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Placement and Chaining for Run-Time IoT Service Deployment in Edge-Cloud

机译:边缘云中运行时IoT服务部署的放置和链接

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This paper investigates an efficient placement and chaining of Virtual Network Functions (VNFs) to provide cloud based IoT services with minimal resource usage cost. We take into account bandwidth capacity and link delay of network connection between clouds where VNFs are allocated and underlying IoT networks where sensors and IoT gateways are deployed. Regarding the constantly changing network dynamics, input traffic of service components is considered at the lower granularity level of messages based on the communication between each VNF and corresponding sensors via IoT gateways. From the algorithm perspective, the specific topology of multiple edge clouds is leveraged to improve the solution. In this paper, we present an NFV-based high-level architecture for a system that enables the deployment of IoT services across multiple edges and clouds. We formulate the VNF placement problem using a non-convex Integer Programming model. Taking into account different IoT topologies, we devise two algorithms for small- and large-scale networks to find the near optimal solution: i) a customized Markov approximation with two techniques, i.e., multi-start and batching, and a node ranking-based heuristic. Simulation and experimental results show that the proposed solution improves the cost up to 21% compared to state-of-the-art schemes.
机译:本文研究了虚拟网络功能(VNF)的有效放置和链接,以提供具有最低资源使用成本的基于云的IoT服务。我们考虑了带宽容量和分配VNF的云与部署传感器和IoT网关的基础IoT网络之间的网络连接的链路延迟。关于不断变化的网络动态,基于每个VNF与相应传感器之间通过物联网网关的通信,在较低的消息粒度级别考虑服务组件的输入流量。从算法的角度来看,可以利用多个边缘云的特定拓扑来改进解决方案。在本文中,我们为系统提供了一种基于NFV的高级体系结构,该体系结构可跨多个边缘和云部署IoT服务。我们使用非凸整数编程模型来制定VNF放置问题。考虑到不同的物联网拓扑,我们为小型和大型网络设计了两种算法以找到接近最佳的解决方案:i)使用多种技术(即多开始和批处理以及基于节点排名)的自定义马尔可夫近似启发式。仿真和实验结果表明,与最新方案相比,所提出的解决方案将成本降低了21%。

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