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首页> 外文期刊>Communications Surveys & Tutorials, IEEE >Complementing IoT Services Through Software Defined Networking and Edge Computing: A Comprehensive Survey
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Complementing IoT Services Through Software Defined Networking and Edge Computing: A Comprehensive Survey

机译：通过软件定义的网络和边缘计算补充IOT服务：全面的调查

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摘要

Millions of sensors continuously produce and transmit data to control real-world infrastructures using complex networks in the Internet of Things (IoT). However, IoT devices are limited in computational power, including storage, processing, and communication resources, to effectively perform compute-intensive tasks locally. Edge computing resolves the resource limitation problems by bringing computation closer to the edge of IoT devices. Providing distributed edge nodes across the network reduces the stress of centralized computation and overcomes latency challenges in the IoT. Therefore, edge computing presents low-cost solutions for compute-intensive tasks. Software-Defined Networking (SDN) enables effective network management by presenting a global perspective of the network. While SDN was not explicitly developed for IoT challenges, it can, however, provide impetus to solve the complexity issues and help in efficient IoT service orchestration. The current IoT paradigm of massive data generation, complex infrastructures, security vulnerabilities, and requirements from the newly developed technologies make IoT realization a challenging issue. In this research, we provide an extensive survey on SDN and the edge computing ecosystem to solve the challenge of complex IoT management. We present the latest research on Software-Defined Internet of Things orchestration using Edge (SDIoT-Edge) and highlight key requirements and standardization efforts in integrating these diverse architectures. An extensive discussion on different case studies using SDIoT-Edge computing is presented to envision the underlying concept. Furthermore, we classify state-of-the-art research in the SDIoT-Edge ecosystem based on multiple performance parameters. We comprehensively present security and privacy vulnerabilities in the SDIoT-Edge computing and provide detailed taxonomies of multiple attack possibilities in this paradigm. We highlight the lessons learned based on our findings at the end of each section. Finally, we discuss critical insights toward current research issues, challenges, and further research directions to efficiently provide IoT services in the SDIoT-Edge paradigm.
机译：数百万个传感器不断生产和传输数据，以使用事物互联网（物联网）中的复杂网络来控制现实世界基础架构。然而，IoT设备的计算能力有限，包括存储，处理和通信资源，以在本地有效地执行计算密集型任务。边缘计算通过将计算较近到IOT设备的边缘来解决资源限制问题。在网络上提供分布式边缘节点可降低集中计算的应力，并克服IOT中的延迟挑战。因此，边缘计算为计算密集型任务提供了低成本解决方案。软件定义的网络（SDN）通过呈现网络的全局视角来实现有效的网络管理。虽然SDN没有明确开发IOT挑战，但它可以提供动力来解决复杂性问题并帮助高效的物联网服务编排。当前的IOT范例大规模数据生成，复杂的基础设施，安全漏洞以及新开发技术的要求使IOT实现有挑战性的问题。在这项研究中，我们对SDN和边缘计算生态系统提供了广泛的调查，以解决复杂物联网管理的挑战。我们使用边缘（SDIOT-Edge）介绍了对软件定义的物质管理器互联网的最新研究，并突出了整合这些多样化架构的关键要求和标准化工作。通过SDIOT-Edge计算的不同案例研究进行了广泛的讨论，以设想潜在的概念。此外，我们基于多种性能参数对Sdiot-Edge生态系统进行了最先进的研究。我们全面呈现SDIOT-Edge计算中的安全和隐私漏洞，并在此范式中提供多种攻击可能性的详细分类。我们突出了根据我们在每个部分结束时所吸取的教训。最后，我们讨论了对当前研究问题，挑战和进一步研究方向的关键见解，以有效地在SDIOT-EDGE范式中提供物联网服务。

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