Modern communication networks are increasingly equipped with in-network computational capabilities and services. Routing in such networks is significantly more complicated than the traditional routing. A legitimate route for a flow not only needs to have enough communication and computation resources, but also has to conform to various application-specific routing constraints. This paper presents a comprehensive study on routing optimization problems in networks with embedded computational services. We develop a set of routing optimization models and derive low-complexity heuristic routing algorithms for diverse computation scenarios. For dynamic demands, we also develop an online routing algorithm with performance guarantees. Through evaluations over emerging applications on real topologies, we demonstrate that our models can be flexibly customized to meet the diverse routing requirements of different computation applications. Our proposed heuristic algorithms significantly outperform baseline algorithms and can achieve close-to-optimal performance in various scenarios.

翻译：现代通信网络正日益配备网内计算能力和服务。此类网络中的路由相较于传统路由更为复杂。一条合法流路径不仅要具备足够的通信与计算资源，还需满足各类应用特定的路由约束。本文对嵌入计算服务网络中的路由优化问题进行了系统性研究。我们针对不同计算场景构建了一套路由优化模型，并推导出低复杂度的启发式路由算法。针对动态需求，我们还开发了一种具有性能保障的在线路由算法。通过在真实拓扑上对新兴应用的评估，我们证明了所提模型能够灵活定制以满足不同计算应用多样化的路由需求。我们提出的启发式算法显著优于基线算法，并在多种场景下能够达到接近最优的性能。