A multi-agent-based model for service-oriented interaction in a mobile grid computing environment

2011 ◽  
Vol 7 (2) ◽  
pp. 270-284 ◽  
Author(s):  
Chunlin Li ◽  
LaYuan Li
Keyword(s):  
Grid Computing ◽  
Agent Based Model ◽  
Computing Environment ◽  
Agent Based ◽  
Mobile Grid ◽  
Service Oriented ◽  
Multi Agent ◽  
Mobile Grid Computing

Real threats using GTP protocol and countermeasures on a 4G mobile grid computing environment

2017 ◽  
Vol 13 (1) ◽  
pp. 3 ◽  
Author(s):  
Seongmin Park ◽  
Sekwon Kim ◽  
Kyungho Son ◽  
Hwankuk Kim ◽  
Junyoung Park ◽  
...  
Keyword(s):  
Grid Computing ◽  
Computing Environment ◽  
Mobile Grid ◽  
Mobile Grid Computing

Real threats using GTP protocol and countermeasures on a 4G mobile grid computing environment

2017 ◽  
Vol 13 (1) ◽  
pp. 3
Author(s):  
Kangbin Yim ◽  
Hwankuk Kim ◽  
Kyungho Son ◽  
Sekwon Kim ◽  
Seongmin Park ◽  
...  
Keyword(s):  
Grid Computing ◽  
Computing Environment ◽  
Mobile Grid ◽  
Mobile Grid Computing

scholarly journals Optimized Application Level Checkpoint Based Load Sharing Model for Heterogeneous Mobile Grid Computing

2017 ◽  
Vol 10 (28) ◽  
pp. 1-13
Author(s):  
Imran Rafique ◽  
Hina Gul ◽  
Salman Rafique ◽  
Syed Asad Raza Kazmi ◽  
Awais Qasim ◽  
...  
Keyword(s):  
Grid Computing ◽  
Load Sharing ◽  
Mobile Grid ◽  
Mobile Grid Computing

An Autonomous Multi-Agent Simulation Model for Acute Inflammatory Response

2013 ◽  
pp. 218-233 ◽  
Author(s):  
John Wu ◽  
David Ben-Arieh ◽  
Zhenzhen Shi
Keyword(s):  
Simulation Model ◽  
Focal Point ◽  
Therapeutic Interventions ◽  
Prognostic Indicators ◽  
Simulation Approach ◽  
Agent Based Model ◽  
Agent Based ◽  
Initial Stage ◽  
Agent Simulation ◽  
Multi Agent

This research proposes an agent-based simulation model combined with the strength of systemic dynamic mathematical model, providing a new modeling and simulation approach of the pathogenesis of AIR. AIR is the initial stage of a typical sepsis episode, often leading to severe sepsis or septic shocks. The process of AIR has been in the focal point affecting more than 750,000 patients annually in the United State alone. Based on the agent-based model presented herein, clinicians can predict the sepsis pathogenesis for patients using the prognostic indicators from the simulation results, planning the proper therapeutic interventions accordingly. Impressively, the modeling approach presented creates a friendly user-interface allowing physicians to visualize and capture the potential AIR progression patterns. Based on the computational studies, the simulated behavior of the agent–based model conforms to the mechanisms described by the system dynamics mathematical models established in previous research.

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