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, a 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 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.


MEMBERS                                                                              Team Private Page

Dr.Lawrence Chung

Tom Hill