云计算技术研究现状综述
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云计算技术的发展现状及未来趋势展望一、引言云计算技术是近年来迅速发展的一项重要技术,它不仅改变了现代计算方式,也对各行各业产生了深远的影响。
本文将综述云计算技术的发展现状,分析其未来的趋势展望。
二、云计算技术的发展现状1. 基础设施建设:大型云计算平台的建设已逐渐完善,包括服务器、存储设备和网络基础设施等。
各大云服务提供商通过数据中心的建设,为用户提供高质量的计算资源。
2. 多样化的服务模式:云计算技术提供了多样化的服务模式,包括基础设施即服务(IaaS)、平台即服务(PaaS)和软件即服务(SaaS)。
用户可以根据需求选择相应的服务模式,实现灵活的资源调度。
3. 大数据与人工智能的结合:随着大数据和人工智能的迅猛发展,云计算技术将二者有效结合,为用户提供更强大的计算和分析能力。
云计算平台不仅可以存储和处理大量的数据,还可以进行深度学习和智能决策等。
4. 安全和隐私问题的关注:随着云计算技术的普及应用,安全和隐私问题成为关注的焦点。
云服务提供商需要加强安全防护,保护用户的数据安全和隐私。
同时,法律法规也在不断完善,以保障用户的权益。
三、云计算技术的未来趋势展望1. 边缘计算的兴起:随着物联网的快速发展,边缘计算将成为云计算技术的重要方向。
将计算和存储资源移到距离用户更近的边缘设备上,可以提高响应速度和减少网络延迟,满足实时性要求。
2. 混合云的发展:混合云将私有云和公有云结合起来,为用户提供更灵活的计算资源选择。
用户可以根据实际需求,通过混合云实现对敏感数据的保护和对公共资源的利用。
3. 自动化运维和智能管理:未来的云计算平台将实现更高度的自动化运维和智能管理。
通过引入自动化工具和人工智能算法,可以实现资源的动态调度和故障的自愈,提高系统的稳定性和可靠性。
4. 扩展到更多领域:云计算技术将向更多领域延伸,如医疗保健、金融、交通等。
通过将云计算技术与各行业的实际需求相结合,可以推动行业的创新和转型升级。
计算机文献综述范文3000字引言计算机科学与技术是一个快速发展的领域,每年都有大量的研究论文涉及到各种各样的主题。
本文旨在对计算机科学与技术领域的一些重要研究进行综述,以探讨当前的研究趋势和未来的发展方向。
一、人工智能人工智能(Artificial Intelligence,AI)是计算机科学与技术领域的一个重要研究方向。
近年来,随着深度学习技术的快速发展,人工智能在图像识别、自然语言处理、智能推荐等方面取得了显著的进展。
例如,深度神经网络在图像识别领域的应用已经达到甚至超过了人类的水平。
此外,强化学习算法在游戏领域的应用也取得了重要的突破,比如AlphaGo在围棋比赛中战胜了世界冠军。
然而,人工智能研究还面临一些挑战。
首先,深度学习算法需要大量的标注数据进行训练,而获取大规模标注数据是一项非常耗时和困难的任务。
其次,深度学习算法的黑盒性质使得其解释性较差,难以理解其决策过程。
此外,人工智能在伦理和法律方面也引发了一系列的讨论和争议,比如自动驾驶汽车的安全性和责任归属等问题。
二、大数据与数据挖掘随着互联网的快速发展,大数据成为了一个热门的研究领域。
大数据的特点是数据量大、数据类型多样、数据生成速度快。
数据挖掘是从大数据中提取有价值信息的一项重要技术。
近年来,大数据与数据挖掘在各个领域的应用越来越广泛,比如金融、医疗、电子商务等。
在大数据与数据挖掘领域,一些重要的研究方向包括数据预处理、特征选择、聚类分析、分类算法等。
例如,数据预处理是在数据挖掘之前对原始数据进行清洗和转换的过程,以提高数据挖掘算法的性能。
特征选择是从众多特征中选择出最有代表性的特征,以减少数据维度和提高分类算法的性能。
三、云计算与边缘计算云计算和边缘计算是计算机科学与技术领域的另外两个热门研究方向。
云计算是一种基于互联网的计算模式,通过将计算和存储资源集中在云端,实现资源的共享和高效利用。
边缘计算是一种将计算和存储资源放置在离用户更近的地方,以减少网络延迟和提高用户体验的计算模式。
本文档包括该专题的:外文文献、文献综述文献标题:An exploratory study on factors affecting the adoption of cloud computing by information professionals作者:Aharony, Noa期刊:The Electronic Library, 33(2), 308-328.年份:2015一、外文文献An exploratory study on factors affecting the adoption of cloud computing byinformation professionals(影响云计算采用与否的一个探索性研究)Aharony, NoaPurpose- The purpose of this study explores what factors may influence information professionals to adopt new technologies, such as cloud computing in their organizations. The objectives of this study are as follows: to what extent does the technology acceptance model (TAM) explain information professionals intentions towards cloud computing, and to what extent do personal characteristics, such as cognitive appraisal and openness to experience, explain information professionals intentions to use cloud computing.Design/methodology/approach- The research was conducted in Israel during the second semester of the 2013 academic year and encompassed two groups of information professionals: librarians and information specialists. Researchers used seven questionnaires to gather the following data: personal details, computer competence, attitudes to cloud computing, behavioral intention, openness to experience, cognitive appraisal and self-efficacy. Findings- The current study found that the behavioral intention to use cloud computing was impacted by several of the TAM variables, personal characteristics and computer competence.Originality/value- The study expands the scope of research about the TAM by applying it to information professionals and cloud computing and highlights the importance of individual traits, such as cognitive appraisal, personal innovativeness, openness to experience and computer competence when considering technology acceptance. Further, the current study proposes that if directors of information organizations assume that novel technologies may improve their organizations' functioning, they should be familiar with both the TAM and the issue of individual differences. These factors may help them choose the most appropriate workers.Keywords: Keywords Cloud computing, TAM, Cognitive appraisal, Information professionals, Openness to experienceIntroductionOne of the innovations that information technology (IT) has recently presented is thephenomenon of cloud computing. Cloud computing is the result of advancements in various technologies, including the Internet, hardware, systems management and distributed computing (Buyya et al. , 2011). Armbrust et al. (2009) suggested that cloud computing is a collection of applications using hardware and software systems to deliver services to end users via the Internet. Cloud computing offers a variety of services, such as storage and different modes of use (Leavitt, 2009). Cloud computing enables organizations to deliver support applications and avoid the need to develop their own IT systems (Feuerlicht et al. , 2010).Due to the growth of cloud computing use, the question arises as to what factors may influence information professionals to adopt new technologies, such as cloud computing, in their organizations. Assuming that using new technologies may improve the functioning of information organizations, this study seeks to explore if information professionals, who often work with technology and use it as an important vehicle in their workplace, are familiar with technological innovations and whether they are ready to use them in their workplaces. As the phenomenon of cloud computing is relatively new, there are not many surveys that focus on it and, furthermore, no one has so far focussed on the attitudes of information professionals towards cloud computing. The research may contribute to an understanding of the variables that influence attitudes towards cloud computing and may lead to further inquiry in this field.The current study uses the well-known technology acceptance model (TAM), a theory for explaining individuals' behaviours towards technology (Davis, 1989; Venkatesh, 2000), as well as personal characteristics, such as cognitive appraisal and openness to new experiences, as theoretical bases from which we can predict factors which may influence information professionals adopting cloud computing in their workplaces. The objectives of this study are to learn the following: the extent to which the TAM explains information professionals' attitudes towards cloud computing, and the extent to which personal characteristics, such as cognitive appraisal and openness to experiences, explain the intention of information professionals to use cloud computing.Theoretical backgroundCloud computingResearchers have divided cloud computing into three layers: Software as a Service (SaaS), Platform as a Service (PaaS) and Infrastructure as a Service (IaaS). SaaS has changed the concept of software as a product to that of a service instead. The software runs in the cloud and the user can access it via the Internet to work on an application. PaaS enables powerful tools for developers to create the applications, without having to deal with concerns about the infrastructure. IaaS provides complete infrastructure resources (e.g. servers, software, network equipment and storage). With IaaS, consumers do not have to purchase the latest technology, perform maintenance, upgrade software or buy software licenses (Anuar et al. , 2013). Cloud computing deployment can be divided into four types: private clouds, public clouds, community clouds and hybrid clouds (Mell and Grance, 2011). Public clouds have open access, private clouds run within organizations, community clouds containresources that are shared with others in the community and hybridclouds encompass two or more cloud models. Anuar et al. (2013) presented the main characteristics of cloud computing: flexible scale that enables flexible-scale capabilities for computing; virtualization that offers a new way of getting computing resources remotely, regardless of the location of the user or the resources; high trust , as the cloud offers more reliability to end users than relying on local resources; versatility , because cloud services can serve different sectors in various disciplines use the same cloud; and on demand service , as end users can tailor their service needs and pay accordingly.As cloud computing is relatively new, there are not a lot of surveys that focus on it. Several researchers conducted in-depth interviews investigating respondents' attitudes towards keeping their virtual possessions in the online world (Odom et al. , 2012). Teneyuca (2011) reported on a survey of cloud computing usage trends that included IT professionals as respondents. Results revealed preferences for virtualization and cloud computing technologies. However, the major reasons for cloud computing adoption being impeded were the lack of cloud computing training (43 per cent) and security concerns (36 per cent). Another report showed that nearly 40 per cent of Americans think that saving data to their hard drive is more secure than saving it to a cloud (Teneyuca, 2011). A further study (Ion et al., 2011) explored private users' privacy attitudes and beliefs about cloud computing in comparison with those in companies. Anuar et al. (2013) investigated cloud computing in an academic institution, claiming that cloud computing technology enhances performance within the academic institution. A study that was carried out in the education arena examined factors that led students to adopt cloud computing technology (Behrend et al. , 2010). Technology acceptance modelThe TAM (Davis, 1989) is a socio-technical model which aims to explain user acceptance of an information system. It is based on the theory of reasoned action (TRA) (Fishbein and Ajzen, 1975) which seeks to understand how people construct behaviours. The model suggests that technology acceptance can be explained according to the individual's beliefs, attitudes and intentions (Davis, 1989). The TAM hypothesizes that one's intention is the best predictor of usage behaviour and suggests that an individual's behavioural intention to use technology is determined by two beliefs: perceived usefulness (PU) and perceived ease of use (PEOU). PU refers to the individual's perception that using a technology will improve performance and PEOU addresses a user's perceptions that using a particular system would be free of effort (Davis, 1989). The current study concentrates on PEOU as the researchers wanted to examine if information professionals' perceptions about new technology is affected by its simplicity and friendly interface. Earlier research mainly investigated personal behaviour to use new information systems and technology in the following: corporate environments (Gefen and Straub, 1997);Web shopping (Chang et al. , 2002; Lin and Lu, 2000);education, particularly e-learning (Park, 2009) and m-learning (Aharony, 2014); and the library arena (Aharony, 2011; Park et al. , 2009).Personal innovativenessA construct which may contribute to information professionals' intention behaviour to use cloud computing is personal innovativeness, a major characteristic in innovation diffusion research in general (Agarwal and Prasad, 1998; Rogers, 1983, 1995). Agarwal and Prasad (1998) have coined the term "personal innovativeness in the domain of IT" (PIIT), which describes a quite stable characteristic of the individual across situational considerations. Previous studies found that personal innovativeness is a significant determinant of PEOU, as well as of PU (Agarwal and Karahanna, 2000; Lewis et al. , 2003). Several researchers have suggested that innovative people will search for intellectually or sensorially stimulating experiences (Uray and Dedeoglu, 1997).Openness to experienceAnother variable that may predict respondents' perspectives towards cloud computing is openness to experience which addresses the tendency to search for new and challenging experiences, to think creatively and to enjoy intellectual inquiries (McCrae and Sutin, 2009). People who are highly open to experience are perceived as also open to new challenges, thoughts and emotions (McCrae and Costa, 2003). Studies reported that there is a positive relation between openness to experience and intelligence tests (Gignac et al. , 2004). According to Weiss et al. (2012), challenging transitions may influence differently those who are high or low in openness to experience. Those who are high may approach these situations with curiosity, emphasizing the new possibilities offered to them. However, those who are low in openness may be threatened and try to avoid them by adhering to predictable environments. Various researchers note that people who are high in openness to experience are motivated to resolve new situations (McCrae, 1996; Sorrentino and Roney, 1999). Furthermore, openness to experience is associated with cognitive flexibility and open-mindedness (McCrae and Costa, 1997), and negatively associated with rigidity, uncertainty and inflexibility (Hodson and Sorrentino, 1999). Thus, people who are less open to experience tend to avoid novelty and prefer certainty. Studies reveal that openness to experience declines in the later years (Allemand et al. , 2007; Donnellan and Lucas, 2008).Challenge and threatThe following section will focus on the personality characteristics of challenge and threat that might affect information professionals' behavioural intention to use cloud computing. Challenge and threat are the main variables of a unidimensional, bipolar motivational state. They are the result of relative evaluations of situational demands and personal resources that are influenced both by cognitive and affective processes in motivated performance situations (Vick et al. , 2008). According to Lazarus and Folkman (1984), challenge refers to the potential for growth or gain and is characterized by excitement and eagerness, while threat addresses potential harm and is characterized by anxiety, fear and anger. Situations that suggest low demands and high resources are described as challenging, while those that suggest high demands and low resources are perceived as threatening (Seginer, 2008). In general, challenge or threat can take place in situations such as delivering a speech, taking a test, sports competitions or performing with another person on a cooperative or competitive task.The challenge appraisal suggests that with effort, the demands of the situation can be overcome (Lazarus et al. , 1980; Park and Folkman, 1997). On the other hand, threat appraisal indicates potential danger to one's well-being or self-esteem (Lazarus, 1991; Lazarus and Folkman, 1984), as well as low confidence in one's ability to cope with the threat (Bandura, 1997; Lazarus, 1991; Lazarus and Folkman, 1984). Different studies (Blascovich et al. , 2002; Blascovich and Mendes, 2000; Lazarus and Folkman, 1984; Lazarus et al. , 1980) have found that challenge leads to positive feelings associated with enjoyment, better performance, eagerness and anticipation of personal rewards or benefits. Several studies which focussed on the threat and challenge variable were carried out in the library and information science environment as well (Aharony, 2009, 2011).Self-efficacyAn additional variable which may influence individuals' behavioural intention to use cloud computing is self-efficacy. The concept of self-efficacy was developed in the discipline of "social learning theory" by Bandura (1997). Self-efficacy addresses individuals' beliefs that they possess the resources and skills needed to perform and succeed in a specific task. Therefore, individuals' previous performance and their perceptions of relevant resources available may influence self-efficacy beliefs (Bandura, 1997). Self-efficacy is not just an ability perception, it encompasses the motivation and effort required to complete the task and it helps determine which activities are required, the effort in pursuing these activities and persistence when facing obstacles (Bandura, 1986, 1997). The construct of self-efficacy is made up of four principal sources of information:"mastery experience" refers to previous experience, including success and failure; "vicarious experience" addresses observing the performances, successes and failures of others;"social persuasion" includes verbal persuasion from peers, colleagues and relatives; and"physiological and emotional states" from which people judge their strengths, capabilities and vulnerabilities (Bandura, 1986, 1994, 1995).As self-efficacy is based on self-perceptions regarding different behaviours, it is considered to be situation specific. In other words, a person may exhibit high levels of self-efficacy within one domain, while exhibiting low levels within another (Cassidy and Eachus, 2002). Thus, self-efficacy has generated research in various disciplines such as medicine, business, psychology and education (Kear, 2000; Lev, 1997; Schunk, 1985; Koul and Rubba, 1999). Computer self-efficacy is a sub-field of self-efficacy. It is defined as one's perceived ability to accomplish a task with the use of a computer (Compeau and Higgins, 1995). Various studies have noted that training and experience play important roles in computer self-efficacy (Compeau and Higgins, 1995; Kinzie et al. , 1994; Stone and Henry, 2003). Several studies have investigated the effect of computer self-efficacy on computer training performance (Compeau and Higgins, 1995) and on IT use (Easley et al. , 2003).HypothesesBased on the study objectives and assuming that PEOU, personal innovativeness,cognitive appraisal and openness to experience may predict information professionals' behavioural intention to use cloud computing, the underlying assumptions of this study are as follows:H1. High scores in respondent PEOU will be associated with high scores in their behavioural intention to use cloud computing.H2. High scores in respondents' personal innovativeness will be associated with high scores in their behavioural intention to use cloud computing.H3. Low scores in respondents' threat and high scores in respondents' challenge will be associated with high scores in their behavioural intention to use cloud computing. H4. High scores in respondents' self-efficacy will be associated with high scores in their behavioural intention to use cloud computing.H5. High scores in respondents' openness to experience will be associated with high scores in their behavioural intention to use cloud computing.H6. High scores in respondents' computer competence and in social media use will be associated with high scores in their behavioural intention to use cloud computing. MethodologyData collectionThe research was conducted in Israel during the second semester of the 2013 academic year and encompassed two groups of information professionals: librarians and information specialists. The researchers sent a message and a questionnaire to an Israeli library and information science discussion group named "safranym", which included school, public and academic librarians, and to an Israeli information specialist group named "I-fish", which consists of information specialists that work in different organizations. Researchers explained the study's purpose and asked their members to complete the questionnaire. These two discussion groups consist of about 700 members; 140 responses were received, giving a reply percentage of 20 per cent. Data analysisOf the participants, 25 (17.9 per cent) were male and 115 (82.1 per cent) were female. Their average age was 46.3 years.MeasuresThe current study is based on quantitative research. Researchers used seven questionnaires to gather the following data: personal details, computer competence, attitudes towards cloud computing, behavioural intention, openness to experience, cognitive appraisal and self-efficacy.The personal details questionnaire had two statements. The computer competence questionnaire consisted of two statements rated on a 5-point Likert scale (1 = strongest disagreement; 5 = strongest agreement). The cloud computing attitude questionnaire, based on Liuet al. (2010), was modified for this study and consisted of six statements rated on a seven-point Likert scale (1 = strongest disagreement; 7 = strongest agreement). A principal components factor analysis using Varimax rotation with Kaiser Normalization was conducted and explained 82.98 per cent of the variance. Principal components factor analysis revealed two distinct factors. The first related to information professionals' personal innovativeness (items 2, 3 and 5), and the second to information professionals' perceptions about cloud computing ease ofuse (PEOU) (items 1, 4, and 6); the values of Cronbach's Alpha were 0.89 and 0.88, respectively.The behavioural intention questionnaire, based on Liu et al. (2010), was modified for this study and consisted of three statements rated on a six-point Likert scale (1 = strongest disagreement; 6 = strongest agreement). Its Cronbach's Alpha was 0.79. The openness to experience questionnaire was derived from the Big Five questionnaire (John et al. , 1991) and consisted of eight statements rated on a five-point Likert scale (1 = strongest disagreement; 5 = strongest agreement); Cronbach's Alpha was 0.81. The cognitive appraisal questionnaire measured information professionals' feelings of threat versus challenge when confronted with new situations. It consisted of 10 statements rated on a six-point scale (1 = fully disagree; 6 = fully agree). This questionnaire was previously used (Aharony, 2009, 2011; Yekutiel, 1990) and consisted of two factors: threat (items 1, 2, 3, 5, 7 and 8) and challenge (items 4, 6, 9 and 10). Cronbach's Alpha was 0.70 for the threat factor and 0.89 for the challenge factor.The self-efficacy questionnaire was based on Askar and Umay's (2001) questionnaire and consisted of 18 statements rated on a five-point scale (1 = fully disagree; 5 = fully agree); Cronbach's Alpha was 0.96.FindingsTo examine the relationship between openness to experience, cognitive appraisal (threat, challenge and self-efficacy), TAM variables (personal innovativeness and PEOU), and behavioural intention to use cloud computing, researchers performed Pearson correlations, which are given in Table I.Table I presents significant correlations between research variables and the dependent variable (behavioural intention to use cloud computing). All correlations are positive, except the one between threat and behavioural intention to use cloud computing. Hence, the higher these measures, the greater the behavioural intention to use cloud computing. A significant negative correlation was found between threat and the dependent variable. Therefore, the more threatened respondents are, the lower is their behavioural intention to use cloud computing.Regarding the correlations between research variables, significant positive correlations were found between openness to experience and challenge, self-efficacy, personal innovativeness and PEOU. A significant negative correlation was found between openness to experience and threat. That is, the more open to experience respondents are, the more challenged they are, the higher is their self-efficacy, personal innovativeness, and PEOU and the less threatened they are. In addition, significant negative correlations were found between threat and self-efficacy, personal innovativeness and PEOU. We can conclude that the more threatened respondents are, the less they are self-efficient, personally innovative and the less they perceive cloud computing as easy to use. Significant positive correlations were also found between self-efficacy and personal innovativeness and PEOU. Thus, the more self-efficient respondents are, the more personally innovative they are and the more they perceive cloud computing as easy to use.The study also examined two variables associated with computer competence:computer use and social media use. Table II presents correlations between these two variables and the other research variables.Significant, high correlations were found between computer competence variables and openness to experience, self-efficacy, personal innovativeness, PEOU and behavioural intention to use cloud computing. Hence, the higher respondents' computer competence, the more they are open to experience, self-efficient and personally innovative, and perceive cloud computing as easy to use, the higher is their behavioural intention to use cloud computing.Researchers also examined relationships with demographic variables. To examine the relationship between age and other research variables, the researchers performed Pearson correlations. A significant negative correlation was found between age and PEOU, r = -0.21, p < 0.05. We may assume that the younger the respondents are, the more they perceive cloud computing as easy to use. To examine whether there are differences between males and females concerning the research variables, a MANOV A was performed and did not reveal a significant difference between the two groups concerning research variables, F (7,130) = 1.88, p > 0.05.The researchers also conducted a hierarchical regression using behavioural intention to use cloud computing as a dependent variable. The predictors were entered as five steps:respondents' openness to experience;respondents' computer competence (computer use and social media use);cognitive appraisal (threat, challenge and self-efficacy);TAM variables (personal innovativeness and PEOU); andinteractions with the TAM variables.The entrance of the four first steps was forced, while the interactions were done according to their contribution to the explained variance of behavioural intention to use cloud computing. The regression explained 54 per cent of behavioural intention to use cloud computing. Table III presents the standardized and unstandardized coefficients of the hierarchical regression of respondents' behavioural intention to use cloud computing.The first step introduced the openness variable that contributed significantly by adding 13 per cent to the explained variance of behavioural intention to use cloud computing. The beta coefficient of the openness variable is positive; hence, the more open to experience respondents are, the higher is their behavioural intention to use cloud computing. The second step introduced the two computer competence variables (computer use and social media use) which contributed 5 per cent to the explained variance of behavioural intention. Of these two variables, only the social media variable contributed significantly and its beta coefficient was positive. In other words, the more respondents use social media, the higher is their behavioural intention to use cloud computing. Note that Pearson correlations found significant positive correlations between these two variables and behavioural intention to use cloud computing. It seems that because of the correlation between these two variables, r = 0.33, p < 0.001, the computer use variable did not contribute to the regression.As the third step, researchers added respondents' personal appraisal variables (threat and challenge, and self-efficacy), and this also contributed significantly by adding 25 per cent to the explained variance of behavioural intention. The beta coefficients of challenge and of self-efficacy were positive, while that of threat was negative. Therefore, we may conclude that the more respondents perceived themselves as challenged and self-efficient, and the less they perceived themselves as threatened, the higher is their behavioural intention to use cloud computing. The inclusion of this step caused a decrease in the [beta] size of the openness to experience variable that changed it into an insignificant one, and may suggest a possibility of mediation. Sobel tests indicated that self-efficacy mediates between openness to experience and behavioural intention (z = 4.68, p < 0.001). Hence, the more respondents are open to experience, the higher is their self-efficacy and, as a result, the higher is their behavioural intention to use cloud computing.The fourth step added the TAM variables (respondents' PEOU and personal innovation), and this also contributed significantly by adding 9 per cent to the explained variance of behavioural intention to use cloud computing. The beta coefficient of this variable was positive; therefore, the more respondents perceived themselves to be personally innovative and cloud computing as easy to use, the higher is their behavioural intention to use cloud computing. Note that in this step there was a decrease in the [beta] size of self-efficacy. Sobel tests indicated that of the two variables, PEOU mediates between self-efficacy and behavioural intention (z = 4.77, p < 0.001). Thus, the more respondents perceive themselves as self-efficient, the higher they perceive cloud computing's PEOU and, as a result, the higher is their behavioural intention to use it.As the fifth step, researchers added the interaction between computer use X personal innovativeness. This interaction added 2 per cent to the explained variance of behavioural intention to use cloud computing and is presented in Figure 1.Figure 1 shows a correlation between personal innovation and behavioural intention to use cloud computing among respondents who are low and high in computer use. This correlation is higher among respondents who are low in computer use, [beta] = . 40, p < 0.05, than among those who are high in computer use, [beta] = 0.04, p < 0.05. It seems that especially among participants who are low in computer use, the higher their personal innovativeness, the higher is their behavioural intention to use cloud computing.DiscussionThe present research explored the extent to which the TAM and personal characteristics, such as threat and challenge, self-efficacy and openness to experience, explain information professionals' perspectives on cloud computing. Researchers divided the study hypotheses into three categories. The first (consisting of H1 -H2 ) refers to the TAM, the second (H3 -H5 ) to personality characteristics and, finally, H6 to computer competence. All hypotheses were accepted. Regarding the first category of hypotheses, results show that both were accepted. Findings suggest that high scores in PEOU and personal innovativeness are associated with high scores in respondents' intention to adopt cloud computing. These findings can be associated with previous。
云计算现状综述在当今数字化的时代,云计算已经成为了信息技术领域的核心驱动力之一。
它如同一场无声的革命,悄然改变着我们的生活和工作方式。
那么,云计算的现状究竟如何呢?让我们一起来探究一番。
云计算,简单来说,就是将计算任务分布在大量的分布式计算机上,而非本地计算机或远程服务器中,企业数据中心的运行将与互联网更相似。
这使得用户能够按需获取计算能力、存储空间和各种软件服务。
从应用领域来看,云计算几乎已经渗透到了各行各业。
在电子商务领域,各大电商平台依靠云计算实现高效的订单处理、库存管理和用户数据分析,从而能够在购物高峰期应对海量的访问流量,为消费者提供流畅的购物体验。
金融行业利用云计算进行风险评估、交易处理和客户关系管理,大大提高了业务的处理效率和安全性。
医疗行业通过云计算实现医疗数据的存储和共享,方便医生远程诊断和研究病情。
教育领域也借助云计算搭建在线教育平台,让学生能够随时随地获取学习资源。
云计算的服务模式主要包括三种:基础设施即服务(IaaS)、平台即服务(PaaS)和软件即服务(SaaS)。
IaaS 提供了服务器、存储和网络等基础设施资源,用户可以根据自己的需求灵活配置和管理这些资源。
这就好比为用户提供了一个“毛坯房”,用户可以按照自己的想法进行装修和布置。
PaaS 则在基础设施之上提供了平台服务,包括操作系统、数据库和中间件等。
它类似于为用户提供了一个“精装修的房子”,用户只需要专注于自己的应用开发,而无需操心底层的基础设施搭建。
SaaS 则直接为用户提供了各种应用软件,如电子邮件、办公软件和客户关系管理系统等。
用户只需按需使用,无需进行安装和维护,就像直接入住“酒店式公寓”一样方便。
目前,全球云计算市场呈现出快速增长的态势。
据相关数据显示,云计算市场规模逐年扩大,预计未来几年仍将保持较高的增长率。
亚马逊的 AWS、微软的 Azure 和谷歌的 Cloud Platform 是全球云计算市场的主要参与者,它们凭借强大的技术实力和广泛的服务体系占据了较大的市场份额。
云计算技术综述随着现代科技的发展,云计算技术开始成为越来越多企业的重要工具。
云计算技术是指通过网络的方式,将计算资源以服务的形式提供给用户。
它可以帮助企业省去昂贵的硬件设备和软件开发成本,提高数据安全性,并改善企业的效率。
本文将对云计算技术进行一些综述,包括技术特点、应用领域、风险和前景。
一、技术特点云计算技术的特点主要包括以下几个方面:1. 虚拟化技术。
云计算平台使用虚拟化技术,将物理服务器分割成多个虚拟机。
这使得服务器利用率更高,可以更加灵活地分配计算资源。
2. 弹性扩容。
云计算平台可以根据不同的需求,快速增加或减少计算资源。
这使得企业可以随时增加设备,并在不需要时减少设备。
3. 自助服务。
云计算平台允许用户通过自助服务界面选择、配置并使用计算资源和服务。
这使得用户可以更加便捷地使用云计算服务,并自主控制资源的使用。
4. 分布式架构。
云计算平台采用分布式架构,使得用户可以从全球各地访问相同的服务,从而提高服务的效率和响应速度。
二、应用领域云计算技术已被广泛应用于许多行业和领域,其中一些重要的领域包括:1. 企业信息化管理。
云计算可以帮助企业将数据和信息集中管理,从而提高企业的效率和响应速度,降低企业运营成本。
2. 科学研究。
云计算可以提供高性能计算、大数据存储和处理等服务,帮助科学家进行更深入的研究。
3. 电子商务。
云计算可以提供安全、高效和可扩展的电子商务解决方案,从而促进电子商务行业的发展。
4. 媒体和广告。
云计算可以提供高质量的媒体存储和处理服务,使得媒体和广告行业可以更好地管理和分发媒体内容。
三、风险虽然云计算技术带来了许多好处,但它也存在一些风险:1. 安全性问题。
由于云计算技术的本质,数据通常存储在第三方的服务器上,企业可能无法完全掌控数据的安全性。
2. 可用性问题。
如果云计算提供商在处理服务方面存在问题或网络连接中断等情况,会影响到企业的正常运营。
3. 隐私问题。
云计算技术可能会产生隐私问题,尤其是对于某些敏感的商业和政治信息。
《云计算研究现状综述》篇一一、引言云计算是近年来信息技术领域中迅速崛起的一项技术,以其强大的计算能力、灵活的扩展性以及高效率的资源利用,正逐渐改变着传统信息技术的运行模式。
本文旨在全面梳理云计算的研究现状,分析其发展历程、主要研究成果、应用领域及未来发展趋势,为相关研究者和从业者提供参考。
二、云计算的发展历程云计算的发展始于上世纪90年代,随着网络技术的不断进步,云计算的概念和技术架构逐渐形成。
经过多年的发展,云计算技术逐渐成熟,并在全球范围内得到广泛应用。
三、云计算的主要研究成果1. 云服务模式研究:研究云服务的不同模式,如基础设施即服务(IaaS)、平台即服务(PaaS)和软件即服务(SaaS),以及不同模式下的服务特点、适用场景和优化策略。
2. 云计算资源管理:研究云计算资源的管理和调度技术,包括虚拟化技术、资源分配策略、负载均衡等,以提高云计算资源的利用率和性能。
3. 云计算安全技术:研究云计算环境下的安全技术,如数据加密、访问控制、身份认证等,保障云计算环境的安全性。
4. 云计算平台架构:研究云计算平台的架构设计,包括云操作系统、云存储、云网络等关键技术,以实现高效、可靠、安全的云计算服务。
四、云计算的应用领域云计算技术已广泛应用于各个领域,包括但不限于:1. 电子商务:利用云计算的强大计算能力和扩展性,实现电商平台的快速部署和灵活扩展。
2. 大数据分析:利用云计算平台的高性能计算和大数据存储能力,实现大规模数据的分析和挖掘。
3. 人工智能:利用云计算资源为人工智能提供强大的计算支持,推动人工智能技术的发展。
4. 医疗健康:利用云计算技术实现医疗数据的共享和协同处理,提高医疗服务的质量和效率。
5. 政府和企业信息化:利用云计算实现政府和企业内部的信息资源共享和协同工作,提高工作效率和管理水平。
五、云计算的未来发展趋势1. 技术创新:随着技术的不断发展,云计算将进一步实现自主化、智能化和虚拟化,提高计算效率和资源利用率。
关于云计算的综述报告在当今数字化的时代,云计算已经成为了信息技术领域的一项关键技术,对企业和个人的生活产生了深远的影响。
云计算不再是一个陌生的概念,它已经融入到了我们日常生活和工作的方方面面。
云计算简单来说,就是一种基于互联网的计算方式,通过这种方式,共享的软件资源、硬件资源和信息可以按需提供给计算机和其他设备。
想象一下,您不再需要在自己的电脑上安装大量的软件和存储海量的数据,只需要通过网络连接到云端,就能够随时随地获取所需的服务和资源,这就是云计算带来的便利。
云计算的类型多种多样。
首先是基础设施即服务(IaaS),它提供了服务器、存储和网络等基础设施资源,用户可以根据自己的需求灵活地配置和管理这些资源。
例如,企业可以在云端快速部署服务器,而无需自己购买和维护硬件设备。
其次是平台即服务(PaaS),它为用户提供了一个平台,用于开发、运行和管理应用程序,省去了搭建和维护底层基础设施的繁琐工作。
最后是软件即服务(SaaS),这是我们最为常见的一种类型,比如在线办公软件、电子邮件服务和客户关系管理系统等,用户只需通过网络访问即可使用,无需进行安装和维护。
云计算具有诸多显著的优势。
首先是成本效益。
对于企业来说,不再需要投入大量资金购买硬件设备和软件许可证,也无需花费大量时间和人力进行系统维护和升级,大大降低了运营成本。
其次是灵活性和可扩展性。
企业可以根据业务需求的变化,快速地调整云计算资源的使用量,轻松应对业务的增长或收缩。
再者,云计算提供了高可靠性和可用性。
云服务提供商通常拥有强大的数据中心和备份机制,能够确保服务的持续稳定运行,减少了因硬件故障或自然灾害等导致的业务中断风险。
此外,云计算还促进了协作和移动办公。
团队成员可以在任何有网络的地方访问和共享相同的资源,提高了工作效率和协同效果。
然而,云计算也并非毫无挑战。
数据安全和隐私保护是用户最为关注的问题之一。
由于数据存储在云端,存在数据泄露、被非法访问或篡改的风险。
计算机科学与技术国内外研究综述范文全文共四篇示例,供读者参考第一篇示例:从20世纪中叶开始,计算机科学与技术在世界范围内快速发展,成为当今国际社会最重要的技术领域之一。
国内外学者们对计算机科学与技术的研究也日益深入,不断推动着这一领域的发展。
本文将综述国内外关于计算机科学与技术的研究进展,以期为读者提供一个全面的了解。
一、人工智能二、物联网技术物联网技术是计算机科学与技术领域的另一个重要研究方向。
国内外学者们在物联网技术领域的研究中,提出了各种创新的理论和方法,推动着物联网技术的发展。
国外的物联网技术主要应用于智能家居、智能交通、智能医疗等领域,融合了传感技术、通信技术、云计算技术等多方面的技术。
国内的物联网技术发展也日益活跃,各种创新应用不断涌现,为我国的工业生产、城市管理等方面带来了巨大改变。
三、大数据技术大数据技术是计算机科学与技术领域的另一个研究热点。
大数据技术的发展为人们提供了更多的数据处理和分析方法,为决策者提供了更准确的数据支持。
国外的大数据技术主要应用于金融、医疗、电商等领域,发挥着重要的作用。
在国内,大数据技术也获得了快速发展,各种大数据平台和工具不断涌现,为我国的经济发展、公共管理等方面提供了强大支持。
计算机科学与技术是一个充满活力的领域,国内外学者们在这一领域的研究中取得了众多重要成果。
希望未来国内外的研究者们能够继续积极探索,共同推动计算机科学与技术领域的发展。
【字数满足要求,结束撰写】。
第二篇示例:计算机科学与技术是一门涉及计算机软硬件系统的学科,随着信息技术的发展和普及,计算机科学与技术在各个领域都有着广泛的应用和影响。
本文将就计算机科学与技术领域的国内外研究现状进行综述,探讨其发展趋势和未来发展方向。
一、国内外研究现状概述在过去几十年中,计算机科学与技术领域取得了巨大的发展,国内外各大高校和科研机构在该领域开展了大量的研究工作,取得了许多重要成果。
在人工智能领域,美国的斯坦福大学、麻省理工学院等世界一流院校一直处于领先地位,他们在深度学习、自然语言处理、计算机视觉等方面取得了突破性进展。
引言概述随着互联网技术的发展,云计算成为了当今社会信息化建设的重要组成部分。
本文将继续对云计算的发展和应用进行综述。
通过对现有文献的调研分析,揭示云计算在各个领域的应用和发展趋势,为读者提供全面且专业的了解。
正文内容1.云计算在企业信息化建设中的应用1.1虚拟化技术及其在云计算中的应用1.2云计算在企业资源管理中的应用1.3云计算在企业数据分析中的应用1.4云计算在企业安全保障中的应用1.5云计算在企业协同办公中的应用2.云计算在教育领域中的应用2.1云计算在教育信息化中的应用2.2云计算在教育资源共享中的应用2.3云计算在教育管理中的应用2.4云计算在在线教育中的应用2.5云计算在教学评估中的应用3.云计算在医疗领域中的应用3.1云计算在医疗信息化中的应用3.2云计算在医疗数据管理中的应用3.3云计算在远程医疗中的应用3.4云计算在智慧医疗中的应用3.5云计算在医疗影像处理中的应用4.云计算在金融领域中的应用4.1云计算在金融信息化中的应用4.2云计算在金融风险管理中的应用4.3云计算在金融交易处理中的应用4.4云计算在金融数据分析中的应用4.5云计算在金融安全保障中的应用5.云计算在政府信息化中的应用5.1云计算在政府统计分析中的应用5.2云计算在电子政务中的应用5.3云计算在政府数据共享中的应用5.4云计算在政府服务提供中的应用5.5云计算在政府智慧城市建设中的应用总结通过对云计算在企业信息化、教育、医疗、金融和政府信息化领域中的应用进行综述,我们可以看到云计算在各个领域中的应用前景巨大。
虚拟化技术、资源管理、数据分析、安全保障、协同办公等方面的应用为企业提供了高效、灵活、安全的信息化解决方案。
在教育领域中,云计算提供了丰富的教育资源和在线教学平台,改变了传统教育的方式和方式。
在医疗和金融领域,云计算的应用为大规模数据处理和安全保障提供了有效的解决方案。
在政府信息化领域,云计算为政府数据共享、智慧城市建设等提供了有力支撑。
第12卷第5期2010年10月北京邮电大学学报(社会科学版)Journal o f Be iji ng U n i versity o f P osts and T eleco mm un i ca tions (Soc i a l Sc i ences Ed ition)V ol 112,N o 15O ct 12010收稿日期:2010-07-15作者简介:董晓霞(1972)),女,河北博野人,北京邮电大学图书馆高级工程师,博士研究生,研究方向为图书馆联盟、数字图书馆、管理工程。
云计算研究综述及未来发展董晓霞1,2,吕廷杰2(11北京邮电大学图书馆,北京 100876;21北京邮电大学经济管理学院,北京 100876)摘 要:作为一种新型的计算范式,云计算已经成为近两年研究的热点,其目标是为用户动态地提供可靠的、可定制的、服务质量(Q oS)保证的IT 计算环境服务。
研究综述从定义、服务层次、计费方式及未来发展等方面对云计算进行了分析,旨在为科学地评估云计算的运营和使用提供一定的参考。
关键词:云计算;效用计算;规模经济;服务层次;计费方式中图分类号:T P39314 文献标识码:A 文章编号:1008-7729(2010)05-0076-06早在50年前,John M cCart h y 就提出了/或许有一天计算可以成为公共服务0的设想[1]。
计算技术和网络技术的发展,尤其是近两年出现的云计算的技术和理念,正逐步将John M c C arthy 的设想演变为现实。
作为按需付费的一种新型的商业模式,云计算将基础设施、平台以及软件作为服务通过I nter net 提供给用户;用户使用云计算服务时,不必配置昂贵的基础设施和复杂的软件系统,也不需要关心数据存储的位置。
尽管目前学术界以及工业界普遍认为云计算具有变革互联网服务的潜在能力,但是工商界对于云计算的接受程度还远在人们的预期之外。
例如,将传统的I T 管理模式过渡到基于云计算的管理模式,对于一个企业来说依然是一个很大的挑战。
论云计算的现状与发展趋势文献综述摘要:正如1949年约翰·冯诺依曼曾经说过的:“我们用计算机技术所取得成就似乎已经达到了极限;不过,人们下这样的断语时应该小心,因为这种话往往在五年之后就会显得相当愚蠢。
”我们今天的信息革命只走到了前半程,也就是信息的积累、创造的手段和技术的储备,伴随着云计算的诞生,已经走到了大规模知识管理、分享、应用和再创造的时候了。
关键词:云计算应用前景分析导言:整整走过了一个世纪,今天信息技术(Information Technology, IT)不仅不是垂垂老矣,相反的,IT真正革命性的序幕才刚刚拉开,而前行的方向就是以云计算为代表的知识技术(Knowledge Technology,KT)。
云计算意味着什么?机遇?挑战?我们应该欣喜?抑或是悲哀?作为新时代的我们,在这个知识更迭飞速的时代,更应该对它的前世今生,及未来的动向有一个理性的认识。
文献综述一、云计算概念目前为止还没有一个统一的概念,南京市金陵中学河西分校的刘维明在云计算ABC中指出大多数学者及专家认为可定义为两种:A、狭义云计算——指IT 基础设施的交付和使用模式,指通过网络以按需、易扩展的方式获得所需资源B、广义云计算——指服务的交付和使用模式,指通过网络以按需、易扩展的方式获得所需服务。
这种服可以是IT 和软件、互联网相关,也可是其它服务”二、云计算简史1.1983年,太阳电脑提出“网络是电脑”。
2.2006年3月,亚马逊推出弹性计算云服务。
3.2006年8月9日,Google首席执行官埃里克·施密特在搜索引擎大会首次提出“云计算”概念。
4.2007年10月,Google与IBM开始在美国大学校园推广云计算的计划。
5.2008年1月30日,Google宣布在台湾启动“云计算学术计划”6.2008年7月29日,雅虎、惠普、和英特尔宣布一项涵盖美国、德国和新加坡的联合计划,推出云计算研究测试床,推进云计算。
云计算综述及云计算在通信行业的应用分析在当今数字化的时代,云计算已经成为了一项至关重要的技术,它正在深刻地改变着各个行业的运作方式和发展模式,通信行业便是其中之一。
云计算,简单来说,就是将计算任务分布在大量计算机构成的资源池上,使各种应用系统能够根据需要获取计算力、存储空间和各种软件服务。
它就像一个巨大的虚拟资源库,用户可以按需取用,而无需关心资源的具体位置和配置。
云计算具有几个显著的特点。
首先是超大规模。
云计算平台通常拥有成千上万台服务器,能够提供强大的计算能力。
其次是虚拟化。
用户可以在云平台上获得虚拟的服务器、存储和网络等资源,感觉就像是在使用独立的实体设备一样。
再者是高可靠性。
云计算采用了数据多副本容错、计算节点同构可互换等措施来保障服务的高可靠性。
此外,通用性和高可扩展性也是其重要特点,云计算不针对特定的应用,能够同时支撑不同的应用运行,并且可以根据用户的需求轻松地进行扩展和收缩。
云计算的服务模式主要有三种:基础设施即服务(IaaS)、平台即服务(PaaS)和软件即服务(SaaS)。
IaaS 提供给用户的是服务器、存储和网络等基础设施服务,用户可以在上面自由地部署和运行操作系统和应用程序。
PaaS 则为用户提供了一个平台,包括操作系统、数据库、中间件等,让用户能够更专注于开发和部署自己的应用。
SaaS直接为用户提供了可以使用的软件应用,用户无需自己安装和维护软件,只需通过网络访问即可使用。
云计算的部署模式也分为几种。
公有云是由云服务提供商提供给公众使用的云服务,任何人都可以按需购买和使用。
私有云则是为一个特定的组织或企业构建的专用云环境,具有更高的安全性和定制性。
混合云则是将公有云和私有云结合起来使用,既能利用公有云的灵活性和成本优势,又能保证私有云的安全性和可控性。
社区云则是由几个具有共同利益的组织或社区共同构建和使用的云服务。
在通信行业中,云计算的应用带来了诸多变革。
首先,云计算为通信运营商提供了强大的计算和存储能力。