New Statistical Algorithms for the Analysis of Mass - FU Berlin, FB MI ...

146 CHAPTER 5. COMPUTER SCIENCE GRID STRATEGIES
3. The workflow execution service stores the state of all current variables
and the new active node to the database. This allows for resuming from
this point after a system crash.
4. The workflow execution service sets the returned node to active and
starts over with step (1).
Experiments have shown that the workflow execution service is idle most of the
time during execution. Therefore, we have implemented this service as a multithreaded
service: The main thread handles all database requests including
scanning the database for new workflows to execute. If a new request is found
and the overall system load is not too high a child-thread is created that
handles this workflow. The main advantage of this approach is that we save
connections to the database, since only the main thread needs to have an active
database connection. This is beneficial since each open connection slows down
the database server (see e.g. (Huddleston et al., 2006)).
5.7 Related Work
As mentioned in the previous sections, most systems that are used for building
distributed computing systems or computational grids have evolved to quite
complex software frameworks. In Table 5.7.1 we list some exemplary Grid
projects that are currently (2007/2008) active and have been studied by us 21 .
There are roughly three categories these projects fall into:
1. e-Infrastructure: This refers to a research environment in which a researcher
has shared access to scientific facilities (such as data, computing
or sensors), regardless of their type and location in the world.
2. Middleware: A middleware connects software applications enabling exchange
of data. Thus, it organizes and integrates the resources in a Grid.
One of its main purpose is to automate the required machine to machine
negotiations, such as negotiating the exchange of resources on behalf of
Grid users and resource providers. It also provides the core foundation
(basic services) for grid applications including areas such as: security,
resource management, information services and data management.
3. Application: These are projects within the context of specific scientific
fields that are devoted to explore and harness grid technology. Depending
on its state (fully operational vs. experimental) these projects are
called application or testbed.
Since there exists neither the exemplary Grid system nor a standard for
Grid systems (although systems like Globus seem to become the de-facto standard)
we will not describe any system in great detail nor give a detailed comparison
to our system 22 . Rather, we use the table to illustrates two things:
(a) there is a need for distributed computing systems in many application
areas and (b) there is a large variety of systems with different scales, aims, approaches
and technological foundations. However, as far as our analyses have
shown none of them manages to provide a powerful and at the same time easy
21 Another even more exhaustive list can be found here (GridInfoware, 2008)).
22 For a detailed comparison of four large Grid systems see e.g. (Asadzadeh et al., 2006)
and references therein.