In order to increase the reliability, accuracy, and efficiency in the eHealth, Internet of Medical Things is playing a vital role. Current development in telemedicine and the Internet of Things have delivered efficient and low-cost medical devices. The Internet of Medical Things architectures being developed do not completely recognize the potential of Internet of Things. The Internet of Medical Things sensor devices have limited computation power; in case if a patient is using implanted medical devices, it is not easy to recharge or replace the devices immediately. Biosensors are small devices with limited energy if these devices do not wisely utilize the energy may drain sharply and devices become inactive. The current medical solutions place the bulk of data on cloud-based systems that ultimately creates a bottleneck. In this article, an energy-efficient fog-to-cloud Internet of Medical Things architecture is proposed to optimize energy consumption. In the proposed architecture, Bluetooth enabled biosensors are used, because Bluetooth technology is an energy efficient and also helps to enable the sleep and awake modes. The proposed fog-to-cloud Internet of Medical Things works in three different modes periodic, sleep–awake, and continue to optimize the energy consumption. The proposed technique enabled the sensing modes that gathers the patients’ data efficiently based on their health conditions. The sensed data are transmitted to the relevant fog and cloud devices for further processing. The performance of fog-to-cloud Internet of Medical Things is evaluated through simulation; the results are compared with the results of existing techniques in terms of an end-to-end delay, throughput, and energy consumption. It is analyzed that the proposed technique reduces the energy consumption between 30% and 40%.

The mounting use of wireless devices and wide range applications in an ultra-dense heterogeneous wireless network has directed to the challenging circumstances that could not be handled till 4G. In order to deal with the critical challenges, the fifth generation (5G) wireless network architecture requires an efficient well-organized wireless network. In this paper, a novel architecture for the 5G ultra-dense heterogeneous cellular network is proposed. In the proposed architecture two main aspects, massive MIMO-OFDMA and IP-based vertical handover are considered. In order to have full network coverage, the whole macro area network is divided into the microcells and each microcell is further divided into the smaller cells. The heterogeneity of different types of base stations (macro area network base station, micro-cell base station, and small cell base station) provides efficient network coverage. By reducing the area of the cell, the frequency efficiency and network coverage are improved. All the base stations are equipped with the massive MIMO-OFDMA antennas and different radio access technologies so a single wireless device can switch from one radio access technology to the other. In order to prevent the link disconnection and save IP address, whenever wireless devices need to perform vertical handover first a new connection is established with new radio access technology. It is important to note the same IP address is used whereas the current connection is disconnected. By utilizing IP-based vertical handover, the new 5G wireless network can become the principal goal of service continuity and minimize the handover processing delay. The simulation results show the improvement in the network performance.

Internet of things (IoT) is a complex and massive wireless network, where millions of devices are connected together. These devices gather different types of data from different systems that transform human daily lives by modernizing home appliances, business, medicine, traveling, research, and so on. Security is a critical challenge for a stable IoT network, for instance, routing attacks, especially sinkhole attack is a severe attack which has the capability to direct network data toward the intruder, and it can also disrupt and disconnect the devices from their network. The IoT needs multi-facet security solutions where network communication is protected with integrity, confidentiality, and authentication verification services. Therefore, the IoT network should be secured against intrusions and disruptions; the data exchanged throughout the network should be an encrypted form. In this article, an intrusion detection system for the prevention of an active sinkhole routing attack (PASR) in IoT is presented. The proposed PASR solves the problem of the sinkhole attack; for this purpose, the whole network is divided into the clusters of IoT. All the IoT devices are connected to their respective gateways. The gateway devices are equipped with an intrusion detection system. The intrusion detection system activates intrusion analyzer to detect anomalies in the context of ad hoc on-demand distance vector protocol. The base station is the main device that is responsible to receive data from all devices. Therefore, it detects and prevents sinkhole attacks; the base station keeps the record of all active devices and their possible links. The PASR is implemented and compared with the existing intrusion detection techniques ad hoc on-demand distance vector, and dual attack detection for black and gray hole attack. It was observed from the simulation results that the PASR outperforms in terms of data packet delivery, energy consumption, the detection rate of sinkhole attack, and routing overhead.

The current enhancement and technical development in radio communication have enabled the efficient, low power, intelligent, and wearable microsensor. These microsensors are tactically embedded in or located outside the human body in a fixed position, which is called Body Area Network (WBAN). Therefore, the key objective of this research work is to discover the current gaps in providing an improved service of WBAN. The paper presents a Fog-based Healthcare Architecture for Wearable Body Area Network (FHA). The fog based architecture is used for real-time patient monitoring and analysis of patients' health condition irrespective of location and time by using an integrated low-power and low-cost WBAN and fog computing. In order to diagnose and monitor the patient's health conditions, mobile wearable sensors are used to gather the patients' real-time data via ZigBee links and forward to the Tele-Lab Server (TLS). Where a Laboratory Information Database (LIDB) module resides that buffer and analyzes the data. The LIDB sends the whole information of all registered patients to the cloud server as a backup. When TLS frequently sends data to the fog server, it creates congestion, the proposed technique avoids the congestion on fog server. When FHA predicts the critical result of any patient, it immediately forwards the data to the fog server for emergency alert and updates the cloud server. From the simulation results, it is observed that the proposed FHA efficiently handle the current issues and increasing throughput, decreasing packet loss, and delay.