發(fā)布時間：2018-02-05 04:49

  本文關(guān)鍵詞： 任務(wù)調(diào)度模型 負(fù)載均衡 并行計算 高性能 遙感產(chǎn)品生產(chǎn)　出處：《河南大學(xué)》2014年碩士論文　論文類型：學(xué)位論文

【摘要】：隨著社會對信息數(shù)據(jù)的巨大需求，遙感影像數(shù)據(jù)量呈爆炸式增長，同時，遙感應(yīng)用對數(shù)據(jù)處理的巨量需求，推動了遙感影像處理技術(shù)的不斷發(fā)展。高性能集群計算是實現(xiàn)海量高分辨率遙感衛(wèi)星數(shù)據(jù)快速處理的重要技術(shù)之一，能有效緩解高分遙感應(yīng)用的“瓶頸”。其中，任務(wù)調(diào)度模型是提升集群系統(tǒng)效率的關(guān)鍵。 作者所參與研發(fā)的國家重大專項課題“高分辨率對地觀測應(yīng)用系統(tǒng)”中海量遙感影像共性產(chǎn)品生產(chǎn)系統(tǒng)，具有任務(wù)性質(zhì)單一、子任務(wù)量輕、資源文件大且相對獨立等特點，而傳統(tǒng)的任務(wù)調(diào)度模型還存在針對性差、實用性不強、調(diào)度時間過長等問題，不能滿足該系統(tǒng)的特點要求。為解決上述問題，本文采用多指標(biāo)負(fù)載均衡技術(shù)以及分層式任務(wù)調(diào)度方法，對系統(tǒng)中原有的調(diào)度模型進(jìn)行改進(jìn)，提出了一種與負(fù)載均衡相結(jié)合的兩級任務(wù)調(diào)度模型。主要工作和貢獻(xiàn)如下： 1.在對海量遙感影像共性產(chǎn)品生產(chǎn)系統(tǒng)以及系統(tǒng)原有的任務(wù)調(diào)度策略分析的基礎(chǔ)上，針對原有任務(wù)調(diào)度策略所存在的吞吐量低、可靠性低以及容錯性差等問題，提出了考慮負(fù)載均衡的兩級任務(wù)調(diào)度模型。 2.在提出該模型的基礎(chǔ)上，首先通過分析負(fù)載均衡技術(shù)，并根據(jù)海量遙感產(chǎn)品生產(chǎn)系統(tǒng)的特點，設(shè)計負(fù)載均衡器，以及任務(wù)管理器與負(fù)載均衡器之間的接口；然后，根據(jù)系統(tǒng)的任務(wù)特點，完成任務(wù)調(diào)度模型的整體流程設(shè)計；最后，完成了任務(wù)調(diào)度模型中的一級任務(wù)調(diào)度和二級任務(wù)調(diào)度的設(shè)計。 3.將改進(jìn)的任務(wù)調(diào)度模型應(yīng)用于海量遙感影像共性產(chǎn)品生產(chǎn)系統(tǒng)中，并通過大量的實驗數(shù)據(jù)表明，相比原有的任務(wù)調(diào)度模型，在系統(tǒng)吞吐量、系統(tǒng)自適應(yīng)性、系統(tǒng)的可靠性以及系統(tǒng)的容錯性等方面，都得到了大大提高。利用改進(jìn)的任務(wù)調(diào)度策略，，某些特定衛(wèi)星切片數(shù)據(jù)的處理時間甚至縮短了一半以上。
[Abstract]:With the huge demand of society for information data, the amount of remote sensing image data increases explosively. At the same time, there is a huge demand for data processing in remote sensing applications. High performance cluster computing is one of the most important technologies to realize the fast processing of massive high resolution remote sensing satellite data. The task scheduling model is the key to improve the efficiency of cluster system. The production system of mass remote sensing image generality product in the national special project "High Resolution Earth observation Application system", which the author participated in, has a single task and a light sub-task. Resource files are large and relatively independent, but the traditional task scheduling model also has some problems, such as poor pertinence, weak practicability and long scheduling time, which can not meet the characteristics of the system. This paper adopts multi-index load balancing technology and hierarchical task scheduling method to improve the original scheduling model in the system. A two-level task scheduling model combined with load balancing is proposed. The main work and contributions are as follows: 1. On the basis of analyzing the common product production system of mass remote sensing image and the original task scheduling strategy of the system, the throughput of the original task scheduling strategy is low. Due to the low reliability and poor fault tolerance, a two-level task scheduling model considering load balancing is proposed. 2. On the basis of this model, the load balancer is designed by analyzing the load balancing technology and according to the characteristics of mass remote sensing product production system. And the interface between task manager and load balancer; Then, according to the task characteristics of the system, the overall process design of the task scheduling model is completed. Finally, the primary task scheduling and the second level task scheduling are designed in the task scheduling model. 3. The improved task scheduling model is applied to the mass remote sensing image generic product production system, and a large number of experimental data show that compared with the original task scheduling model, the system throughput. The adaptability of the system, the reliability of the system and the fault tolerance of the system have been greatly improved, using the improved task scheduling strategy. Processing time for certain satellite slicing data is even reduced by more than half.
【學(xué)位授予單位】：河南大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2014
【分類號】：TP79

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