## 1 Introduction
The concept of web services with a service-oriented solution is introduced to cater to this problem. The main idea was to integrate the Web of Things technology with intelligent devices. The authors in this paper conducted a survey and pointed out some open research challenges in IoT. Challenges in terms of service management in IoT are categorized into four areas. Interoperability challenges include connectivity issues between different devices and protocols, which lead to integrating diverse IoT platforms and how to manage them. The scalability-related challenge in IoT regarding service and management is also discussed. Service management issues regarding scalability include the registration of new devices and upgradation of any software and firmware in a heterogeneous environment. Various applications are running on the internet. Each application and service has different requirements for QoS (quality of service). Bandwidth, less delay, and packet loss are all parameters that indicate the QoS of any service. These parameters vary according to the QoS with respect to the application's nature. In a traditional network, it is challenging to maintain QoS for various applications and services. Many methods have been proposed to resolve QoS issues, but none of them have had a significant impact due to the nature of traditional networks. Heterogeneity, directly and indirectly, impacts every other parameter or challenge in IoT. QoS (Quality of Service) is one of the most critical factors in IoT. As multiple domain applications and services are part of the IoT, and their requirements are different, they require different QoS. However, IoT systems consist of heterogeneous devices, in which various network connectivity options, communications modes, and protocols are implemented. Therefore, there is a high degree of heterogeneity in IoT, and there is expected to be more in the future. QoS is one of the burning topics by researchers. There are various issues under the QoS, such as interoperability, response time, reliability availability, mobility, security, and many more defined by researchers [6; 7]. All these challenges have direct ties with heterogeneity. Researchers have seen potential in SDN to resolve challenges in IoT. Research communities have presented many methods to cater to different challenges in IoT. The researchers considered the virtualization of networks, implementation of gateways, and SDN-based frameworks to counter the interoperability and heterogeneity problems. The authors also discussed some other challenges in IoT related to QoS (quality of service) that different services require different quality to maintain in large systems. Handling massive amounts of data and keeping them is another complex issue, as is gathering useful information from data and delivering services of IoT to apply AI and ML techniques for better results. Scalability, security, and management are other open research challenges in IoT [4]. In SD-WAN (software defined-wide area network), the controller becomes overwhelmed due to a continuous increase in traffic, and it has limited processing capacity. This impacts the QoS of the network. To cater to this issue, authors in [8; 9] presented deep reinforcement learning (DRL) in SD-WAN. They achieved optimization of load-balancing, minimizing the average request delay and increasing the survivability of the network. These studies show the controller capacity's impact on QoS and how modern techniques are being used to mitigate these kinds of challenges.