QoS Based Framework for Effective Web Services in Cloud Computing

Enhancements in technology always follow Consumer requirements. Consumer requires best of service with least possible mismatch and on time. Numerous applications available today are based on Web Services and Cloud Computing. Recently, there exist many Web Services with similar functional characteristics. Choosing “a-right” Service from group of similar Web Service is a complicated task for Service Consumer. In that case, Service Consumer can discover the required Web Service using non functional attributes of the Web Services such as QoS. Proposed layered architecture and Web Service-Cloud, i.e. WS-Cloud computing Framework synthesizes the non functional attributes that includes reliability, availability, response time, latency etc. The Service Consumer is projected to provide the QoS requirements as part of Service discovery query. This framework will discover and filter the Web Services form the cloud and rank them according to Service Consumer preferences to facilitate Service on time.

Toward Cloud Computing QoS Architecture:Analysis of Cloud Systems and Cloud Services

Cloud can be defined as a new computing paradigm that provides scalable, on-demand, and virtualized resources for users. In this style of computing, users can access a shared pool of computing resources which are provisioned with minimal management efforts of users. Yet there are some obstacles and concerns about the use of clouds. Guaranteeing quality of service QoS by service providers can be regarded as one of the main concerns for companies tending to use it. Service provisioning in clouds is based on service level agreements representing a contract negotiated between users and providers. According to this contract, if a provider cannot satisfy its agreed application requirements, it should pay penalties as compensation. In this paper, we intend to carry out a comprehensive survey on the models proposed in literature with respect to the implementation principles to address the QoS guarantee issue. © 2014 Chinese Association of Automation.

Neighborhood Search Based Improved Bat Algorithm for Web Service Composition

Web services are provided as reusable software components in the services-oriented architecture.More complicated composite services can be combined from these components to satisfy the user requirements represented as a workflow with specified Quality of Service(QoS)limitations.The workflow consists of tasks where many services can be considered for each task.Searching for optimal services combination and optimizing the overall QoS limitations is a Non-deterministic Polynomial(NP)-hard problem.This work focuses on the Web Service Composition(WSC)problem and proposes a new service composition algorithm based on the micro-bats behavior while hunting the prey.The proposed algorithm determines the optimal combination of the web services to satisfy the complex user needs.It also addresses the Bat Algorithm(BA)shortcomings,such as the tradeoff among exploration and exploitation searching mechanisms,local optima,and convergence rate.The proposed enhancement includes a developed cooperative and adaptive population initialization mechanism.An elitist mechanism is utilized to address the BA convergence rate.The tradeoff between exploration and exploitation is handled through a neighborhood search mechanism.Several benchmark datasets are selected to evaluate the proposed bat algorithm’s performance.The simulation results are estimated using the average fitness value,the standard deviation of the fitness value,and an average of the execution time and compared with four bat-inspired algorithms.It is observed from the simulation results that introduced enhancement obtains significant results.

Toward a More Accurate Web Service Selection Using Modified Interval DEA Models with Undesirable Outputs

With the growing number of Web services on the internet,there is a challenge to select the best Web service which can offer more quality-of-service(QoS)values at the lowest price.Another challenge is the uncertainty of QoS values over time due to the unpredictable nature of the internet.In this paper,we modify the interval data envelopment analysis(DEA)models[Wang,Greatbanks and Yang(2005)]for QoS-aware Web service selection considering the uncertainty of QoS attributes in the presence of desirable and undesirable factors.We conduct a set of experiments using a synthesized dataset to show the capabilities of the proposed models.The experimental results show that the correlation between the proposed models and the interval DEA models is significant.Also,the proposed models provide almost robust results and represent more stable behavior than the interval DEA models against QoS variations.Finally,we demonstrate the usefulness of the proposed models for QoS-aware Web service composition.Experimental results indicate that the proposed models significantly improve the fitness of the resultant compositions when they filter out unsatisfactory candidate services for each abstract service in the preprocessing phase.These models help users to select the best possible cloud service considering the dynamic internet environment and they help service providers to improve their Web services in the market.

基于改良蜂群算法的Web服务组合优化方法

为提高Web组合优化算法的开发能力和运行结果的适应度、稳定性,以满足用户对Web服务的服务质量(Quality of Service,QoS)需求,提出了一种基于QoS模型和改良蜂群算法(modified Artificial Bee Colony,mABC)的Web服务组合优化方法。构建应用于Web服务组合优化问题的QoS顺序数学模型,使用基于混沌的对立学习方法,在进程运行的初始化阶段生成更好的初始群体,在蜂群算法的雇佣蜂阶段和围观蜂阶段使用新的相位搜索方程和围观搜索策略,有效地提高蜂群算法的探测能力和开发能力。将改良蜂群算法与人工蜂群算法(Artificial Bee Colony,ABC)、差分进化算法(Differential Evolution,DE)、改进灰狼优化算法(Modified Grey Wolf Optimizer,MGWO)、最优导向人工蜂群算法(Guided-best Artificial Bee Colony,GABC)和改进人工蜂群算法(Improved Artificial Bee Colony,IABC)进行了多次对比实验。实验结果表明,改良蜂群算法尽管在执行时间方面比其余算法都要略微长一些,但它在更为重要的适应度、稳定性方面都优于其余几种对比算法。

Cloud Computing-Based Forensic Analysis for Collaborative Network Security Management System

Internet security problems remain a major challenge with many security concerns such as Internet worms, spam, and phishing attacks. Botnets, well-organized distributed network attacks, consist of a large number of bots that generate huge volumes of spam or launch Distributed Denial of Service （DDoS） attacks on victim hosts. New emerging botnet attacks degrade the status of Internet security further. To address these problems, a practical collaborative network security management system is proposed with an effective collaborative Unified Threat Management （UTM） and traffic probers. A distributed security overlay network with a centralized security center leverages a peer-to-peer communication protocol used in the UTMs collaborative module and connects them virtually to exchange network events and security rules. Security functions for the UTM are retrofitted to share security rules. In this paper, we propose a design and implementation of a cloud-based security center for network security forensic analysis. We propose using cloud storage to keep collected traffic data and then processing it with cloud computing platforms to find the malicious attacks. As a practical example, phishing attack forensic analysis is presented and the required computing and storage resources are evaluated based on real trace data. The cloud- based security center can instruct each collaborative UTM and prober to collect events and raw traffic, send them back for deep analysis, and generate new security rules. These new security rules are enforced by collaborative UTM and the feedback events of such rules are returned to the security center. By this type of close-loop control, the collaborative network security management system can identify and address new distributed attacks more quickly and effectively.

面向瘦客户端的WebOS研究

基于浏览器的WebOS是操作系统技术向网络化发展的一个典型代表。WebOS整合Internet上服务和资源,供在线用户"随时随地"使用,这种特点使得它将成为未来瘦客户端Web应用的一种重要使用模式。首先阐述了WebOS的由来、概念和组成,接着分析了WebOS的发展现状和趋势,然后论述了制约其发展的主要技术因素。在此基础上,选择较有代表性的开源EyeOS进行了深入研究,分析了其原理和组成,并对其服务器端功能进行了扩充。

基于云计算仿真平台的Web Service探究

本文主要介绍了基于云计算仿真平台的Web Service研究,提出了与计算仿真平台的建立及体系架构,以及在该平台下采用虚拟化技术对子云层进行整合,为Web Service提供服务的关键技术,发挥了平台的可用性、协同性、扩展性等特点。

云计算与WebService技术在高校数字化校园中的实践

本文介绍了云计算与Web Service技术在数字化校园建设中的实际运用。数字校园整体架构为六层设计,最底层利用OpenStack搭建了Iaas服务,构成数字化校园的基础平台;业务层利用Web Service技术实现了统一的用户管理、权限管理和资源管理,使得各个具体业务能够紧密融合。

基于Web Services的云服务安全方案分析与研究

在分析云安全和云服务的基础上,通过分析云计算遇到的安全问题,给出了云安全体系架构模型和安全机制体系,提出了基于Web Services的云服务安全方案,详细阐述了该方案中设计的关键安全机制,设计了方案实现的模型和访问流程,通过分析证明了其安全性,为云服务安全构架提供了有效的理论基础。

Artificial Bee Colony with Cuckoo Search for Solving Service Composition

In recent years,cloud computing has provided a Software As A Service(SaaS)platform where the software can be reused and applied to fulfill compli-cated user demands according to specific Quality of Services(QoS)constraints.The user requirements are formulated as a workflow consisting of a set of tasks.However,many services may satisfy the functionality of each task;thus,searching for the composition of the optimal service while maximizing the QoS is formulated as an NP-hard problem.This work will introduce a hybrid Artificial Bee Colony(ABC)with a Cuckoo Search(CS)algorithm to untangle service composition problem.The ABC is a well-known metaheuristic algorithm that can be applied when dealing with different NP-hard problems with an outstanding record of performance.However,the ABC suffers from a slow convergence problem.Therefore,the CS is used to overcome the ABC’s limitations by allowing the abandoned bees to enhance their search and override the local optimum.The proposed hybrid algorithm has been tested on 19 datasets and then compared with two standard algorithms(ABC and CS)and three state-of-the-art swarm-based composition algorithms.In addition,extensive parameter study experiments were conducted to set up the proposed algorithm’s parameters.The results indicate that the proposed algorithm outperforms the standard algorithms in the three comparison criteria(bestfitness value,averagefitness value,and average execution time)overall datasets in 30 different runs.Furthermore,the proposed algorithm also exhibits better performance than the state–of–the–art algorithms in the three comparison criteria over 30 different runs.

OpenRS-Cloud:A remote sensing image processing platform based on cloud computing environment

This paper explores the use of cloud computing for remote sensing image processing.The main contribution of our work is to develop a remote sensing image processing platform based on cloud computing technology(OpenRS-Cloud).This paper focuses on enabling methodical investigations into the development pattern,computational model,data management and service model exploring this novel distributed computing model.The experimental INSAR processing flow is implemented to verify the efficiency and feasibility of OpenRS-Cloud platform.The results show that cloud computing is well suited for computationally-intensive and data-intensive remote sensing services.

Generation of Labelled Datasets to Quantify the Impact of Security Threats to Cloud Data Centers

Anomaly based approaches in network intrusion detection suffer from evaluation, comparison and deployment which originate from the scarcity of adequate publicly available network trace datasets. Also, publicly available datasets are either outdated or generated in a controlled environment. Due to the ubiquity of cloud computing environments in commercial and government internet services, there is a need to assess the impacts of network attacks in cloud data centers. To the best of our knowledge, there is no publicly available dataset which captures the normal and anomalous network traces in the interactions between cloud users and cloud data centers. In this paper, we present an experimental platform designed to represent a practical interaction between cloud users and cloud services and collect network traces resulting from this interaction to conduct anomaly detection. We use Amazon web services (AWS) platform for conducting our experiments.

一种基于云计算的语义Web服务组合模型研究

提出一种基于云计算的语义服务组合模型.通过云计算中的云概念,把云中的云滴与Web服务结合起来进行研究,并采用正态云进行刻画,分析出具有正态云特征的Web服务,并进行相关定义与描述;同时,采用正态云发生器算法来实现服务发现、组合.采用一种云计算的语义服务组合的结构进行实验表明,此方法可行.

基于云仿真的Web服务选择研究

针对当前Web服务海量增加,而现有的Web服务选择算法低效、缓慢的问题,提出了一种基于云计算的粒子群优化算法的Web服务选择方法。该方法在云平台下对粒子分群映射、相似分群并行化简、适时更新分群,并且寻找与用户需求最相似、服务质量最好的策略。实验表明,该方法能有效减少流程执行过程中Web服务选择导致的时间开销,并提高Web服务选择的可靠性。

云环境下Web服务应用层DDoS攻击检测系统

针对云计算环境中的Web服务应用层容易遭受攻击的问题,提出一种用来检测XML和HTTP层分布式拒绝服务(DDo S)攻击的防御系统,并嵌入到云环境中,实现对云中介和云服务提供商的保护。从属于特定简单对象访问协议(SOAP)正常操作中提取数据集的特征值,构建相应的高斯请求模型;对Web服务的网络服务描述语言(WSDL)中的一些属性进行设置,实现对攻击的初步过滤;对服务请求的HTTP头部和XML内容进行检查,并与模型数据比较,进一步实现攻击检测。实验结果表明,该系统能够有效地预防多种DDo S攻击,且消耗较少的响应时间。

云计算环境下Web服务集成系统的研究

作为云平台提升应用性能的一种重要手段,Web服务集成技术近年来受到了工业界和学术界的广泛关注。从云计算与Web服务集成技术的结合入手,分析设计了基于云计算的系统体系结构,并基于此提出了基于Web Services的异构数据集成方法和应用集成的总体架构。最后,给出了该系统的相关实现实例。实验表明,该系统架构的应用在降低构建成本的同时大幅提高了系统性能。

云计算环境下大规模Web服务故障诊断技术研究

随着Web服务规模的不断增大,系统中往往会伴随着大量的噪音数据;为了提高Web服务诊断在噪音影响下的健壮性,文章研究了大规模Web服务下的故障诊断;首先,提出了一种Web服务自动诊断框架;其次,分别定义了转移矩阵和发射矩阵,并通过这两种矩阵来表达Web服务的状态转换过程;最后,提出了一种基于Viterbi方法的故障诊断算法;实验表明,文章提出的算法与其它相关的Web服务故障诊断算法相比准确性高,并且对噪音数据有着良好的健壮性。

基于云计算技术的电子病历管理系统设计与研究

电子病历(Electronic Medical Record,EMR)作为病人医疗信息载体,能够为医生提供真实有效的病人过往病情信息。同时随着互联网的快速发展,云计算的出现让电子病历可以跨医院实现共享,为医生更快速有效地判断病人病情并提供有效的治疗手段。该文建立了基于云计算的Web服务连接各医院数据信息库实现电子病历区域数据共享,同时使用XML技术使信息快速转换并且信息储存具有高度私密性。通过测试表明,基于云计算技术的电子病历管理系统,能够实现病人电子病历数据的安全有效传输。

云环境下基于用户偏好的粒子群优化算法的Web服务选择

针对当前Web服务的海量增加,而现有的服务选择算法低效以及粒子群算法在复杂的组合优化类问题上的不足,该算法分析用户对于Web服务的一些软性偏好,提出了一种在云环境下基于用户偏好的粒子群改进算法的Web服务选择.该算法通过对粒子分群映射、相似分群并行化简,同时利用模糊约束来表达用户的偏好,最终使得用户能够根据偏好从中进行选择.实验表明,该算法能有效减少执行过程中Web服务选择导致的时间开销,并提高服务选择的性能.