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.

中文翻译：

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通过软件定义网络和边缘计算补充物联网服务：综合调查

数以百万计的传感器使用物联网 (IoT) 中的复杂网络不断产生和传输数据，以控制现实世界的基础设施。然而，物联网设备的计算能力有限，包括存储、处理和通信资源，无法在本地有效地执行计算密集型任务。边缘计算通过使计算更接近物联网设备的边缘来解决资源限制问题。在整个网络中提供分布式边缘节点可减少集中计算的压力并克服物联网中的延迟挑战。因此，边缘计算为计算密集型任务提供了低成本的解决方案。软件定义网络 (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 并未明确针对物联网挑战而开发，但它可以 然而，为解决复杂性问题提供动力，并有助于高效的物联网服务编排。大量数据生成的当前物联网范式、复杂的基础设施、安全漏洞以及新开发技术的要求使物联网实现成为一个具有挑战性的问题。在这项研究中，我们对 SDN 和边缘计算生态系统进行了广泛的调查，以解决复杂的物联网管理挑战。我们展示了使用 Edge (SDIoT-Edge) 进行软件定义物联网编排的最新研究，并重点介绍了集成这些不同架构的关键要求和标准化工作。对使用 SDIoT-Edge 计算的不同案例研究进行了广泛讨论，以设想基本概念。此外，我们根据多个性能参数对 SDIoT-Edge 生态系统中的最新研究进行分类。我们全面介绍了 SDIoT-Edge 计算中的安全和隐私漏洞，并在此范例中提供了多种攻击可能性的详细分类。我们在每个部分的末尾强调根据我们的发现吸取的经验教训。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重要见解，以在 SDIoT-Edge 范式中有效地提供物联网服务。