Thèse de doctorat: Algorithmes de classification répartis sur le cloud

tel-00744768, version 1 - 23 Oct 2012
26 CHAPTER 2. PRESENTATION OF CLOUD COMPUTING
given ratio. Other techniques of automation can be found in [72] or [79].
A key factor in cloud performance bandwidth (whether intra or inter data centers
bandwidth) is the spatial disposition of the hardware in the data center, as well
as the network topology between the different nodes dedicated to data storage
and computing. While a lot of research has been made on this subject, major
cloud companies have not been disclosing much about this major technological
challenge and their own implementation. According to [59], Microsoft plans to
upgrade some of its data centers following the networking architecture studied in
[18].
Software technologies
Several software technology stacks have been developed to make the access to
CPU and storage easier. They split into three abstraction level : the storage level,
the execution level, and the DSL (domain-specific language) level.
– The storage level is responsible for preserving the data into the physical storage.
It handles all the issues of distributed storage management, of data contention
and provides the data with a structured access. It can be SQL or No-SQL
storage, as described in Section 2.4. This storage can also be used as a means
of communication between machines. Other types of storage are available
in IaaS solutions such as Amazon Elastic Block Store that provides storage
volumes that can be attached as a device to a running Amazon EC2 instance
and that persist independently from the life of this instance.
– The execution level defines the general execution framework. It specifies how
the machines are supposed to organize themselves, it monitors the workers and
restarts the failing machines. Depending on the type of Cloud Computing offers
(IaaS, PaaS, etc.), the execution level can provide each computing device with
anything a standard OS could achieve, or it can give a much more constrainted
execution framework where the execution flow must be designed in a specific
way (the most famous example of such a constrained execution framework is
MapReduce, described in Subsection 2.5.1).
– The DSL level is a higher level execution framework than the execution level.
It often provides a declarative language instead of the procedural approach
provided by the execution level, therefore saving the users from specifying how
the work is supposed to be parallelized. It provides automated and under the
hood parallelization, scheduling and inter-machines communications. Therefore,
the DSL level helps users focus only on defining the result they want,