relationship between slugs’ speed and length occurring during the migration phase of the life cycle of D. discoideum. Results show the impact of the length of the slug on its speed and the effect of ammonia on the distribution of slugs. Our computational results show similar behaviour to our biological experiments, using Ax2(ka) strain. For swarm robotics experiments, we focus on the transition phase, slugs’ chaining, merging and moving away from each other.

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