Adopting MQTT for a multi protocols IoMT system

<span>Coronavirus disease (COVID-19) altered the way of caregiving and the new pandemic forced the health systems to adopt new treatment protocols in which remote follow-up is essential. This paper introduces a proposed system to link a remote healthcare unit as it is inside the hospital. Two different network protocols; a global system for mobile communication (GSM) and Wi-Fi were used to simulate the heath data transfer from the two different geographical locations, using Raspberry Pi development board and Microcontroller units. Message queuing telemetry transport (MQTT) protocol was employed to transfer the measured data from the healthcare unit to the hospital’s Gateway. The gateway is used to route the aggregated health data from healthcare units to the hospital server, doctors’ dashboards, and the further processing. The system was successfully implemented and tested, where the experimental tests show that the remote healthcare units using a GSM network consumed about 900 mWh. A high percentage of success data packets transfer was recorded within the network framework as it reaches 99.89% with an average round trip time (RTT) of 7.5 milliseconds and a data transfer rate up to 12.3 kbps.</span>

The Delay Measurement and Analysis of Unreachable Hosts of Internet

Delay related metrics are significant quality of service criteria for the performance evaluation of networks. Almost all delay related measurement and analysis studies take into consideration the reachable sources of Internet. However, unreachable sources might also shed light upon some problems such as worm propagation. In this study, we carry out a delay measurement study of unreachable destinations and analyse the delay dynamics of unreachable nodes. 2. Internet Control Message Protocol (ICMP) destination unreachable Internet Control Message Protocol-Destination Unreachable (ICMP T3) packets are considered for the delay measurement according to their code types which shows network un reach ability, host un reach ability, port un reach ability, etc. Measurement results show that unreachable sources exhibit totally different delay behaviour compared to reachable IP hosts. A significant part of the unreachable hosts experiences extra 3 seconds Round Trip Time (RTT) delay compared to accessible hosts mostly due to host un reach ability. It is also seen that, approximately 79% of destination un reach ability causes from host un reach ability. Obtained Hurst parameter estimation results reveal that unreachable host RTTs show lower Hurst degree compared to reachable hosts which is approximately a random behaviour. Unreachable sources exhibit totally different distributional characteristic compared to accessible ones which is best fitted with Phased Bi-Exponential distribution.

Round Trip Time of Network Cables: A Comparative Analysis

This experimental research study was conducted to compare the round-trip time of commonly used network cables among Internet Cafés in Estancia, Iloilo. Specifically, it focused on the brand names of network cable and the distance of cable from the access point to remote terminal. This study attempted to determine whether there was no significant difference among cables which differs from their brand names and distances. The research instrument used in gathering the data was the researchers-made survey form which was submitted to the three panels of experts for face validation before the instrument was given to Internet Cafe Owner’s and computer stores in the Municipality of Estancia. The statistical tools used were the frequency counts, percentages, rank, arithmetic mean, and chi-square. The results revealed that there were significant differences in the round-trip time between brands of network cables when tested at long and short distances from access point to remote terminal. It was found out that there was no significant difference in the overall round-trip time between brands of network cables when tested at long, medium, and short distances from access point to remote terminal. This simply showed that Internet Cafés can make use of any brand available in the market because they perform the same. However, among the three brands being tested it was also revealed that the best brand of network cables in terms of round-trip time was the Belden.

An XGB-Based Reliable Transmission Method in the mMTC Scenarios

Massive machine-type communications (mMTCs) for Internet of things are being developed thanks to the fifth-generation (5G) wireless systems. Narrowband Internet of things (NB-IoT) is an important communication technology for machine-type communications. It supports many different protocols for communication. The reliability and performance of application layer communication protocols are greatly affected by the retransmission time-out (RTO) algorithm. In order to improve the reliability and performance of machine-type communications, this study proposes a novel RTO algorithm UDP-XGB based on the user datagram protocol (UDP) and NB-IoT. It combines traditional algorithms with machine learning. The simulation results show that real round-trip time (RTT) is close to the RTO, which is obtained by this algorithm, and the reliability and performance of machine-type communications have improved.

A Survey of Recent Indoor Localization Scenarios and Methodologies

Recently, various novel scenarios have been studied for indoor localization. The trilateration is known as a classic theoretical model of geometric-based indoor localization, with uniform RSSI data that can be transferred directly into distance ranges. Then, a trilateration solution can be algebraically acquired from theses ranges, in order to fix user’s actual location. However, the collected RSSI or other measurement data should be further processed and classified to lower the localization error rate, instead of using the raw data influenced by multi-path effect, multiple nonlinear interference and noises. In this survey, a large number of existing techniques are presented for different indoor network structures and channel conditions, divided as LOS (light-of-sight) and NLOS (non light-of-sight). Besides, the input measurement data such as RSSI (received signal strength indication), TDOA (time difference of arrival), DOA (distance of arrival), and RTT (round trip time) are studied towards different application scenarios. The key localization techniques like RSSI-based fingerprinting technique are presented using supervised machine learning methods, namely SVM (support vector machine), KNN (K nearest neighbors) and NN (neural network) methods, especially in an offline training phase. Other unsupervised methods as isolation forest, k-means, and expectation maximization methods are utilized to further improve the localization accuracy in online testing phase. For Bayesian filtering methods, apart from the basic linear Kalman filter (LKF) methods, nonlinear stochastic filters such as extended KF, cubature KF, unscented KF and particle filters are introduced. These nonlinear methods are more suitable for dynamic localization models. In addition to the localization accuracy, the other important performance features and evaluation aspects are presented in our paper: scalability, stability, reliability, and the complexity of proposed algorithms is compared in this survey. Our paper provides a comprehensive perspective to compare the existing techniques and related practical localization models, with the aim of improving localization accuracy and reducing the complexity of the system.

Using machine learning to find the hidden relationship between RTT and TCP throughput in WiFi

Is it possible to find hidden relationships among variables in WiFi network using machine learning (ML)? Can we use ML to find a variable that significantly affects the TCP throughput in WiFi? In this work, we employ a publicly available WiFi dataset to investigate these questions. We use ML techniques, including principal component analysis (PCA), linear regression (LR), and random forest (RF), to study the effect of link speed, received signal strength, round-trip time (RTT), and number of available access points on TCP throughput in WiFi. More specifically, we are interested in employing ML to find the variable that most accurately predicts and thereby most significantly affects the throughput. Simple correlation analysis indicates that a combination of multiple variables is more likely to act as a reasonable predictor of the throughput, whereas a single variable, such as RTT, alone is not likely to predict the throughput with reasonable accuracy. From PCA, the first principal component (PC1) is seen as highly correlated to RTT. During predictive analysis, it is observed that the LR model is unable to find any hidden relationship between throughput and other variables. However, the RF model discovers that RTT explains the variation in throughput more closely and as such it predicts the throughput more accurately compared to other variables. PC1 captures nearly all of the variation in throughput with the RF model and predicts throughput with very high accuracy, which indirectly confirms RTT as the variable that most significantly affects the TCP throughput in WiFi. Consequently, we discover a very close relationship between RTT and TCP throughput using appropriate ML techniques, and these results can be helpful in developing a better understanding of the relationship between latency and throughput for designing future low-latency networks.

Formation Control of Dual Auto Guided Vehicles Based on Compensation Method in 5G Networks

With commercial application of 5G networks, many researchers have started paying attention to real-time control in 5G networks. This paper focuses on dual auto guided vehicles collaborative transport scenarios and designs a formation control system in current commercial 5G networks. Firstly, the structure of the 5G network researched in this paper is introduced. Then the round-trip time of 5G networks is measured and analyzed. The result shows that although the 5G round-trip time has randomness, it is mainly concentrated in 19 ± 3 ms, and the jitter mainly in 0 ± 3 ms. The Kalman filter is applied to estimate the transmission delay and experiment result shows the effectiveness of the estimation. Furthermore, the total delay including transmission delay and execution delay in control system is discussed. After establishing the AGV kinematic and formation model, complete control system based on compensation method is proposed. Finally, an experiment is carried out. Compared to the result without formation control, maximum distance error is reduced by 82.61% on average, while maximum angle error 45.91% on average. The result shows the effectiveness of the control system in formation maintaining in 5G network.

Implementation of MQTT Protocol in Health Care Based on IoT Systems: A Study

Internet of things IoT systems have become one of the most promising technologies in all fields. Data transmission is one of the important aspects, and the tendency to messaging protocols is an important aspect of IoT systems. One of these most important protocols is MQTT. This protocol depends on the Publish/Subscribe model, and it is a lightweight protocol. Reliability, simplicity, quality of service levels, and being Resource-constrained make MQTT common in the IoT industry. This paper designed an IoT device that consists of the sensor MLX 90614 non-contact IR Temperature connected to a development board (Node MCU ESP8266). A person's temperature is one of the important vital signs. This system measures human temperature values and transmits the measured values to the Mosquitto broker by using the MQTT protocol in real-time. The technology used is Wi-Fi. The person or the doctor can read the patient’s temperature remotely through a program (Flutter Android Client) representing the subscriber. Also, MQTT protocol control packets of the system were analyzed using Wireshark. The three levels of QoS were used in subscriber clients to compare the throughput. The results indicate that QoS2 is more reliable and offers more throughput but more delay. The results also show that the average round trip time (RTT) of the MQTT protocol is five milliseconds which means optimal performance for IoT applications.

Applying MMD Data Mining to Match Network Traffic for Stepping-Stone Intrusion Detection

A long interactive TCP connection chain has been widely used by attackers to launch their attacks and thus avoid detection. The longer a connection chain, the higher the probability the chain is exploited by attackers. Round-trip Time (RTT) can represent the length of a connection chain. In order to obtain the RTTs from the sniffed Send and Echo packets in a connection chain, matching the Sends and Echoes is required. In this paper, we first model a network traffic as the collection of RTTs and present the rationale of using the RTTs of a connection chain to represent the length of the chain. Second, we propose applying MMD data mining algorithm to match TCP Send and Echo packets collected from a connection. We found that the MMD data mining packet-matching algorithm outperforms all the existing packet-matching algorithms in terms of packet-matching rate including sequence number-based algorithm, Yang’s approach, Step-function, Packet-matching conservative algorithm and packet-matching greedy algorithm. The experimental results from our local area networks showed that the packet-matching accuracy of the MMD algorithm is 100%. The average packet-matching rate of the MMD algorithm obtained from the experiments conducted under the Internet context can reach around 94%. The MMD data mining packet-matching algorithm can fix the issue of low packet-matching rate faced by all the existing packet-matching algorithms including the state-of-the-art algorithm. It is applicable to network-based stepping-stone intrusion detection.