In many embedded systems, existence of a data cache might influence the effectiveness of process scheduling policy significantly. Consequently, a scheduling policy that takes inter-process data reuse into account might result in large performance benefits. In this paper, we focus on array-intensive embedded applications and present a locality-conscious scheduling strategy where we first evaluate the potential data reuse between processes, and then, using the results of this evaluation, select

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... order for process executions. We also show how process codes can be transformed by an optimizing compiler for increasing inter-process data reuse, thereby making localityconscious scheduling more effective. Our experimental results obtained using two large, multi-process application codes indicate significant runtime benefits.