Numerous municipalities employ the smart city model in large cities to improve the quality of life of their residents, utilize local resources efficiently, and save operating expenses. This model incorporates many heterogeneous technologies such as Cyber-Physical Systems (CPS), Wireless Sensor Networks (WSNs), and Cloud Computing (ClCom). However, effective networking and communication protocols are required to provide the essential harmonization and control of the many system mechanisms to achieve these crucial goals. The networking requirements and characteristics of smart city applications (SCAs) are identified in this study, as well as the networking protocols that can be utilized to serve the diverse data traffic flows that are required between the dissimilar mechanisms. Additionally, we show examples of the networking designs of a few smart city systems, such as smart transport, smart building, smart home, smart grid, smart water, pipeline monitoring, and control systems.

The Internet of things (IoT) extends the Internet space by allowing smart things to sense and/or interact with the physical environment and communicate with other physical objects (or things) around us. In IoT, sensors, actuators, smart devices, cameras, protocols, and cloud services are used to support many intelligent applications such as environmental monitoring, traffic monitoring, remote monitoring of patients, security surveillance, and smart home automation. To optimize the usage of an IoT network, certain challenges must be addressed such as energy constraints, scalability, reliability, heterogeneity, security, privacy, routing, quality of service (QoS), and congestion. To avoid congestion in IoT, efficient load balancing (LB) is needed for distributing traffic loads among different routes. To this end, this survey presents the IoT architectures and the networking paradigms (i.e., edge–fog–cloud paradigms) adopted in these architectures. Then, it analyzes and compares previous related surveys on LB in the IoT. It reviews and classifies dynamic LB techniques in the IoT for cloud and edge/fog networks. Lastly, it presents some lessons learned and open research issues.

Widespread usage of unmanned aerial vehicles (UAVs) in new and emerging applications needs dynamic and adaptive networking. The development of routing protocols for UAV ad hoc networks faces numerous issues because of the unique characteristics of UAVs, such as rapid mobility, frequent changes in network topology, and limited energy consumption. The Optimized Link State Routing (OLSR) protocol seems to be a promising solution as it offers improved delay performance. It is expected that OLSR will satisfy the strict demands of real-time UAV applications such as “search and rescue” (SAR) missions as it involves the most recent update of routing information. The classical OLSR routing protocol and its enhanced versions, D-OLSR, ML-OLSR, and P-OLSR, use different techniques to make an appropriate decision for routing packets. These routing techniques consider the quality of a wireless link, type of antenna, load, and mobility-aware mechanism to select the best UAV to send the message to the destination. This study evaluates and examines the performance of the original and modified OLSR routing protocols in UAV ad hoc networks for three SAR scenarios: (1) increasing mobility, (2) increasing scalability, and (3) increasing the allowed space of UAVs. It analyzes and validates the performance of the four OLSR-based routing protocols. It determines the best OSLR routing protocol by taking into account the packet delivery ratio, latency, energy consumption, and throughput. The four routing protocols and the SAR scenarios were simulated using NS-3.32. Based on the simulation results, ML-OLSR outperforms OLSR, D-OLSR, and P-OLSR in the considered measures.

Network Digital Twin (NDT) is an evolving technology that provides a framework through which a network administrator can have a virtual representation of a computer network. As a result, analysis, monitoring, testing, running new protocols, and more can be performed using the NDT before the final deployment of the developed approach. In this way, the consequences of direct deployment and the negative impact on network operations can be avoided. Telecommunications, along with traffic engineering as one of its critical components, play a prominent role across various networking domains, including Internet service providers, data centers, cellular networks, intelligent transportation systems, and smart cities. In this context, NDT has the potential to serve as a key enabler for optimizing these domains by providing a digital framework, which can facilitate the evaluation and enhancement of scenarios such as congestion management and routing strategies. Accordingly, this paper presents a comprehensive survey on how NDT can facilitate advancements in network traffic engineering across a wide range of networking domains. First, we start with an in-depth analysis of the evolution of the network digital twin technology and provide a comparison with simulation tools in order to make it feasible to select the right one based on the requirements. Next, we examine the role of NDT in various networking and telecommunication domains, including its potential as an enabler for 5G/6G networks, the Industrial Internet of Things (IIoT), smart manufacturing, intelligent transportation systems, and smart cities. We also explore the applicability of NDT technology from a traffic engineering perspective across different network types. Subsequently, we highlight key open research questions and potential future directions that warrant further investigation. Finally, we conclude by outlining the promising future trajectory of NDT within the aforementioned domains.