基于最优树算法的服务组合算法研究

SOA在各个领域的集成发展,业务与IT之间就逐渐构成了以服务集成的服务契约解耦,其价值直接体现是他们之间的灵活性和服务质量,而服务组合是实现这一过程的关键。在实现过程中,通过以服务为单位的组合依赖关系来构建业务流程,完成业务处理和用户需求。而服务组合的优越性一直倍受研究,因此提出以依赖强度的最优树算法来实现一种新的服务组合算法。

一种基于语义的Web服务组合算法研究

语义Web服务组合算法研究对于Web服务组合有着重要的意义。说明一种基于语义的Web服务组合算法的思想,给出服务组合框架和算法的工作流程。它的核心是通过语义I/O和P/E的匹配来实现自动化Web服务组合,本质是通过交互不断地寻找合适的前继服务,以满足用户的服务请求。

Web服务组合QoS最优化问题研究

随着云计算的蓬勃发展,Web服务的研究和应用也迎来了新的挑战。传统的服务组合一般只考虑到服务的功能性需求,对服务的非功能性需求和总体服务质量(QoS)考虑较少。本文首先对近年来基于QoS的服务组合问题进行了归纳总结,目前大多数研究都是基于粒子群算法、模拟退火算法,skyline方法等。本文做出新的尝试,提出将布谷鸟算法应用于服务组合问题,通过使用从QWS数据集中挑选出的相似服务构建服务集进行实验,与传统的应用粒子群算法的服务组合方法进行对比,对提出的方法的可行性进行了验证。

Automatic Web services composition algorithm based on optimal matching

A novel layered method was proposed to solve the problem of Web services composition.In this method,services composition problem was formally transformed into the optimal matching problem of every layer,then optimal matching problem was modeled based on the hypergraph theory,and solved by computing the minimal transversals of the hypergraph.Meanwhile,two optimization algorithms were designed to discard some useless states at the intermediary steps of the composition algorithm.The effectiveness of the composition method was tested by a set of experiments,in addition,an example regarding the travel services composition was also given.The experimental results show that this method not only can automatically generate composition tree whose leaf nodes correspond to services composition solutions,but also has better performance on execution time and solution quality by adopting two proposed optimization algorithms.

Optimizing bus services with variable directional and temporal demand using genetic algorithm

As a major mode choice of commuters for daily travel, bus transit plays an important role in many urban and metropolitan areas. This work proposes a mathematical model to optimize bus service by minimizing total cost and considering a temporally and directionally variable demand. An integrated bus service, consisting of all-stop and stop-skipping services is proposed and optimized subject to directional frequency conservation, capacity and operable fleet size constraints. Since the research problem is a combinatorial optimization problem, a genetic algorithm is developed to search for the optimal result in a large solution space. The model was successfully implemented on a bus transit route in the City of Chengdu, China, and the optimal solution was proved to be better than the original operation in terms of total cost. The sensitivity of model parameters to some key attributes/variables is analyzed and discussed to explore further the potential of accruing additional benefits or avoiding some of the drawbacks of stop-skipping services.

Pre-filtering based automatic composition of multi-QoS semantic web services

To support the rapid automatic services composition and fulfill multi-quality of service （multi- QoS） demand, we propose a novel approach to realize services composition automatically by a prefihering process. Aimed at a set of web services with similar functionality and different quality of service （QoS） , a semantic services chain is given and a corresponding constructing algorithm is proposed to construct the data structure. A pre-filtering process is put forward to find whether a composition service before planning exists. It can avoid aborted planning. An optimal planning algorithm is proposed which can choose the most suitable service from a lot of similar candidate services based on semantic service chains and multi-QoS values. The algorithms can improve the correctness and automation performances of automated semantic web services composition. As an example, a concrete composite process is analyzed. Experimental results show the validity of the composite process.

CHC-TSCM:A Trustworthy Service Composition Method Based on an Improved CHC Genetic Algorithm

Trustworthy service composition is an extremely important task when service composition becomes infeasible or even fails in an environment which is open,autonomic,uncertain and deceptive.This paper presents a trustworthy service composition method based on an improved Cross generation elitist selection,Heterogeneous recombination,Catacly-smic mutation(CHC) Trustworthy Service Composition Method(CHC-TSCM) genetic algorithm.CHCTSCM firstly obtains the total trust degree of the individual service using a trust degree measurement and evaluation model proposed in previous research.Trust combination and computation then are performed according to the structural relation of the composite service.Finally,the optimal trustworthy service composition is acquired by the improved CHC genetic algorithm.Experimental results show that CHC-TSCM can effectively solve the trustworthy service composition problem.Comparing with GODSS and TOCSS,this new method has several advantages:1) a higher service composition successrate;2) a smaller decline trend of the service composition success-rate,and 3) enhanced stability.

Multi-Strategy Improvement of Sparrow Search Algorithm for Cloud Manufacturing Service Composition

In existing research,the optimization of algorithms applied to cloud manufacturing service composition based on the quality of service often suffers from decreased convergence rates and solution quality due to single-population searches in fixed spaces and insufficient information exchange.In this paper,we introduce an improved Sparrow Search Algorithm(ISSA)to address these issues.The fixed solution space is divided into multiple subspaces,allowing for parallel searches that expedite the discovery of target solutions.To enhance search efficiency within these subspaces and significantly improve population diversity,we employ multiple group evolution mechanisms and chaotic perturbation strategies.Furthermore,we incorporate adaptive weights and a global capture strategy based on the golden sine to guide individual discoverers more effectively.Finally,differential Cauchy mutation perturbation is utilized during sparrow position updates to strengthen the algorithm's global optimization capabilities.Simulation experiments on benchmark problems and service composition optimization problems show that the ISSA delivers superior optimization accuracy and convergence stability compared to other methods.These results demonstrate that our approach effectively balances global and local search abilities,leading to enhanced performance in cloud manufacturing service composition.

T-QoS-aware based parallel ant colony algorithm for services composition

In order to make cloud users get credible, high-quality composition of services, the trust quality of service aware(TQoS-aware) based parallel ant colony algorithm is proposed. Our approach takes the service credibility as the weight of the quality of service, then calculates the trust service quality T-QoS for each service, making the service composition situated in a credible environment. Through the establishment on a per-service T-QoS initialization pheromone matrix, we can reduce the colony's initial search time. By modifying the pheromone updating rules and introducing two ant colonies to search from different angles in parallel,we can avoid falling into the local optimal solution, and quickly find the optimal combination of global solutions. Experiments show that our approach can combine high-quality services and the improvement of the operational success rate. Also, the convergence rate and the accuracy of optimal combination are improved.