Task Allocation and Optimization of Distributed Embedded Systems with Simulated Annealing and Geometric Programming

Abstract

We consider the task model of periodic tasks running on a network of processor nodes connected by a bus based on the time-triggered protocol, an industry-standard bus protocol designed for safety-critical automotive and avionics distributed embedded systems, and present an integrated optimization framework that jointly considers one or more of the following attributes: task-to-processor allocation, task priority assignment, task period assignment and bus access configuration. We adopt a hierarchical optimization framework, where each possible task allocation and priority assignment is treated as one top-level coarse-grained state, which may contain many lower-level fine-grained states defined by different task period assignments and bus access configurations. Simulated annealing is used to explore the top-level states, which calls a geometric programming solver as a subroutine to explore the lower-level states contained within a given top-level state. Performance evaluation shows that our framework has good performance in terms of solution quality and scalability.