1. Adaptive Resource Management Architecture for DRE Systems Nishanth Shankaran nshankar@dre.vanderbilt.edu

2. 2 Motivation: Distributed Real-time & Embedded Systems Problem Need to operate in open & unpredictable environments No accurate apriori knowledge of operating conditions, resource availability, and input workload Effective utilization of multiple resources – computational power and network bandwidth Solution Solution Adaptive Resource Management Architecture – Resource Allocation and Control Engine (RACE) System Characteristics Operate under limited resources Tight real-time performance QoS constraints Dynamic & uncertain environments Loss or degradation of hardware with time Distribution of computation Multiple nodes & data centers Task distribution among hosts/data centers Integration of information Data collection – Radar Compute counter measure(s) Execute counter measure(s) Coordinated operation E.g., NASA Earth Science Mission & Total Ship Computing Environment

3. 3 Resource Allocation and Control Engine Dynamic resource management framework atop CORBA Component Model (CCM) middleware (CIAO/DAnCE) Allocates components to available resources Configure components to satisfy QoS requirements based on dynamic mission goals Perform run-time adaptation Coarse-grained mechanisms React to new missions, drastic changes in mission goals, or unexpected circumstances such as loss of resources e.g., component re-allocation or migration Fine-grained mechanisms Compensate for drift & smaller variations in resource usage e.g., adjustment of application parameters, such as QoS settings

4. 4 DRE System Model QoS Setting at the Application Layer QoS Setting at the Middleware Layer QoS Setting at the OS Layer QoS Setting at the N/W Layer QoS parameters are all layers need to be configured/managed to met end-to-end QoS requirements

5. 5 System Model of a CCM Based DRE System Container provides an encapsulation for the application QoS settings are specified at the container level These settings are then used to configure the middleware RACE currently manages OS QoS parameters/knobs to meet e-2-e QoS requirements Bandwidth Broker determines Network QoS settings

6. 6 System Model of a DDS Based DRE System RACE can manage OS & N/W QoS settings even for DDS based systems

7. 7 Concluding Remarks and Future Work Architecturally, both distribution middleware are similar Resource/QoS management architecture developed for one can be applied for the other with minor modifications Currently, we have applied RACE for CCM based DRE systems In the future, we plan to apply RACE for DDS bases DRE systems