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.

中文翻译：

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边缘云中运行时物联网服务部署的放置和链接

本文研究了虚拟网络功能 (VNF) 的有效放置和链接，以提供基于云的物联网服务，并且资源使用成本最低。我们考虑了分配 VNF 的云与部署传感器和物联网网关的底层物联网网络之间网络连接的带宽容量和链路延迟。对于不断变化的网络动态，基于每个 VNF 和相应传感器通过物联网网关之间的通信，在较低粒度级别的消息中考虑服务组件的输入流量。从算法的角度来看，利用多个边缘云的特定拓扑来改进解决方案。在本文中，我们提出了一个基于 NFV 的高级体系结构，该体系结构支持跨多个边缘和云部署物联网服务。我们使用非凸整数规划模型来制定 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优的解决方案：i) 使用两种技术（即多启动和批处理）以及基于节点排名的定制马尔可夫近似启发式。仿真和实验结果表明，与最先进的方案相比，所提出的解决方案将成本提高了 21%。