Distributed Agent-based Simulation For Smart City Application

With the development of computer simulation technology and its application in other research fields,more and more researchers have begun to adopt computer simulations as essential research methods.In computer simulation technology,distributed discrete event simulation has been used more and more with the progress of distributed computing.This type of simulation has excellent performance for large-scale simulation applications.On the other hand,in recent years,in order to solve the problem of food shortage,urban agriculture has gradually become an emerging concept in the study of city planning.In urban agriculture,the food production and consumption chain no longer strictly follows the one-way structure from rural to urban but mixes urban with agricultural production to improve agricultural production efficiency through cutting-edge technologies.This research consists of two parts.The first is to design and implement a mechanism for dynamic computing resources management of distributed simulation engines for multi-agent systems.The second is to build a multi-agent model from the urban agriculture scenario and simulate it with the aforementioned mechanism.The main contributions in this thesis are listed as follows:Firstly,this thesis proposes a dynamic computing resource adjustment mechanism for the distributed discrete event simulation platform PDES-MAS.The mechanism is described in detail from the perspective of the underlying implementation.It monitors the computing resources in the system during simulation execution.When it finds that there are insufficient computing resources or redundant computing resources in the system due to changes in the simulation model's behavior,this mechanism can dynamically allocate or reclaim computing resources to achieve better simulation performance.Secondly,the dynamic computing resource adjustment mechanism is further analyzed,designed,and improved for the event message routing and range query functionalities in distributed discrete event simulation.This thesis studies the implementation details of event message routing and range query in the PDES-MAS simulation platform.By analyzing its assumptions about the computing cluster topology,this thesis clarifies the shortcomings of the current PDES-MAS simulation system in dynamic scalability,reconstructs its existing design and implements a dynamic computing resource adjustment mechanism that support s message routing and range query.Thirdly,a multi-agent model of urban agricultural systems in smart cities is proposed.By simplifying and abstracting the food supply chain in the smart city system,this thesis implements a smart city model on the PDES-MAS platform for the characteristics of a series of links from food production,transportatio n,and sales.Finally,this thesis completes some performance evaluations for the dynamic computing resource adjustment mechanism based on different simulation experiments.We use the performance benchmark model Tile World in distributed discrete event simulation and the constructed smart city model to simulate under different experimental conditions.The performance of the dynamic computing resource adjustment mechanism is analyzed by the time required for simulation.Through the results of this study,we not only improve the performance of distributed discrete event simulation platform PDES-MAS in large-scale simulation applications by dynamic computing resource adjustment mechanism but also extend the application scope of computer simulation technology according to the modeling and simulation of practical problems.The design of message routing and load balancing in the dynamic computing resource adjustment mechanism can be applied to other parallel discrete event simulation systems.On the other hand,the smart city model established can also be used to build a more complex and realistic simulation model by adding more content and restrictions.