Presenting a Reliable Routing Approach in IoT Healthcare Using the Multiobjective-Based Multiagent Approach

Developments in information and related technologies have led to a wider use of the Internet of things (IoT). By integrating both virtual and physical worlds, IoT creates an integrated communication framework of interrelated things and operating systems. With the advent of IoT systems based on digital remote care, transferring medical data is becoming a daily routine. Healthcare is one of the most popular IoT applications and tries to monitor patients’ vital signs during the day for weeks and to eliminate the need for hospitalization. In a healthcare system, many sensors are installed to collect the patient’s information, including environmental monitoring sensors and vital and unstructured message sensors in order to reduce the patients’ expenses. The IoT network contains flexible sensors in dynamically changing environments where sensors collect environmental information and send it to nursing stations for healthcare applications. Due to the wireless nature of IoT networks, secure data transmission in the healthcare context is very important. Data collected from sensors embedded in healthcare devices may be lost for various reasons along the transmission path. Therefore, establishing a secure communication path in IoT networks in the context of healthcare is of great importance. In this paper, in order to provide a reliable data transfer protocol in the context of healthcare, a reliable routing using multiobjective genetic algorithm (RRMOGA) method is presented. The contribution of this paper can be summarized in two steps: (i) using a multiobjective optimization approach to find near-optimal paths and (ii) using reliable agents in the network to find backup paths. The simulation outcomes reveal that the proposed approach, based on the use of the multiobjective optimization approach, tries to find optimal paths for information transfer that improve the main parameters of the network. Also, the use of secure agents leads to a secure information transfer in the network in the context of healthcare. Experimental results show that the proposed method has achieved reliability and data delivery rates, 99% and 99.9%, respectively. The proposed method has improved network lifetime, delivery rate, and delay by 14%, 2%, and 5.6%, respectively.

A Hybrid Reliable Routing Algorithm Based on LQI and PRR in Industrial Wireless Networks

In Industrial Wireless Networks (IWNs), the communication through Machine-to-Machine (M2M) is often affected by the noise in the industrial environment, which leads to the decline of communication reliability. In this paper, we investigate how to improve route stability through M2M in an industrial environment. We first compare different link quality estimations, such as Signal-Noise Ratio (SNR), Received Signal Strength Indicator (RSSI), Link Quality Indicator (LQI), Packet Reception Ratio (PRR), and Expected Transmission Count (ETX). We then propose a link quality estimation combining LQI and PRR. Finally, we propose a Hybrid Link Quality Estimation-Based Reliable Routing (HLQEBRR) algorithm for IWNs, with the object of maximizing link stability. In addition, HLQEBRR provides a recovery mechanism to detect node failure, which improves the speed and accuracy of node recovery. OMNeT++-based simulation results demonstrate that our HLQEBRR algorithm significantly outperforms the Collection Tree Protocol (CTP) algorithm in terms of end-to-end transmission delay and packet loss ratio, and the HLQEBRR algorithm achieves higher reliability at a small additional cost.

Highly Reliable Routing In Healthcare Systems Based on Internet of Things

Healthcare is an important application of Internet of things (IoT) and body sensor networks (BSNs). Known as a method of measuring and collecting data in healthcare applications, a BSN must provide more reliable routing. Therefore, it is necessary to develop a method for reducing communication rates and improving reliability in healthcare systems. This paper proposes a novel method for routing data packets to enhance reliability in IoT-based healthcare systems. Given the nature of healthcare systems and importance of energy consumption, the proposed method employs different criteria (residual energy and variance of distance from neighbours) to perform the routing process. The results of implementing the proposed method indicated its acceptable performance in comparison with LSR, OLSR, and MAEB protocols. The method also managed to achieve the goals of retaining the quality of packets received by the sink and reducing energy consumption in healthcare systems.