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.

Mobile ad hoc networks (MANETs) possess numerous and unique characteristics, such as high channel error-rate, severe link-layer contentions, frequent link breakage (due to node mobility), and dissimilar path properties (e.g., bandwidth, delay, and loss rate) that make these networks different from the traditional ones. These characteristics seriously interfere with communication and hence, ultimately degrade the overall performance in terms of end-to-end delay, packet delivery ratio, network throughput, and network overhead. The traditional referenced layered strict architecture is not capable of dealing with MANET characteristics. Along with this, the most important apprehension in the intent of MANETs is the battery-power consumption, which relies on non-renewable sources of energy. Even though improvements in battery design have not yet reached that great a level, the majority of the routing protocols have not emphasized energy consumption at all. Such a challenging aspect has gained remarkable attention from the researchers, which inspired us to accomplish an extensive literature survey on power-aware optimization approaches in MANETs. This survey comprehensively covers power-aware state-of-the-art schemes for each suggested group, major findings, crucial structures, advantages, and design challenges. In this survey, we assess the suggested power-aware policies in the past in every aspect so that, in the future, other researchers can find new potential research directions.

A huge amount of generated data is regularly exploding into the network by the users through smartphones, laptops, tablets, self-configured Internet-of-things (IoT) devices, and machine-to-machine (M2M) communication. In such a situation, satisfying critical quality-of-service (QoS) requirements (e.g., throughput, latency, bandwidth, and reliability) is a large challenge as a vast amount of data travels into the network. Nowadays, strict QoS requirements must be satisfied efficiently in many networked multimedia applications when intelligent multi-homed devices are used. Such devices support the concept of multi-homing. To be precise, they have multiple network interfaces that aim to connect and communicate concurrently with different networking technologies. Therefore, many multipath transport protocols are provided to multi-homed devices, which aim (1) to take advantage of several network paths at the transport layer (Layer-4) and (2) to meet the strict QoS requirements for providing low network latency, higher data rates, and increased reliability. To this end, this survey first presents the challenges/problems for supporting multipath transmission with possible solutions. Then, it reviews recent research efforts related to the concurrent multipath transmission (CMT) protocol and the multipath transmission control protocol (MPTCP). It reviews the latest research efforts by considering (1) how a multipath transport protocol operates (i.e., its functionality); (2) in what type of network; (3) what path characteristics it should consider; and (4) how it addresses various design challenges. Furthermore, it presents some lessons learned and discusses open research issues in multipath transport protocols.

Concurrent Multipath Transfer (CMT) uses multi-homing feature of Stream Control Transmission Protocol (SCTP) to transfer data concurrently over the multiple paths. CMT provides bandwidth aggregation, fault tolerance, and reliability in multipath data transfer. In multipath data transmission, each path has different delay and bandwidth. Therefore, destination receives unordered data which causes receiver buffer blocking and unwanted congestion window (cwnd) reduction. Both the problem degrades the CMT performance significantly. Thus, this paper proposes a new delay-based fast retransmission policy to adjust the transmission rate of each path according to path delay. Simulation results show that the proposed approach achieves better throughput, reduces the number of the timeout and improves the cwnd growth. The proposed approach improved throughput up to 16% in variable packet loss and 18% in variable network delay environment.