本文選題：Web服務(wù)組合 + QoS�。� 參考：《南京財(cái)經(jīng)大學(xué)》2014年碩士論文

【摘要】：Web服務(wù)是一個嶄新的分布式計(jì)算模型,能有效地實(shí)現(xiàn)網(wǎng)絡(luò)中數(shù)據(jù)和信息的集成,是集成技術(shù)新的發(fā)展方向。由于現(xiàn)在功能相同但QoS不同的Web服務(wù)越來越多,這導(dǎo)致了服務(wù)的搜索空間不斷增大,也使得服務(wù)組合問題變得更加復(fù)雜。基于此,本文設(shè)計(jì)了一個Pareto多目標(biāo)人工蜂群算法來解決服務(wù)組合優(yōu)化問題,主要工作如下：首先,本文給出了一種Pareto解集的構(gòu)造方法,在解決多目標(biāo)優(yōu)化問題時(shí),通常直接比較當(dāng)前進(jìn)化種群中每個解的適應(yīng)度值,最終只產(chǎn)生一個最優(yōu)解推薦給用戶。但在處理Web服務(wù)組合這一實(shí)際問題時(shí),由于網(wǎng)絡(luò)中的服務(wù)錯綜復(fù)雜,甚至?xí)幸恍┨摷俜⻊?wù),單個的組合方案很難滿足用戶的特定需求。所以,本文采用構(gòu)造當(dāng)前種群Pareto解集的方式來解決多目標(biāo)優(yōu)化問題,最后推薦給用戶一組非劣解,以此來更好的解決Web服務(wù)組合這一實(shí)際問題。接著,本文對蜂群算法進(jìn)行了改進(jìn),原始算法在解的選擇階段采用輪盤賭策略進(jìn)行解的選擇,但這種策略會使算法容易過早收斂,種群的多樣性較差�；诖�,本文采用Bolzmann策略來改進(jìn)算法,該策略可使算法的全局搜索能力更好,種群的多樣性也能夠得到提高。同時(shí),本文對蜜源放棄策略做了相應(yīng)的調(diào)整,對領(lǐng)域搜索公式進(jìn)行了相應(yīng)改進(jìn),以適應(yīng)Web服務(wù)組合這一實(shí)際問題。最后,通過仿真實(shí)驗(yàn)驗(yàn)證本文提出的改進(jìn)方案的可行性。實(shí)驗(yàn)表明改進(jìn)方案可以使種群的多樣性增加,有效地避免“早熟”現(xiàn)象,最后產(chǎn)生的組合方案更能滿足實(shí)際情況中用戶需求。從而表明該方法可以更好地處理Web服務(wù)組合優(yōu)化問題。
[Abstract]:Web Services is a new distributed computing model, which can effectively realize the integration of data and information in the network. It is a new development direction of integration technology. Because there are more and more Web services with the same function but different QoS, this leads to the increasing search space of the services and the complexity of the service composition problem. Based on this, a Pareto multi-objective artificial bee colony algorithm is designed to solve the service composition optimization problem. The main work is as follows: firstly, this paper presents a method to construct the Pareto solution set, which is used to solve the multi-objective optimization problem. Usually, the fitness of each solution in the current evolutionary population is directly compared, and only one optimal solution is recommended to the user. However, in dealing with the practical problem of Web service composition, because of the complexity of services in the network and even some false services, it is difficult for a single composition scheme to meet the specific needs of users. Therefore, this paper uses the method of constructing the current population Pareto solution set to solve the multi-objective optimization problem, and finally recommends a group of non-inferior solutions to the user, so as to better solve the practical problem of Web service composition. Then, the bee colony algorithm is improved in this paper. The original algorithm adopts roulette strategy to select the solution in the phase of solution selection, but this strategy will make the algorithm easy to converge prematurely and the diversity of population is poor. Based on this, the Bolzmann strategy is adopted to improve the algorithm. This strategy can improve the global search ability of the algorithm and the diversity of the population. At the same time, this paper adjusts the policy of honey source abandonment and improves the domain search formula to meet the practical problem of Web service composition. Finally, the feasibility of the proposed scheme is verified by simulation experiments. The experimental results show that the improved scheme can increase the diversity of the population, effectively avoid the phenomenon of "precocity", and the resulting combination scheme can better meet the needs of the users in the actual situation. It is shown that this method can better deal with the problem of Web service composition optimization.
【學(xué)位授予單位】：南京財(cái)經(jīng)大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2014
【分類號】：TP18;TP393.09

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本文編號：1883119