  In this paper, to analyze end-to-end timing behavior in heterogeneous
processor and network environments accurately, we adopt a heterogeneous
selection value on communication contention (HSV_CC) algorithm, which can
synchronize tasks and messages simultaneously, for stream processing
distribution. In order to adapt HSV_CC to automotive data stream management
system (DSMSs), one must address three issues: (i) previous task and message
schedules might lead to less efficient resource usages; (ii) the conventional
method to determine the task scheduling order may not be best suited to deal
with stream processing graphs, and; (iii) there is a need to be able to
schedule tasks with time-varying computational requirements efficiently. To
address (i), we propose the heterogeneous value with load balancing and
communication contention (HVLB_CC) (A) algorithm, which considers load
balancing in addition to the parameters considered by the HSV_CC algorithm. We
propose HVLB_CC (B) to address issue (ii). HVLB_CC (B) can deal with stream
processing task graphs and more various directed acyclic graphs to prevent
assigning a higher priority to successor tasks. In addition, to address issue
(iii), we propose HVLB_CC_IC. To schedule tasks more efficiently with various
computation times, HVLB_CC_IC utilizes schedule holes left in processors. These
idle time slots can be used for the execution of an optional part to generate
more precise data results by applying imprecise computation models.
Experimental results demonstrate that the proposed algorithms improve minimum
schedule length, accuracy, and load balancing significantly compared to the
HSV_CC algorithm. In addition, the proposed HVLB_CC (B) algorithm can schedule
more varied task graphs without reducing performance, and, using imprecise
computation models, HVLB_CC_IC yields higher precision data than HVLB_CC
without imprecise computation models.
