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    題名: 適用於大型動態分散式系統的調適性計算模型;Adaptive Computing for Large-Scale Dynamic Distributed Systems
    作者: 康惟翔;Wei-xiang Kang
    貢獻者: 資訊工程研究所
    關鍵詞: 網路生物體;網格計算;自我供給;自我調適;自動計算;雲端運算;cyber organism;grid computing;cloud computing;automatic computing;self-provision;self-adaptation
    日期: 2010-07-23
    上傳時間: 2010-12-09 13:51:34 (UTC+8)
    出版者: 國立中央大學
    摘要: 在資料量以及運算量需求大量增加的現今,單一電腦已難應付各種計算需求,因此各種大型運算架構紛紛被提出,例如計算網格 (Computational Grid) 以及雲端運算 (Cloud Computing)。這些系統通常採用分散式的架構,內部的組成單元也多是異質性的計算資源,因此在系統管理上與資源使用上往往會遇到很多困難。對程式設計師來說,這些計算資源的差異與系統的使用規則會造成程式設計上的困擾,並難以對程式效能做最佳化。目前這方面的研究大多是以達成整體系統效能最佳化為目的,如Condor、Globus Toolkit、IOS等,所以在多程式的執行環境中無法針對所有的應用程式進行個別的效能最佳化。 因此,本研究提出了網路有機體 (Cyber Organism)的計算模式,希望能讓個別應用程式能夠像有機體的自我調適一般以適應各種不同的情況,讓程式顯得更加的聰明。在這個計算模式之下,個別應用程式具有內部溝通能力、環境感測的能力、自我調適的能力。而計算環境應該提供資訊讓個別應用程式感測環境的變化。依據這個計算模式,本研究採用Message Passing Interface (MPI)函式庫發展出一個擁有自我調適功能的系統,並提供許多介面讓應用程式呼叫,以利動態偵測系統環境並進行調節的工作。 我們所提出的計算架構的主要優點是個別應用程式可以依據自己的需求執行自己最佳化的方法,也就是自動偵測目前系統環境的情況,針對系統的各種情況,去做出適度的調整,以達到最好的效能。實驗結果也顯示出,本研究所提出的自我調適功能都能有效的改善應用程式效能,具備著良好的適應性,很適合發展到多種不同的分散式架構之下。The demand for computing power continues growing year by year. Meanwhile, sequential processing techniques are becoming insufficient for many complex problems. As a result, large-scale computing frameworks, such as cloud computing and grid computing, become necessary to fulfill the computing needs. A large-scale computing framework is usually comprised of distributed and heterogeneous computing resources. The distributed and heterogeneous properties intricate system management, and may impose additional rules and restrictions on the environment while using it. The rules and restrictions are very likely to puzzle application developers and make application optimization difficult to achieve. Most systems in literature aim to optimize the throughput of the entire system, such as Condor, Globus Toolkit, and IOS. Those systems ignore individual application performance in most cases, and thus may not be fare to all users. Furthermore, they cannot handle the environment change seamlessly. This research proposes an alternative computing model relating to cyber organisms, aiming to make applications smarter and more adaptive to environment changes. In this model, the computing environment is not responsible for application optimization and reconfiguration. Instead, it provides necessary information for each individual application through a standard interface. Each application consists of several processes to cooperate some given tasks. The sub-components are able to communicate with each other, sense the change of the environment, and react accordingly. Based on the proposed model, we implement a prototype using Message Passing Interface (MPI). The major contribution of the proposed system is that the applications are self-manageable and self-provisioning. In other words, it can automatically add new processes to a right computing host, delete old processes from a wrong computing host, and move data to balance workload between hosts when the environment changes. Therefore, different applications can be optimized for different purposes. The experimental results confirm that our system can effectively adapt to the change of the environment and automatically improve application performance.
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