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arXiv 2210.03338cs.NI
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论嵌入计算服务的网络中的路由优化

On Routing Optimization in Networks with Embedded Computational Services

Lifan Mei, Jinrui Gou, Jingrui Yang, Yujin Cai, Yong Liu

AI总结:

针对嵌入计算服务的网络,本文建立多类路由优化模型,提出低复杂度启发式算法及具性能保证的在线算法,并在真实拓扑上验证其灵活适配性与近优性能。

摘要:

现代通信网络正越来越多地配备网内计算能力和服务。此类网络中的路由比传统路由复杂得多。一条流的合法路由不仅需要具备足够的通信和计算资源,还必须符合各类特定于应用的路由约束。本文对嵌入计算服务的网络中的路由优化问题进行了全面研究。我们开发了一组路由优化模型,并针对多样化的计算场景推导出低复杂度的启发式路由算法。对于动态需求,我们还开发了一种具有性能保证的在线路由算法。通过在真实拓扑上对新兴应用进行评估,我们证明了所提模型能够灵活定制,以满足不同计算应用的多样化路由需求。我们提出的启发式算法显著优于基线算法,并能在各种场景中取得接近最优的性能。

英文摘要:

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.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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