中文摘要
網格計算系統是一個整合各種不同的分配資源系統，用來提供一個高速而且有效的計算處理大量並且繁雜的任務。隨著系統越來越大，網格計算系統成為了基礎並且強大的科學方法。在網格計算系統中，資源分配系統是用來將任務分割成不同的子任務並且指派給系統的資源點已得到最好的服務要求。其中服務要求可以成本、執行時間、可靠度等等的需求。到目前為止，科學家已經提供了許多的數學方法來處理找尋這些最好的服務要求，像是SDP、IE、UGFM等等的方法。但是這些數學方法都有個缺點就是時間複雜度大大，在處理大規模的系統問題的時候，需要花很多時間在計算上面。因此，我們採取蒙地卡羅模擬法結合細胞自動機的概念去加速在大規模問題中尋找任務要求。在本文中討論的是總成本，這各種成本包含了執行的時間成本和可靠度成本。最後如何找出一個最好的任務分配狀況，我們透過基因演算法使得可以更加快速的找到一個有最小總成本的任務分配情形。

Abstract：
The grid system consists of many different distributed resources, which can supply high-speed computing efficiency to deal with several mass and complex workloads. Thus, the Grid computing is a powerful and fundamental technology in the future. In Grid systems, a resource management system (RMS) would assign many subtasks to adequate resources for sake of better service cost (time or reliability). Nowadays, lots of methodologies (such as the SDP, IE, and UGFM et al.) can exactly calculate the service cost (time or reliability) of a grid system, but those have high time complexity when service require was evaluated in a large-scale system. Therefore, we applied Cellular automata Monte-Carlo simulation to estimate approximate service reliability of a large-scale grid system. In this paper we computed total cost by system reliability and maximum time. Finally, we adopted Genetic Algorithm to search the best assignment combination of subtasks and resource for optimal service total cost.

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