【摘要】：隨著近年來云計算技術(shù)的蓬勃發(fā)展，使得Web服務(wù)的研究和應(yīng)用迎來了新的挑戰(zhàn)。而由于Web服務(wù)數(shù)量的增加，Web服務(wù)組合問題的研究也得到了廣泛的關(guān)注。傳統(tǒng)的Web服務(wù)組合一般只考慮服務(wù)的功能性需求，對服務(wù)的非功能性需求和總體服務(wù)質(zhì)量（QoS）考慮較少�？梢哉f，服務(wù)選擇算法的選取是關(guān)系到最終決定服務(wù)組合QoS性能好壞的關(guān)鍵性因素。 首先本文對近年來基于QoS的服務(wù)組合問題從多個研究方向進行了分類和總結(jié)。在選擇優(yōu)化算法的選擇上，普遍采用粒子群算法、蟻群算法、Skyline方法等。因大量實驗已經(jīng)證明布谷鳥算法在解決多目標函數(shù)方面的表現(xiàn)要優(yōu)于其他現(xiàn)存的算法，而且相較于其他的元啟發(fā)式優(yōu)化算法具有更好的通用性,因此作者提出將其應(yīng)用于服務(wù)組合問題。本文首先建立了將QoS的服務(wù)組合問題從多目標問題轉(zhuǎn)化為單目標問題的數(shù)學(xué)模型。通過使用從QWS數(shù)據(jù)庫中選定的相似服務(wù)，，構(gòu)建抽象服務(wù)組合模型。為了驗證該方法的可行性，本文還在提出的數(shù)學(xué)模型的基礎(chǔ)上實現(xiàn)了目前研究最廣泛的基于粒子群算法的Web服務(wù)組合最優(yōu)化問題，通過對比，最終證明了布谷鳥算法在解決Web服務(wù)組合問題上的可行性。最后對原始布谷鳥算法的隨機取值過程進行了改進，并進一步通過實驗驗證，改進的布谷鳥算法在Web服務(wù)組合最優(yōu)化問題的實現(xiàn)上效率的提高。
[Abstract]:With the rapid development of cloud computing technology in recent years, the research and application of Web services is facing new challenges. Due to the increasing number of Web services, the research on Web services composition has been paid more and more attention. The traditional Web service composition only considers the functional requirements of the service, but the non-functional requirements and the overall quality of service (QoS) are less considered. It can be said that the selection of service selection algorithm is the key factor to determine the performance of service composition QoS. Firstly, this paper classifies and summarizes the service composition problems based on QoS in recent years. Particle swarm optimization (PSO), ant colony algorithm (ACO) and Skyline method are widely used in the selection of optimization algorithm. Because a large number of experiments have proved that the cuckoo algorithm is superior to other existing algorithms in solving multi-objective functions, and compared with other meta-heuristic optimization algorithms, it has better universality. Therefore, the author proposes to apply it to the service composition problem. In this paper, a mathematical model is established to transform the service composition problem of QoS from multi-objective problem to single-objective problem. An abstract service composition model is constructed by using similar services selected from the QWS database. In order to verify the feasibility of the proposed method, this paper also implements the most widely studied Web service composition optimization problem based on particle swarm optimization algorithm on the basis of the proposed mathematical model. Finally, the feasibility of cuckoo algorithm in solving Web service composition problem is proved. Finally, the random selection process of the original cuckoo algorithm is improved, and further verified by experiments, the efficiency of the improved cuckoo algorithm in the Web service composition optimization problem is improved.
【學(xué)位授予單位】：東北師范大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2014
【分類號】：TP393.09;TP301.6

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