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Ultra Large-Scale Wireless Network Models using Massively Parallel Discrete-Event Simulation

机译:超大型无线网络模型使用大规模并行离散事件仿真

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Mobile ad-hoc networks (MANETs) are becoming pervasive in our always-connected lives of iPhones, laptops, etc. While entertainment is important, next generation military applications can and will come to depend on these new technologies. Connectivity can no longer be optional; it has become a must-have requirement. Over the past decade, the DoD has spent billions of dollars investigating new approaches to radio including the Joint Tactical Radio System (JTRS) and Software-Defined Radios (SDRs). However, large-scale deployments (1 million+ nodes) have never been tested for a single homogeneous network of that magnitude. The goal of this paper is to demonstrate the efficacy of large-scale wireless network simulations on multiple High-Performance Computing (HPC) platforms. By exploiting the strengths of two different supercomputers, we evaluate our million node Optimized Link State Routing (OLSR) network on the CCNI Blue Gene/L as well as the Army Research Lab's SGI ICE 8200 (Harold) compute cluster. By exploiting infrequent synchronization we may push the simulation to its maximum potential for our model. We realize speedups between 315-450 in our normalized parallel simulation over sequential.
机译:移动ad-hoc网络(MANET)在我的始终关联的iPhone,笔记本电脑等人的生活中变得普遍存在。娱乐很重要,下一代军事应用可以依赖这些新技术。连接不能再是可选的;它已成为必要的要求。在过去十年中,国防部已经花费了数十亿美元,调查包括联合战术无线电系统(JTR)和软件定义的无线电(SDR)的新近的无线电方法。但是,大规模部署(100万+节点)从未测试过该幅度的单个均匀网络。本文的目标是展示大规模无线网络仿真对多个高性能计算(HPC)平台的功效。通过利用两种不同超级计算机的优势,我们在CCNI Blue Gene / L和Army Research Lab的SGI ICE 8200(HAROLD)计算群集上评估我们百万节点优化链路状态路由(OLSR)网络。通过利用不常见的同步,我们可以将模拟推向其模型的最大潜力。我们在顺序上实现了我们归一化的并行模拟中的315-450之间的加速。

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