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Policy-constrained bio-inspired processes for autonomic route management

机译:受政策约束的生物启发式流程,用于自主路线管理

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Autonomic networking systems must be designed to achieve an appropriate balance between the operation of decentralized algorithms and processes that seek to maintain optimal or near-optimal behavior in terms of global stability, improved performance and adaptability, robustness and security, with the requirement for top-down control of the system by humans to ensure business goals are met. Taking a communications networking survivability case study, we show how the operation of decentralized algorithms, inspired by the operation of biological systems, can be controlled and constrained through the deployment of management policies authored by network administrators. We present sur-vivability-related routing algorithms (inspired by chemotaxis, reaction-diffusion and quorum sensing biological processes) which work together to effectively reconfigure network resources when transient link failures occur and demonstrate how these algorithms can be re-parameterized via policies to improve performance given prevailing network conditions. Simulation results show how the combined operation of these algorithms, as controlled by policies, allows the network to react well to survive link failure events.
机译:自主网络系统的设计必须在分散算法的操作和寻求在全局稳定性,改进的性能和适应性,鲁棒性和安全性方面保持最佳或接近最佳行为的过程之间达到适当的平衡,并要求最高人工控制系统,以确保实现业务目标。以通信网络的可生存性案例研究为例,我们展示了如何通过部署由网络管理员编写的管理策略来控制和约束分散式算法的运行(受生物系统的运行启发)。我们提出了与生存能力相关的路由算法(受趋化性,反应扩散和群体感应生物过程启发),这些算法可以一起工作,以在发生瞬时链路故障时有效地重新配置网络资源,并演示如何通过策略对这些算法进行重新参数化以改善性能在当前网络条件下的性能。仿真结果表明,受策略控制的这些算法的组合操作如何使网络做出良好反应,以应对链路故障事件。

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