發(fā)布時(shí)間：2021-10-07 19:23

　　隨著計(jì)算機(jī)仿真技術(shù)的發(fā)展和在其他學(xué)科中的應(yīng)用,越來(lái)越多研究領(lǐng)域開始采用計(jì)算機(jī)仿真來(lái)作為重要的研究手段之一。在計(jì)算仿真技術(shù)中,分布式離散事件仿真隨著分布式計(jì)算的進(jìn)步得到了越來(lái)越多的應(yīng)用。這類仿真方式對(duì)大規(guī)模的仿真應(yīng)用具有較好的性能表現(xiàn)。另一方面,近年來(lái),為了解決糧食短缺問(wèn)題,在城市規(guī)劃學(xué)研究中,城市農(nóng)業(yè)逐漸成為受到人們關(guān)注的新興概念。在城市農(nóng)業(yè)中,食品生產(chǎn)消費(fèi)鏈不再嚴(yán)格按照從農(nóng)村到城市的單向結(jié)構(gòu),而是將城市與農(nóng)業(yè)生產(chǎn)混合,通過(guò)前沿技術(shù)提高農(nóng)業(yè)生產(chǎn)效率。本文的研究?jī)?nèi)容主要包含兩個(gè)方面。首先是實(shí)現(xiàn)一種多智能體系統(tǒng)分布式仿真引擎的動(dòng)態(tài)計(jì)算資源管理機(jī)制;其次是在城市農(nóng)業(yè)系統(tǒng)情境下構(gòu)建出一個(gè)智慧城市多智能體模型,并結(jié)合上述機(jī)制對(duì)其進(jìn)行仿真。本研究的主要貢獻(xiàn)列舉如下:第一,對(duì)分布式離散事件仿真平臺(tái)PDES-MAS設(shè)計(jì)了動(dòng)態(tài)計(jì)算資源調(diào)整機(jī)制。我們從底層實(shí)現(xiàn)的角度對(duì)該機(jī)制進(jìn)行了詳細(xì)的描述。它在仿真執(zhí)行過(guò)程中對(duì)系統(tǒng)中的計(jì)算資源進(jìn)行監(jiān)測(cè)。當(dāng)發(fā)現(xiàn)因?yàn)榉抡婺Ｐ托袨榉绞降淖兓鴮?dǎo)致系統(tǒng)中出現(xiàn)計(jì)算資源不足,或者計(jì)算資源冗余的情況時(shí),該機(jī)制能夠動(dòng)態(tài)地分配或回收計(jì)算資源。第二,針對(duì)分布式離散事件仿真中事件消息路由功能和... 

【文章來(lái)源】：哈爾濱工業(yè)大學(xué)黑龍江省 211工程院校 985工程院校

【文章頁(yè)數(shù)】：99 頁(yè)

【學(xué)位級(jí)別】：碩士

【文章目錄】：
摘要
Abstract
Chapter 1 Introduction
    1.1 Background, Purpose and Significance of this Research
        1.1.1 Background of Multi-Agent Simulation
        1.1.2 Developmental of Intelligent Agriculture
        1.1.3 Purpose and Significance
    1.2 Related Work
        1.2.1 Research status of Parallel and Discrete Event Simulation
        1.2.2 Research Status of Intelligent Agriculture
    1.3 Main Research Content
        1.3.1 Multi-agent systems
        1.3.2 PDES Simulation Technology
        1.3.3 PDES-MAS Simulation Platform
        1.3.4 Load Balancing Algorithm
        1.3.5 Tile World Model
        1.3.6 Developmental of Intelligent Agriculture
        1.3.7 Validation of This Research
        1.3.8 Evaluation Index of This Research
    1.4 Research Framework and Methods
    1.5 Main Points of Innovation
    1.6 Organization of this Thesis
Chapter 2 Research on the Framework of Dynamic Capacity Adjustment
    2.1 Introduction
    2.2 PDES-MAS Architecture and Its Problems
    2.3 Limitations of Load Balancing Mechanism
    2.4 Research on the Implementation of Dynamic Capacity Expansion
        2.4.1 Node spawning method based on MPI standard
        2.4.2 Communicator Switching through Multithreading
        2.4.3 Deadlock Problem and Root-CLP Based Scheduling
        2.4.4 Criterion for Starting Node Spawning
    2.5 Research on the Implementation of Dynamic Capacity Contraction
        2.5.1 Criterion for Starting Node Deletion
        2.5.2 Implementation of Node Deletion
    2.6 Brief Summary
Chapter 3 Research on Dynamic Topology Adjustment Supporting MessageRouting
    3.1 Introduction
    3.2 Basic Concept of Message Routing Mechanism
    3.3 Effect of Load balancing Algorithm on Message Routing
    3.4 Implementation of Message Routing in PDES -MAS
    3.5 Design of Dynamic Capacity Adjustment for Message Routing
        3.5.1 Message Type Design
        3.5.2 Design of Dynamic Capacity Expansion for Message Routing
        3.5.3 Design of Dynamic Capacity Contraction for Message Routing
    3.6 Brief Summary
Chapter 4 Research on Dynamic Topology Adjustment Supporting RangeQuery
    4.1 Introduction
    4.2 Basic Concept of Range Query
    4.3 Implementation of Range Query in PDES -MAS
        4.3.1 Port Ranges of CLP nodes
        4.3.2 Range Period and Range Period List
    4.4 Design of Dynamic Adjustment Mechanism for Range Query
        4.4.1 Design of Dynamic Capacity Expansion for Range Query
        4.4.2 Design of Dynamic Capacity Contraction for Range Query
    4.5 Brief Summary
Chapter 5 Experiments on the Tile World Benchmark
    5.1 Introduction
    5.2 Experiment environment
    5.3 Implementation of Tile World model on PDES -MAS
    5.4 Simulation Experiment for Node Spawning
        5.4.1 Analysis of Simulation Conditions
        5.4.2 Comparison of Simulation Results
    5.5 Simulation Experiment for Node Deletion
        5.5.1 Analysis of Simulation Conditions
        5.5.2 Comparison of Simulation Results
    5.6 Brief summary
Chapter 6 Modeling and Simulation for Smart City Application
    6.1 Analysis of the Smart City System
    6.2 Implementation of Smart City Model on PDES -MAS
    6.3 Experiments on the Smart City Model
        6.3.1 Simulation Experiment for Node Spawning
        6.3.2 Simulation Experiment for Node Deletion
    6.4 Brief Summary
Conclusions
結(jié)論
References
Papers Published in the Period of Master Education
Acknowledgements



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