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Wireless Sensor Networks (WSN) include a large number of sensor nodes that are connected to each other with the limitations in energy sources, battery life, memory, mobility and computational capacity. Since the traditional layered architecture was appropriate only for the wired network. It works within a strict boundary that leads to more energy usage as well as more communication traffic. It also impacts on the overall network lifespan and performance of the system. Energy efficiency and network lifespan are the primary concern of WSN due to the fact that each node in the network operates with extremely limited energy. Recent studies have shown that the Open System Interconnection (OSI) model cannot meet the demands of the wireless sensor network. To overcome such limitations, the cross-layer design has been introduced. It allows direct interactions between protocol at non-adjacent layers. In this paper, we present different types of cross-layer design techniques in Wireless Sensor Network (WSN) and discusses several cross-layer proposals given by researchers. At the end, the paper highlights some challenges faced in implementing CLD in Wireless Sensor Networks.

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Transmission Control Protocol (TCP) used multiple paths for performing transmission of data simultaneously to improve its performance. However, previous TCP protocols in Internet of Things (IoT) networks experienced difficulty to transmit a greater number of subflows. To overcome the above issues, we introduced cross-layer framework to perform efficient packet scheduling and congestion control for increasing the performance of TCP in IoT networks. Initially, the proposed IoT network is constructed based on grid topology using Manhattan distance which improves the scalability and flexibility of the network. After network construction, packet scheduling is performed by considering numerous parameters such as bandwidth, delay, buffer rate, etc., using fitness based proportional fair (FPF) scheduling algorithm and selecting best subflow to reduce the transmission delay. The scheduled subflow is sent over an optimal path to improve the throughput and goodput. After packet scheduling, congestion control in TCP is performed using cooperative constraint approximation 3 + (CoCoA3 + -TCP) algorithm in which three stages are employed namely congestion detection, fast retransmission, and recovery. The congestion detection in TCP-IoT environment is performed by considering several parameters in which cat and mouse-based optimization (CMO) is utilized to adaptively estimate retransmission timeout (RTO) for reducing the delay and improving the convergence during retransmission. Fast retransmission and recovery are performed to improve the network performance by adjusting the congestion window size thereby avoiding congestion. The simulation of cross-layer approach is carried out using network simulator (NS-3.26) and the simulation results show that the proposed work outperforms high TCP performance in terms of throughput, goodput, packet loss, and transmission delay, jitter, and congestion window size.

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The Internet of Things (IoT) is widely known as a revolutionary paradigm that offers communication among different types of devices. The primary goal of this paradigm is to implement efficient and high-quality smart services. It requires a protocol stack that offers different service requirements for inter-communication between different devices. Transmission Control Protocol (TCP) and User Datagram Protocol (UDP) are used as transport layer protocols in IoT to provide the quality of service needed in various IoT devices. IoT encounters many shortcomings of wireless networks, while also posing new challenges due to its uniqueness. When TCP is used in an IoT system, a variety of challenging issues have to be dealt with. This paper provides a comprehensive survey of various issues which arises due to the heterogeneous characteristics of IoT. We identify main issues such as Retransmission Timeout (RTO) algorithm issue, congestion and packet loss issue, header overhead, high latency issue, link layer interaction issue, etc. Moreover, we provide several most probable solutions to the above-mentioned issues in the case of IoT scenarios. RTO algorithm issue has been resolved by using algorithms such as CoCoA, CoCoA+, and CoCoA++. Apart from these, the high latency issue has been solved with the help of a long lived connection and TCP Fast open. Congestion and packet loss issue has been resolved by using several TCP variants such as TCP New Reno, Tahoe, Reno, Vegas, and Westwood.