Mapping Task-Graphs on Distributed ECU Networks: Efficient Algorithms for Feasibility and Optimality

Abstract

We consider the problem of scheduling a number of periodic tasks T on a real-time architecture composed of a set of identical processors P connected by a common bus. Each processor p \in P has a certain amount of memory \mu (p). In our setting, a task \tau \in¸ T is specified by the period t(\tau), the memory requirement \mu (\tau), the execution time c(\tau), and the deadline d(\tau). We always assume d (\tau) \leqslant t(\tau). Tasks may communicate with each other by sending messages. We denote the set of messages by M, and for each m \in M, src(m) is the source task of m, dst(m) is the target task of m, l(m) is the length of m, and d(m) is the deadline for m. The problem is to find a mapping \prod\limits_{}{} : T \in P representing an assignment of the tasks to the processors that satisfies timing and resource requirements for both tasks and messages. The problem is known to be NP-hard even if tasks do not communicate with each other [9].