With the evolution of the fifth-generation (5G) wireless network, the Internet of Things (IoT) has become a revolutionary technique that enables a diverse number of features and applications. It can able a diverse amount of devices to be connected in order to create a single communication architecture. As it has significantly expanded in recent years, it is fundamental to study this trending technology in detail and take a close look at its applications in the different domains. It represents an enabler of new communication possibilities between people and things. The main asset of this concept is its significant influence through the creation of a new world dimension. The key features required for employing a large-scale IoT are low-cost sensors, high-speed and error-tolerant data communications, smart computations, and numerous applications. This research work is presented in four main sections, including a general overview of IoT technology, a summary of previous correlated surveys, a review regarding the main IoT applications, and a section on the challenges of IoT. The purpose of this study is to fully cover the applications of IoT, including healthcare, environmental, commercial, industrial, smart cities, and infrastructural applications. This work explains the concept of IoT and defines and summarizes its main technologies and uses, offering a next-generation protocol as a solution to the challenges. IoT challenges were investigated to enhance research and development in the fields. The contribution and weaknesses of each research work cited are covered, highlighting eventual possible research questions and open matters for IoT applications to ensure a full analysis coverage of the discussed papers.

The rejection of an ongoing connection/session is serious problem and it degrades the QoS and efficiency of the network rather than rejecting a request for new connection. The impact on performance of handovers is a serious problem in cellular systems that must be addressed. During handover there may be delay in packets and connections may drop. Real time applications i.e., VoIP and streaming video can be adversely affected by such kind of delays. In this study we used TCP and UDP as an underlying protocol for exchange of data between two wireless mobile nodes in a WiMax access network and had evaluated the effect on performance in terms of end-to-end delay and throughput. The results showed that when handover is triggered the transfer window resets to zero causing higher throughput and end-to-end delay for TCP than UDP based on packet size and traffic load.

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In mobile ad hoc networks (MANETs), mobile devices connect with other devices wirelessly, where there is no central administration. They are prone to different types of attacks such as the black hole, insider, gray hole, wormhole, faulty node, and packet drop, which considerably interrupt to perform secure communication. This paper has implemented the denial-of-service attacks like black hole attacks on general-purpose ad hoc on-demand distance vector (AODV) protocol. It uses three approaches: normal AODV, black hole AODV (BH_AODV), and detected black hole AODV (D_BH_AODV), wherein we observe that black holes acutely degrade the performance of networks. We have detected the black hole attacks within the networks using two techniques: (1) intrusion detection system (IDS) and (2) encryption technique (digital signature) with the concept of prevention. Moreover, normal AODV, BH_AODV, and D_BH_AODV protocols are investigated for various quality of service (QoS) parameters, i.e., packet delivery ratio (PDR), delay, and overhead with varying the number of nodes, packet sizes, and simulation times. The NS2 software has been used as a simulation tool to simulate existing network topologies, but it does not contain any mechanism to simulate malicious protocols by itself; therefore, we have developed and implemented a D_BH_AODV routing protocol. The outcomes show that the proposed D_BH_AODV approach for the PDR value delivers around 40 to 50% for varying nodes and packets. In contrast, the delay decreases from 300 to 100 ms and 150 to 50 ms with an increase in the number of nodes and packets, respectively. Furthermore, the overhead changes from 1 to 3 for various nodes and packet values. The outcome of this research proves that the black hole attack degrades the overall performance of the network, while the D_BH_AODV enhances the QoS performance since it detects the black hole nodes and avoids them to establish the communication between nodes.