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Communications (CaaS) and more recently (Lenk
et al. 2009), Humans (HuaaS) and Personalization
(Guo et al. 2009). The last service, Personalization
is very important in the context of mobile users.
A classification of the technologies behind the
Everything as a Service (XaaS) paradigm helps
understand the cloud better. It is interesting to
explore the Cloud ecosystem and get insights into
the services that Cloud offers, understanding the
myriad technical terms used in the cloud parlance.
The literature cited at the end of this chapter has
abundant discussion on the tools and example of
the services offered.
Cloud computing works best assuming that
there are no significant constraints on the band-
width. However, bandwidth is expensive and could
be constrained, particularly since the distances
could be huge. Therefore, ideally, there may be
a need for writing applications that can adopt to
bandwidth and other constraints as applicable
in that context. Cloud computing often crosses
country boundaries, calling for a need to evaluate
and adapt to legal frameworks. Trust and privacy
become extremely important in such contexts.
In this chapter, we talk about these and other
difficulties that Cloud Computing brings with it,
explaining some of the challenges and discussing
any opportunities that they could be translated into.
The changes happening in the web world are
also helping the paradigm shift to Cloud Comput-
ing. To the user, the original web was read-only.
Web 2.0 made it read-write: WWW became World
Wide Wall, where anyone could write. Web 3.0
attempts to make it executable as well, making
it the ubiquitous computer. Now that this ubiqui-
tous computer is fully functional, what would be
the next avatar of the web? How does the cloud
landscape change with developments on the web
front? This chapter answers these questions by
pointing to future directions for research in this
area. The authors predict that the ubiquitous com-
puter will take the same route as the Von Neumann
machine and improve drastically in performance
and scalability, driven by certain key aspects such
as mobility and intelligence.
There is already a discussion on forming
virtual cloudlets (Satyanarayanan et al. 2009) to
address the issue of response times when using
expensive applications on the mobile devices
such as augmented reality. This chapter covers
these exploratory ideas and present the authors'
perspective on them.
BACKGROUND
We have been already using cloud computing
whenever we use free e-mail or for that matter
do a search on the Internet. Thanks to the levels
of transparency that cloud computing provides,
the user is unaware of the thousands of clusters
working behind the scene for her when an Inter-
net search is done. The same idea of thousands
of clusters doing the job transparently is now
borrowed into cloud computing. Solving tough
problems that involve large data and massive
computation has traditionally been a forte of major
business houses, such as Google. In fact, most of
the Cloud Computing techniques evolved from
the technologies used by Google (Chang 2010)
and others in this area. This is no longer true with
the advent of Cloud Computing. Even startups
can enter the fray with minimal investment. The
traditional datacenter with thousands of machine
clusters typical of the environment in these big
companies has transformed into the cloud, open
to wider access and use.
In a sense, Cloud Computing takes us back to
the days when users “rented” computing time on
Mainframes to get their jobs processed. Though
there is a distinction between “renting” comput-
ing time and “utility computing” that the Cloud
represents (Michael et al. 2009), for convenience,
we use the term “rent” to mean either. Computing
as a utility is not really new. What makes Cloud
Computing really interesting now is the all-
pervasive Internet and the networking bandwidth
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