Conferences & Events

  • - AVICPS 2010, San Diego, CA
  • - RTSS 09. Washington, D.C.
  • - RTAS 09. Sweden.
  • - ICDCS 10. Italy
  • - ECRTS 10

Research Areas

Predictable Scheduling for Multicore Processors for Real-Time Systems

While multiprocessor real-time systems is an old problem, multicore processors had brought a renew interest along with new dimensions to the problem. For instance, there is a need to tradeoff different levels of migration cost, different degrees of inter-core hardware sharing (e.g. memory bandwidth), etc. Our research is aimed at providing new knobs to perform these tradeoffs with additional application information.

Beyond real-time systems general-purpose systems are now faced with the fact that they need to parallelize their work in order to get the expected performance increment from additional cores in the new processors. However, partition the work into parallel pieces is a necessary but not sufficient condition. Equally important is the allocation of CPU cycles to these parallel pieces (tasks). In the extreme if we run all the tasks of the parallel pieces in the same core, such parallelism is completely wiped out. Hence, the task-to-core allocation and the scheduling of hardware resources between core (e.g. cache, memory bandwidth) are allocated can change completely the performance that is possible to obtain. We are working on new ways to take advantage of application knowledge to use them as parameter in the scheduling algorithms at all levels of the computer system.

Mixed-Criticality Scheduling for Real-Time Systems

Functionally consolidation bring the problem of resources sharing between tasks of different criticality. When these different criticalities are combined with tasks with execution times that have large variations depending on the environment, we end up in a situation where overload are common and the scheduler needs to have a well-defined overload guarantees. For instance, the execution time of an obstacle avoidance (OA) task in an autonomous vehicle depends on the number of obstacles that the vehicle detects. As a result, when an excessive number of obstacles is detected, the scheduler should be able to provide more CPU cycles to the OA task stealing them from other less important tasks.

Predictable Dynamic Real-Time Systems

As systems scale, both centralized control and unique steady-state execution behavior blur. This changes the way we need to think about resource allocation in large real-time systems. On the one hand, decentralized control implies that resource allocation decisions needs to be negotiated among peers instead of mandated from a centralized authority. On the other hand, the dynamism of these systems forces us to, not only have multiple steady-state behaviors, but also develop new ways to ensure predictable transitions between behaviors and converges of the system toward the desirable steady states.

Analytic Integration of Cyber-Physical Systems

A recent NIST study found that up to 70% of the cost of a software projects is spent correcting errors. Furthermore, in multi-tier industries where the final product is comprised of components provided by multiple suppliers, the bulk of the problems are found at integration time. This is the case of the avionics and automotive industries where conflicting design decisions and assumptions made by the different suppliers, can create costly integration errors.

To solve the integration problem we are working on new approaches to replace the integration of physical parts with an integration of analytical models. Once models are integrated, analysis algorithms are used to replace integration testing in the discovery of potential errors. This replacement is not a one-to-one replacement, instead, it is aimed at raising the confidence of the validation to very high levels while keeping the cost of the correction of errors as low as possible. Because, this integration process does not involve a physical integration it is called virtual integration.

The avionics industry has formed the Aerospace Vehicle Systems Institute (AVSI) to explore the use of model-based engineering approaches for virtual integration in this industry.

Two DARPA research initiatives are exploring related topics. First, the META-II is exploring the foundry manufacturing style where a comprehensive model is the only interfase between design and manufacturing. Such a model must contain a complete description of the desired behavior. The design stage is then responsible of both producing and testing the model for correctness. Once the model is out of this design stage then the model is the only and complete description of the system that can be use in a foundry to create the final and correct product. This character of the model implies the use of analysis algorithms that verifies the behavior of the model in the same approach we are pursuing.

Secondly, the Systems 2020 initiative is aimed at increasing the speed of development of cyber-physical systems and their foreseen changes while keeping them adaptable to unforeseen changes. Both, model-based engineering and platform-based engineering are recognized as two key technologies to achieve these goals. We believe that analytic models can play a key role in this effort at least in two areas. On the one hand, analytic models can increase the speed of the development of cyber-physical systems but also the confidence in their correctness. On the other hand, these models can exploit analytic invariants of stable PBE layers (e.g. limited interaction between components) that can simplify the analysis of models increasing its scalability and even enabling new types of analysis and properties.

Finally, we recognize that there is still an important number of research challenges ahead of us. As a result, we organized the Analytic Virtual Integration of Cyber-Physical Systems Workshop to lead an effort in the research community in this front. The first instance of this workshop already took place collocated with the IEEE Real-Time Systems Symposium in San Diego, CA in December of 2010. We are incluiding in both the steering and program committees people not only from academia but also from DARPA, AFRL, AVSI, and the avionics and automotive industries.

Highlights

  • First Analytic Virtual Integration of Cyber-Physical Systems Workshop (AVICPS) @ RTSS 2010