# Cloud Based Smart City Services for Industrial Internet of Things in Software-Defined Networking
## 2 Literature Review
### IoT-SDN in Smart Cities  
In order to provide a more scalable and agile network, we support IoT-based smart city environments with the SDN paradigm. On top of the configured city, [PERSON] et al. [21], authors introduced a privacy-preserving technique. This is accomplished by the fact that the data packets of all IoT devices are handled by the SDN controller and their data is separated depending on the context. [PERSON] et al. [22] presented our SDN-IoT focused smart city framework, which is optimised, regulated, and controlled by a global control centre. The proposed architecture embraces heterogeneous networks and includes multiple networks, namely ZigBee, MANETs, sensor networks, and Bluetooth. [PERSON] et al. [23] proposed model utilizes flow routing, a network routing technique that takes into consideration changes in data flow to improve routing efficiency and modify the duration of packet forwarding between the various nodes from each instance of the Routing Protocol for Low-Power and Lossy Networks (RPL). These two network control levels, called SD- multi-hop clustering technique (MHC)-RPL, deliver better results in respect of network efficiency. [PERSON] et al. [21] implemented to test the SDN network infrastructure integrated IoT management framework, and also the interaction of IoT traffic with SDN switches. We conducted numerous IoT traffic tests to perform management system and network infrastructure behavioral investigations, which were generated based on the one M2M specification of the productive resources. [PERSON] et al. [24] discussed the use case of Poznan Smart City, illustrating how a single unifying SDN-based platform can be used to \"split\" a city into multiple smart spaces functioning over a shared network and cloud infrastructure, as well as how the network architecture allowed by OpenFlow can be used to automate the development of IoT devices to be used in cloud-based multi-tenant implementations. [PERSON] et al. [25] proposed a new control system based on SDN and IoT integration in smart city environments. When an emergency situation occurs, this control system works and automatically alters the paths of regular and emergency traffic congestion to diminish the amount of time that emergency services need to access the emergency area [26] proposed the LBBSRT load balancing method, which is based on server response times and takes benefit of SDN adaptability. We execute user requests by achieving equally balanced server loads using real-time response time of each server determined by the controller for load balancing. Our approach has a greater load balancing impact and processes requests with the shortest average server response times, according to simulations. The authors of [27] suggested to use POX controller to transform openflow devices into hubs, switches, load balancers, and firewalls. The POX controller makes running OpenFlow/SDN tests simple. Various QoS can be supplied to POX based on real or experimental topologies, enabling you to execute experiments on real hardware, testbeds, or in a mininet emulator. The first half of this paper will offer an introduction to POX, OpenFlow, and SDN, followed by a description of the link between POX and Mininet [28] represent a new software-defined networking (SDN) architecture for meeting the QoS needs of different IoT services and balancing traffic among IoT servers at the same time. The issue is first expressed as an NP-hard integer linear programming (ILP) paradigm. Then, using time-series analysis and fuzzy logic, a predictive and proactive heuristic technique is implemented. The proposed methodology creates the different clusters in IoT which will balance the load of all the clusters depending on the number of requests received on each cluster. If the number of requests are greater than the threshold value assigned then the extra requests received will be switched to the inter cluster from intra cluster so as to balance the load on all the clusters in IoT.