scholarly journals Machine-to-Machine Communication for Device Identification and Classification in Secure Telerobotics Surgery

2021 ◽  
Vol 2021 ◽  
pp. 1-16
Author(s):  
Meghana P. Lokhande ◽  
Dipti Durgesh Patil ◽  
Lalit V. Patil ◽  
Mohammad Shabaz
Keyword(s):  
Smart Devices ◽  
Primary Concern ◽  
Transportation Industry ◽  
Major Purpose ◽  
Machine To Machine ◽  
Device Identification ◽  
Telerobotic Surgery ◽  
Machine To Machine Communication ◽  
Iot Devices ◽  
Machine Communication

The capacity of machine objects to communicate autonomously is seen as the future of the Internet of Things (IoT), but machine-to-machine communication (M2M) is also gaining traction. In everyday life, security, transportation, industry, and healthcare all employ this paradigm. Smart devices have the ability to detect, handle, store, and analyze data, resulting in major network issues such as security and reliability. There are numerous vulnerabilities linked with IoT devices, according to security experts. Prior to performing any activities, it is necessary to identify and classify the device. Device identification and classification in M2M for secure telerobotic surgery are presented in this study. Telerobotics is an important aspect of the telemedicine industry. The major purpose is to provide remote medical care, which eliminates the requirement for both doctors and patients to be in the same location. This paper aims to propose a security and energy-efficient protocol for telerobotic surgeries, which is the primary concern at present. For secure telerobotic surgery, the author presents an Efficient Device type Detection and Classification (EDDC) protocol for device identification and classification in M2M communication. The periodic trust score is calculated using three factors from each sensor node. It demonstrates that the EDDC protocol is more effective and secure in detecting and categorizing rogue devices.

On Multiple Access of a Large Number of Machine-Type Devices in Cellular Networks

2018 ◽  
pp. 105-114
Author(s):  
O. S. Galinina ◽  
S. D. Andreev ◽  
A. M. Tyurlikov
Keyword(s):  
Success Probability ◽  
Random Access ◽  
Time Interval ◽  
Short Time Interval ◽  
Control Mechanisms ◽  
Network Access ◽  
Smart Meters ◽  
Machine To Machine ◽  
Machine To Machine Communication ◽  
Machine Communication

Introduction: Machine-to-machine communication assumes data transmission from various wireless devices and attracts attention of cellular operators. In this regard, it is crucial to recognize and control overload situations when a large number of such devices access the network over a short time interval.Purpose:Analysis of the radio network overload at the initial network entry stage in a machine-to-machine communication system.Results: A system is considered that features multiple smart meters, which may report alarms and autonomously collect energy consumption information. An analytical approach is proposed to study the operation of a large number of devices in such a system as well as model the settings of the random-access protocol in a cellular network and overload control mechanisms with respect to the access success probability, network access latency, and device power consumption. A comparison between the obtained analytical results and simulation data is also offered. 

scholarly journals Accommodating Machine-To-Machine Traffic In IEEE 802.15.4: The Prioritized Wait Time Approach

2021 ◽  
Author(s):  
Vida Azimi
Keyword(s):  
Ieee 802.15.4 ◽  
Wait Time ◽  
Smart Devices ◽  
Personal Area Networks ◽  
Wireless Personal Area Networks ◽  
Machine To Machine ◽  
M2m Communications ◽  
Distribution Logistics ◽  
Machine Communication ◽  
Transmission And Distribution

Machine-to-Machine communication (M2M) refers to automated applications executing on smart devices or machines that communicate through a network with little or no human intervention at all. By enabling smart devices to communicate directly with one another, M2M communications technology has the potential to radically change the world around us and the way that we interact with objects. Many applications can benefit from M2M communications, such as transportation, health care, smart energy production, transmission, and distribution, logistics, city automation and manufacturing, security and safety, and others. This work describes an approach to implement M2M communications using the well-known IEEE 802.15.4 / ZigBee communications standard for low data rate wireless personal area networks. In order to achieve better performance for M2M traffic, we propose some improvements in the protocol. Our simulation results confirm the validity

scholarly journals Energy Versus Throughput Optimisation for Machine-to-Machine Communication

Sensors ◽  
2020 ◽  
Vol 20 (15) ◽  
pp. 4122
Author(s):  
Emma Fitzgerald ◽  
Michał Pióro ◽  
Artur Tomaszewski
Keyword(s):  
Mesh Networks ◽  
Numerical Study ◽  
Minimum Energy ◽  
Mixed Integer ◽  
Energy Usage ◽  
Maximum Throughput ◽  
Machine To Machine ◽  
Machine To Machine Communication ◽  
Optimisation Model ◽  
Machine Communication

We investigate the trade-off between energy usage and (packet) throughput in wireless mesh networks performing machine-to-machine communication. For this we provide a novel mixed-integer programming formulation to maximise the throughput while maintaining minimal energy usage, together with an effective price-and-branch solution algorithm based on column generation. The resulting optimisation model is the main original contribution of the presented paper. We conducted a numerical study using network examples from 10 to 40 nodes, in which periodic sensor measurements are aggregated and disseminated to actuators. In almost all cases, we were able to achieve maximum throughput and minimum energy usage simultaneously, and in those cases where this was not possible, the costs incurred in one objective in order to achieve the other were typically low. The solution times for all network sizes were of the order of seconds, showing that our optimisation model is feasible to use in practice.

Sign in / Sign up

Export Citation Format

Share Document