Developing Complex Systems of Systems Using Cloud and
Evaluating their Architectures Using Simulation and Benchmarking
With funding from the NSF NCSS
I/UCRC and Google App Engine Research Award, the SilverLining team of researchers led by Professor Lawrence Chung and several student and industrial
researchers are helping understand why complex systems of systems need to
be built and evaluate their architectures using simulation and
benchmarking. This research team
includes senior as well as female U.S. citizens as participants and is motivated
by the increasing cost of initial purchase, re-purchase, and operation of
computing equipment that has become unsustainable and, hence, is becoming
an increasingly great burden on the US economy. This research investigates
how to build, evaluate and select computing resources in a fast and
inexpensive way, with a special emphasis on Cloud Computing as a
sustainable and economic computing paradigm.
The
research objective includes determining if it is possible to predict:
-
whether an operational system can migrate
to a cloud, while making everyone happy;
-
the performance
and scalability of the system after or even before it is actually built.
The outcome of the research provides a step towards answering this question.
The research team is investigating “how to make everyone happy” by using a
goal-oriented approach, and how to confirm and reconfirm whether the
architecture of a complex system of systems will live up to everyone’s
expectations in a fair manner by using simulations.
Technically speaking, the team captures the stakeholders’ goals,
including cost, performance and scalability (how well the system will
respond with increasing workloads), together with workflows and reflects them in a good topology of a system of
systems. A system can be a subway monitoring system or a ticketing system,
out of which a more complex system, such as a transportation system, can be
built. Even this transportation system can in turn become a part of yet
another bigger system, such as a system of public facility systems.
The
methodology being deployed in this project is reflected in the following
diagram, which uses the world’s largest public transportation system.
The
space of architectural design for such a system of systems is usually huge,
hence making it practically infeasible to try out each and every possible
design. This research instead explores better architectural alternatives
using simulations – better with respect to the stakeholders’ goals which
often tend to conflict with each other. It would be a daunting challenge to
understand, develop, and successfully operate a complex system of systems,
and this goal-oriented, simulation-based approach provides a fast way with
little financial and manpower resources to tackle the challenge.
Benchmarking
is the process of comparing the metrics of one
system to the metrics of another system, oftentimes industry bests or best
practices. For example, if an organization wants to migrate
their system to a cloud and wants to know if they can get the kind of
performance they need and how much such service can cost, they can consult
a similar system with the best performance characteristics and see how much
cost is involved. Since benchmarking usually involves a reasonably simple
comparison, it can be even faster and less inexpensive than simulation for
the purpose of prediction. Benchmarking can also help reduce the space of
architectural design to be simulated, since simulation can be centered around the configuration of the architecture with the
best performance and cost characteristics.
In a nutshell, this research will demonstrate a
fast and inexpensive way of exploring, evaluating, and selecting among architectural
design alternatives as per stakeholder goals. As a special case, it provides a rational
decision support for Cloud Computing, which seems to be among the most
critical technological innovations for cost savings, especially in these
tough economic times. This is also one of the first proposals for a
rational and systematic way of transitioning from stakeholder goals to the
architectural design of a cloud computing-based system. The work
demonstrates the value of goal-oriented – i.e. a rational - approach to the
science of design. It also demonstrates the value of simulation and
benchmarking in understanding and conquering the complexity of a
(cloud-based) system of systems.
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