Introduction - Cloud Data Management - page 3

mechanisms. Jim Gray, a database software pioneer and a Microsoft researcher,
called the shift a “ fourth paradigm ”[ 151 ]. The first three paradigms were experi-
mental , theoretical and, more recently, computational science . Gray argued that the
only way to cope with this paradigm is to develop a new generation of computing
tools to manage, visualize and analyze the data flood. In general, the current
computer architectures are increasingly imbalanced where the latency gap between
multi-core CPUs and mechanical hard disks is growing every year which makes the
challenges of data-intensive computing harder to overcome [ 76 ].
Recently, there has been a great deal of hype about cloud computing. Cloud
computing is associated with a new paradigm for the provision of computing
infrastructure. This paradigm shifts the location of this infrastructure to the network
to reduce the costs associated with the management of hardware and software
resources. Hence, businesses and users become able to access application services
from anywhere in the world on demand. Therefore, it represents the long-held dream
of envisioning computing as a utility [ 68 ] where the economy of scale principles
help to drive the cost of computing infrastructure effectively down. Big players such
as Amazon, Google, IBM, Microsoft and Sun Microsystems have established new
data centers for hosting Cloud computing applications in various locations around
the world to provide redundancy and ensure reliability in case of site failures.
In principle, one of the main reasons for the success of cloud computing is the
role it has played in eliminating the size of an enterprise as a critical factor in
its economic success. An excellent example of this change is the notion of data
centers which provide clients with the physical infrastructure needed to host their
computer systems, including redundant power supplies, high bandwidth commu-
nication capabilities, environment monitoring, and security services. In practice,
on-premise data centers are often under-utilized due to over-provisioning, as well as
the time-varying resource demands of typical enterprise applications. Multi-tenancy
is an optimization mechanism for hosted services in which multiple customers are
consolidated onto the same operational system (a single instance of the software
runs on a server, serving multiple clients) and thus the economy of scale principles
help to effectively drive down the cost of computing infrastructure. In particular,
multi-tenancy allows pooling of resources which improves utilization by eliminating
the need to provision each tenant for their maximum load. This makes multi-tenancy
an attractive mechanism for both: Cloud providers (who are able to serve more
customers with a smaller set of machines) and Customers of cloud services (who
do not need to pay the price of renting the full capacity of a server). Therefore,
Public data centers have helped to eliminate the need for small companies to make
a large capital expenditure in building an infrastructure to create a global customer
base [ 62 ]. The data center model has been effective since it allows an enterprise
of any size to manage growth with the popularity of its product or service while at
the same time also allows the enterprise to cut its losses if the launched product or
service does not succeed.
In general, the concept of renting computing power goes back decades to the days
when companies would share space on a single mainframe with big spinning tape
drives and it has been envisioned that computing facilities will be provided to the