Network-on-chip (NoC) is a paradigm shift for communication between cores in multi-processor systems. It has emerged as a solution for addressing the limitations of bus-based communication in multi-processor system design. The use of MPSoC (Multi-Processor System on Chip) based design of real-time safety-critical embedded systems (such as, Avionics, Automotive etc.) is really a challenge because of the requirement of time predictability and reliability of highest degree. Task mapping and flow priority assignment are two crucial steps for real-time NoC design. Most of the earlier work on priority assignment for on-chip communications are either based on exhaustive search or are heuristic in nature.

In this paper, a search based explorative solution to the priority assignment problem has been proposed with a Genetic Algorithm (GA) based formulation that uses experimentally determined heuristics to converge faster with a better solution. Unlike other works in the area, proposed work considers the task execution time while assigning flow priorities. The paper proposes a combined priority assignment and task mapping solution. The approach has been validated with two real-time industrial applications - one from automotive domain, while the other one is from avionics.

片上网络（NoC）是多处理器系统中内核之间的通信的一种范式转换。它已成为解决多处理器系统设计中基于总线的通信局限性的解决方案。由于对时间的可预测性和最高可靠性的要求，使用基于MPSoC（片上多处理器系统）的实时安全关键嵌入式系统（例如航空电子，汽车等）的设计确实是一个挑战。任务映射和流程优先级分配是实时NoC设计的两个关键步骤。片上通信优先级分配的大部分早期工作要么基于穷举搜索，要么本质上是启发式的。

在本文中，已经提出了一种基于搜索的优先级分配问题的探索性解决方案，其中采用了基于遗传算法（GA）的公式，该公式使用实验确定的启发式方法更快地收敛于更好的解决方案。与该地区的其他工作不同，拟议工作在分配流程优先级时会考虑任务执行时间。本文提出了一种组合的优先级分配和任务映射解决方案。该方法已在两种实时工业应用中得到验证-一种来自汽车领域，另一种来自航空电子。