MIST：无线Mesh网络中软件定义组播的一种高效方法
MIST: An Efficient Approach for Software-Defined Multicast in Wireless Mesh Networks
AI总结：
本文针对无线Mesh网络中软件定义组播面临的邻域干扰问题，提出最小干扰Steiner树（MIST）双准则优化模型，并利用子模性质设计具有性能保证的两阶段松弛近似算法，以同时优化组播树长度代价与干扰。
摘要：
组播是软件定义网络（SDN）中一种至关重要的信息传播技术。借助SDN，组播服务可以整合在不同节点上实现的网络功能，这被称为软件定义组播。面向5G及未来（B5G）的新兴泛在无线网络天然支持组播。然而，无线信道的广播特性，尤其是在密集部署场景下，会导致邻域干扰成为系统性能下降的主要因素，这给无线Mesh网络中的软件定义组播带来了新的挑战。为解决这一问题，本文提出了一种创新方法，其核心思想是同时最小化组播树的总长度代价和干扰。据此，本文形式化了一个新的双准则优化问题——最小干扰Steiner树（MIST），它是顶点加权隔离Steiner树问题的边加权变体。为求解该双准则问题，本文没有采用启发式方法，而是使用了一种具有性能保证的MIST近似算法。具体而言，该方法利用干扰度量的单调子模性质，识别MIST的Pareto最优解，然后将问题转化为Steiner树约束下的子模最小化问题，并设计了一个两阶段松弛算法。仿真结果展示并验证了所提算法的性能。
英文摘要：
Multicasting is a vital information dissemination technique in Software-Defined Networking (SDN). With SDN, a multicast service can incorporate network functions implemented at different nodes, which is referred to as software-defined multicast. Emerging ubiquitous wireless networks for 5G and Beyond (B5G) inherently support multicast. However, the broadcast nature of wireless channels, especially in dense deployments, leads to neighborhood interference as a primary system degradation factor, which introduces a new challenge for software-defined multicast in wireless mesh networks. To tackle this, this paper introduces an innovative approach, based on the idea of minimizing both the total length cost of the multicast tree and the interference at the same time. Accordingly, a novel bicriteria optimization problem is formulated--\emph{Minimum Interference Steiner Tree (MIST)}, which is the edge-weighted variant of the vertex-weighted secluded Steiner tree problem \cite{chechik2013secluded}. To solve the bicriteria problem, instead of resorting to heuristics, this paper employs an innovative approach that is an approximate algorithm for MIST but with guaranteed performance. Specifically, the approach exploits the monotone submodularity property of the interference metric and identifies Pareto optimal solutions for MIST, then converts the problem into the submodular minimization under Steiner tree constraints, and designs a two-stage relaxation algorithm. Simulation results demonstrate and validate the performance of the proposed algorithm.
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。
