An Agent-based Data Collection Architecture for Distributed Simulations

2004 ◽  
Vol 24 (2) ◽  
Author(s):  
Y. Xu ◽  
S. Sen ◽  
F.W. Ciarallo
Keyword(s):  
Data Collection ◽  
Agent Based ◽  
Distributed Simulations

Hybrid simulation modeling for humanitarian relief chain coordination

2015 ◽  
Vol 5 (3) ◽  
pp. 325-347 ◽  
Author(s):  
Caroline C Krejci
Keyword(s):  
Decision Making ◽  
Data Collection ◽  
Simulation Modeling ◽  
Model Development ◽  
Hybrid Simulation ◽  
Humanitarian Logistics ◽  
Content Type ◽  
Agent Based ◽  
Data Collection And Analysis ◽  
Over Time

Purpose – The purpose of this paper is to present a conceptual framework for a hybrid simulation model that can be used to study the decision making and behaviors of humanitarian logistics actors to determine how/whether certain coordination mechanisms enable better relief chain efficiency and effectiveness over time. Design/methodology/approach – The agent-based portion of the model is used to represent human decision making and interactions in a more realistic way than has been done previously, and the discrete-event simulation (DES) portion of the model allows the movement of vehicles, materials, and information throughout a supply network to be represented in a way that allows for dynamic and stochastic behavior. Findings – Coordinated efforts by actors in humanitarian logistics operations involve complex interactions and adaptations over time, which can be capture and explored via hybrid agent-based model (ABM)-DES modeling. Research limitations/implications – This paper describes a framework for a hybrid ABM-DES model. The actual development and implementation of the model, including input data collection and analysis, model development, experimentation, and output data collection and analysis, will be the subject of future work. Practical implications – The hybrid model framework provides other researchers with a starting point for model development. Social implications – This paper provides a basis for future modeling and assessment of coordination in humanitarian logistics, an area that is in need of research. Originality/value – The hybrid simulation modeling framework presented in this paper is a novel application of a new modeling methodology to the problem of coordination in humanitarian logistics.

A Multi-Agent-Based Data Collection and Aggregation Model for Fog-Enabled Cloud Monitoring

2021 ◽  
Vol 11 (1) ◽  
pp. 73-92
Author(s):  
Chetan M. Bulla ◽  
Mahantesh N. Birje
Keyword(s):  
Data Collection ◽  
Fog Computing ◽  
Communication Overhead ◽  
Aggregation Model ◽  
Agent Based ◽  
Redundant Data ◽  
Monitoring Process ◽  
Proposed Model ◽  
Cloud Monitoring ◽  
Multi Agent

The fog-enabled cloud computing has received considerable attention as the fog nodes are deployed at the network edge to provide low latency. It involves various activities, such as configuration management, security management, and data management. Monitoring these activities is essential to improve performance and QoS of fog computing infrastructure. Data collection and aggregation are the basic tasks in the monitoring process, and these phases consume more communicational power as the IoT nodes generate a huge amount of redundant data frequently. In this paper, a multi-agent-based data collection and aggregation model is proposed for monitoring fog infrastructure. The data collection model adopts a hybrid push-pull algorithm that updates the data when a certain change in new data compared to old data. A tree-based data aggregation model is developed to reduce communication overhead between fog node and cloud. The experimental results show that the proposed model improves data coherency and reduces communication overhead compared to existing data collection and aggregation models.

Computational Intelligence as a Platform for a Data Collection Methodology in Management Science

2011 ◽  
pp. 38-54
Author(s):  
Kristina R. Jespersen
Keyword(s):  
Data Collection ◽  
Computational Intelligence ◽  
Role Play ◽  
Management Science ◽  
Agent Based Modeling ◽  
Agent Based Simulation ◽  
Agent Based ◽  
Technological Support ◽  
Business Applications ◽  
New Generation

With an increased focus in management science on how to collect data close to the real world of managers, we consider how agent-based simulations have interesting prospects that are usable for the design of business applications aimed at the collection of data. As an example of a new generation of data collection methodologies, this chapter discusses and presents a behavioral simulation founded in the agent-based simulation life cycle and supported by Web technology. With agent-based modeling the complexity of the method can be increased without limiting the research as a result of limited technological support. This makes it possible to exploit the advantages of a questionnaire, an experimental design, a role-play and a scenario, gaining the synergy of a combination of these methodologies. At the end of the chapter an example of a simulation is presented for researchers and practitioners to study. 1

Model Informed Data Collection in Coupled Human-Water Systems: An Exploratory Application of a Hydrological and Agent-Based Model

2021 ◽  
Author(s):  
Behshad Mohajer ◽  
David Yu ◽  
Marco Janssen ◽  
Margaret Garcia
Keyword(s):  
Decision Making ◽  
Data Collection ◽  
Qualitative Data ◽  
Hydrological Model ◽  
International Association ◽  
Agent Based Model ◽  
Water Modeling ◽  
Catchment Scale ◽  
Survey Question ◽  
Agent Based

<p>Hydrological systems in the Anthropocene have shown substantial shifts from their natural processes due to human modifications. Consequently, deploying coupled human-water modeling is a critical tool to analyze observed changes. However, the development of socio-hydrological models often requires extensive qualitative data collection in the field and analysis. Despite the advances in developing inter-disciplinary methodologies in utilizing qualitative data for coupled human-water modeling, there is a need to identify influential parameters in these systems to inform data collection. Here, we present an exploratory socio-hydrological model to systemically investigate the feedback system of public infrastructure providers, resource users, and the dynamics of water scarcity at the catchment scale to inform data collection and analysis in the field. Specifically, we propose a novel socio-hydrological model by employing and integrating a top-down hydrological model and an extension of Aqua.MORE Model (an Agent-Based Model designed to simulate dynamics of water supply and demand). Specifically, we model alternate behavioral theories of human decision-making to represent the agents’ behavior. Then, we perform sensitivity analysis techniques to identify key socio-economic and behavioral parameters affecting emergence patterns in a stylized human-dominated catchment. We apply the proposed methodology to the Lake Mendocino Watershed in Northern California, US. The results will potentially point which parameters are influential and how they could be mapped to a particular interview or survey question. This study will help us to identify features of decision-making behavior for inclusion in fieldwork, that be might be overlooked in the absence of the proposed modeling. We anticipate that the proposed approach also contributes to the current Panta Rhei Research Initiative of the International Association of Hydrological Sciences (IAHS) which aims at improving the interpretation of the hydrological processes governing the socio-hydrological systems by focusing on their changing dynamics in connection with rapidly changing human systems.</p>

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