The Future of Cloud Computing
Introduction
Cloud Computing
Cloud computing applies to the development of parallel computing, distributed computing, and grid computing (Rad, et al., 2009). Cloud computing refers both to a platform and a type of application (Buyya, Yeo, Venugoplas, Broberg, & Brandic 2009). Cloud computing platforms provide the services necessary for developers to create new SaaS applications; it is a dynamic process that provisions, configures, reconfigures, and deprovisions servers. Cloud platforms provide a pool of resources to host different applications where computing power is delivered on demand (Van, Tran, & Menaud, 2009). Cloud applications use large databases and powerful servers that host Internet-based applications and services. Thus, cloud platforms are for developers, and cloud applications are for users. The two concepts are intimately interrelated and there are several factors to consider when analysing their interconnectedness: infrastructure, platform, storage, applications, and core. Figure 1 illustrates some of these possible interconnections.
Figure 1. Cloud application interconnections
Applications
A logical first step in the understanding of cloud computing is to begin by looking at the cloud services at the user end, starting with software as a service application (SaaS). First, we have SaaS application services like Salesforce.com’s CRM application that allow users to integrate on-premises applications, or packaged software, with cloud applications (Hallestad, 2005). The vast storage capacity and infrastructure of cloud platforms have lured organizations into using cloud platforms to develop their own SaaS applications. In addition, the current trend in SaaS is to move away from traditional licensing of software into software subscriptions, further promoting a move to the cloud.
One of the most widely used cloud services other than the SaaS applications are the search engines; including universal application search engines like Google, Bing, and LiveSearch, and specialized search engine applications like Nexis/Lexis, and PubMed. Not only does one access the search engines via server that connects through the cloud, but the search engines themselves also provide cloud application services or interconnect through cloud platforms (Rad, et al., 2009). For example, PubMed allows the user to search for information within their own databanks while providing links to other proprietary databases, ranging from access to the vast genetic databanks, to the websites or private email accounts of the authors in the PubMed databank. In other words, search engines are more like applications than infrastructure services. Further blurring the line between application services and infrastructure services is the fact that mega service providers like Google and Microsoft tend to bundle cloud application services under one umbrella. Cloud storage is clearly an infrastructure service and cloud search is clearly an application service, but services such as Microsoft’s Alert service might be seen as a hybrid of the two (Buyya, et al., 2009).
One of the most powerful services is storage. Limitations in storage capacity have until now defined the boundaries of research. Large-scale experiments often need a vast amount of computing and storage capacity. In the past, these needs were met by using high-performance super computers that are expensive, and which require professional maintenance and training. Now, cloud computing can offer these services at a fraction of the cost and with real-time online support, and are offered through service level agreements (SLA) that contract quality of service (QoS). Vecciola, Pandely, and Buyya (2009) evaluated the services of Aneka, one of these providers, which uses private and public clouds to deliver the computing power necessary to run the desired programs. The authors conducted a survey to evaluate the effectiveness of Aneka in the classification of genetic data and in fMRI imaging, and found that Aneka could deliver cost-effective on-demand high quality services that allowed for wider use of computing applications in the experimental arena. In a similar study, Langmead, Hansen, and Leek (2010) used Myrna, another specialized cloud computing pipeline, to conduct RNA-sequencing differential expression analyses. The authors analysed a large publicly available RNA-Seq dataset with over 1 billion reads, and found that the application services provided by Myrna were ultra-fast and memory efficient. Like Aneka, Myrna uses the cloud to run multiple computers and processors using Amazaon Elastic MapReducs on either a Hadoop cluster, or circumventing Hadoop altogether. One issue to consider is that privacy concerns might curtail the use of this service.
A wide range of applications have been targeted for the private sector, but no cloud application has grown as fast not has a wider use than do the social network applications. There are many such social networks but by far the largest is Facebook. One can find all sorts of Facebook statistics online, mostly from unfiltered sources, and they all say one thing: that Facebook is used by over 500 million people around the world; that is, 1 out of 13 on the planet are registered users, and half of them log in every day. Gjoka, Sirivianos , Markopoulou , and Yang (2008) conducted a more formal assessment of Facebook and suggest that Facebook’s application platform is behind the unprecedented success of this network, which allows for third-party social networking applications. The authors gathered Facebook application usage data over six months and found that the distribution of the popularity of Facebook applications is rather skewed, with 18-24 year old users representing the core segment at over 60%. They also found that as the number of Facebook applications increase, their average use decreased, and the more applications a user has installed, the more likely the user is to install more applications.
Park, Kee, and Valenzuela (2009) conduced a survey of 1,715 college to determine the attraction of one of these applications—Facebook Groups—and found that the primary reason for joining such groups were a need to socialize, be entertained, improve the standing of their status, and acquire information. The level of participation in these groups correlated with gender, hometown, and year in school. In addition, students with political and civic interests were more likely to join Facebook Groups for informational rather than recreational uses. In a similar study, Zhang, Tang, and Leung (2011) explored the impact of an individual’s psychological traits on their use of Facebook and discovered that self-esteem, the ability to express emotional online, and concerns about communication were strongly associated with degree of networking in Facebook. However, there have also been concerns regarding the safety of Facebook. In addition to potential risks with social predators and cyber bullying, there is the real risk of Internet addiction. Kittinger, Correia, and Irons (2012) assessed the level of Internet addiction in a group of 281 college undergraduate students. The students completed a set of online questionnaires as well as the Internet Addiction Test and found that a significant number of students reported problems and symptoms related to Internet addiction.
The influence of Facebook goes far beyond campus life and keeps spreading across all areas of social life. Marzouki et al. (2012) analysed the impact of Facebook on the success of the Tunisian revolution. The authors describe the perception of Tunisian Internet users that see Facebook as a catalyst for their revolution. The study began five days after the fall of the regime via an online survey of 333 participants who rated the impact of Facebook on the revolution and provided reasons for their evaluation. The results showed that Facebook had three salient functions: political, informational, and as a media platform, all three of which interacted to connect Tunisian Internet users under a common goal.
There are countless other applications and as new devices are being developed new applications soon follow. Table 1 is a representative sample of some of these other applications.
In the research and development sector, cloud computing infrastructure promotes the development and adoption of innovations. It provides the resources necessary for developers to test and share their innovations and thus frees innovators from having to search for the means and the resources to conduct their research and development. Cloud computing also fosters innovation by providing flexibility and adaptability. It is also cheap. In the business sector, cloud computing infrastructure provides for more efficient use of information technology hardware and software investments. Cloud computing also increases profits by allowing for more efficient use of computing resources as well as for more efficient use of human resources by promoting cooperative and collaborative teamwork.
The next step is to evaluate the various platforms used to develop, deliver, and maintain these applications.
Table 1. Cloud services and applications
Cloud Service
Service Provider
Application
Webmail
Gmail, Yahoo, Hotmail
Private communication
Social networking
Facebook, MySpace
Social communication
Professional networking
LinkedIn,
Professional communication
Document applications
Google Docs,
Document archiving and sharing
Blogging
Wordpress, Blogger
Public broadcast by individuals
Microblogging
Twitter
Public broadcast by individuals
Business sites
eBay, Amazon, Craigslist
Consumer advantage
Video-sharing
YouTube, Vimeo, GoAnimate
Public sharing of private work
Picture-sharing
Flickr
Private sharing of images
Desktop publishing
PhotoShop, SumoPaint
Publishing, drawing
Search
Professional databanks
Pubmed, MedScape, Nexis, Lexis
Access to professional information, professional development
Search
NPO/Government databanks
CDC, WHO
Public welfare
Search
Education
Molecular Workbench, BrainPop, Nobelprize
Self-guided learning Home-schooling Professional Development
Consumer services
Search
Yelp, TripAdvisor
Consumer advantage
Search
Universal information
Wikipedia, WolframAlpha
Dissemination of knowledge
Storage
Google, Microsoft, banks
Private storage of data
Mega-storage and data streaming
Aneka, Myrna, Human Genome Project
Mega data analyses Public storage of mega data
Remote employment
CareerBuilder
Home-based work
References
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