The breakdown of vital communication infrastructures is one of the most common characteristics of all disasters. It can cause severe communication problems such as time delays and data loss, which cause deterioration in system performance. New techniques are needed to cope with such situations, many of which have been made possible due to the ongoing evolution of artificial intelligence technologies. In this study, we consider the case of a network consisting of several router allocation problems in situations of high priority and emergency data allocation. A novel network component called the scheduler is introduced and window constraints for routers are imposed. To solve the studied problem, four different algorithms are developed in this work. These algorithms were then applied in a particular scenario consisting of several routers and 2200 instances. In terms of the gap and running time, the proposed algorithms provide acceptable results. The best performances were achieved using the critical packet algorithm for 80% of instances with an average gap value of 0.009 and an average time of 0.209 s. 

A Novel Model Based on Window-Pass Preferences for Data Emergency Aware Scheduling in Computer Networks

Internet of things (IoT) will be the main part in upcoming generation devices that would not simply sense and report, also will have the controlling capability. It may be a connected vehicle, connected devices, robot, a building automation system, a door lock or a thermostat, these connected machines or devices will provide greater impact on our daily lives. Control data and the operating instructions could be protected to ensure control and autonomy for our safety and security, this could be a critical task. Privacy and security are important consideration in designing the system. With the intense growth of devices or devices with facilities such as computing and communication are carried out using a profound technology known as machine to machine (M2M) communication, which is specially designed for cross‐platform integration. In many industries, smart homes, smart cities, smart agriculture, government, connected devices, security, healthcare, education, public safety, and supply chain management. Internet of things (IoT) and machine to machine communication have to be implemented in near future. Also, this paper gives an in depth view about the different M2M techniques with interconnected IoT for truly connected, smart, and sustainable world.

/pdf/machine-to-machine-communication-enabled-internet-of-things-25rwwcoq.pdf

Machine to machine communication enabled internet of things: a review

The breakdown of vital communication infrastructures is one of the most common characteristics of all disasters. It can cause severe communication problems such as time delays and data loss, which cause deterioration in system performance. New techniques are needed to cope with such situations, many of which have been made possible due to the ongoing evolution of artificial intelligence technologies. In this study, we consider the case of a network consisting of several router allocation problems in situations of high priority and emergency data allocation. A novel network component called the scheduler is introduced and window constraints for routers are imposed. To solve the studied problem, four different algorithms are developed in this work. These algorithms were then applied in a particular scenario consisting of several routers and 2200 instances. In terms of the gap and running time, the proposed algorithms provide acceptable results. The best performances were achieved using the critical packet algorithm for 80% of instances with an average gap value of 0.009 and an average time of 0.209 s.

Human evolution has included the development of transportation systems. People are currently driving a significant number of fuel-powered automobiles. This resulted in an increase in the number of accidents as well as pollution in the environment. To address the disadvantages of gasolinebased vehicles, this study presents an IoT-based E-vehicle monitoring system (E-VMS) for early accident detection and to make the environment cleaner and greener by using alternative energy. E-VMS employs internet of things (IoT) technology to continuously monitor the vehicle as well as to access and control it remotely. The IoT devices installed in vehicles are built using an Arduino microcontroller and sensors to detect accidents quickly. When an accident occurs, the E-VMS recognizes it quickly and determines the severity of the incident. The machine will then promptly alert the authorities. The E-VMS is also familiar with the GPS system. This will allow the E-VMS to maintain track of the cars' location in real time. This information will be used to locate the car in the event of an accident or theft. The E-VMS system's results were promising in terms of accurately identifying accidents, determining the severity of the accident, and determining the position of the vehicle.

IoT based E-vehicle monitoring system using sensors and imaging processing algorithm

A significant shift towards autonomous and connected cars is currently expected in the automotive sector. This creates new risks in terms of privacy and the complexity of electrical and electronic systems. Although safety risk management is still in its infancy, it is encouraging that the auto industry has well-known and regulated safety risk management practices. They propose a showed improved risk assessment framework and show its validity with an actual use-case to make it easier to derive safety procedures & safety solutions for automotive integrated devices. The adequacy of functional safety to existing methods and accessibility for non-safety professionals are some of the important aspects. Risk analysis is an essential element of the methodology used to assess properties and capacity risks. The level of hazard and the level of effect are estimated in the next stage of the risk management process. This step uses several existing guidelines and requirements to make amendments as necessary. To create high-level security objectives, a level of security has finally been determined. This architecture should be well adapted to the requirements of the automobile industry due to its excellent convergence with current principles and specifications.

A Safety Assessment Model for Automotive Embedded Systems Networks

The use of a real-time operating system is required for the demarcation of industrial wireless sensor network (IWSN) stacks (RTOS). In the industrial world, a vast number of sensors are utilised to gather various types of data. The data gathered by the sensors cannot be prioritised ahead of time. Because all of the information is equally essential. As a result, a protocol stack is employed to guarantee that data is acquired and processed fairly. In IWSN, the protocol stack is implemented using RTOS. The data collected from IWSN sensor nodes is processed using non-preemptive scheduling and the protocol stack, and then sent in parallel to the IWSN's central controller. The real-time operating system (RTOS) is a process that occurs between hardware and software. Packets must be sent at a certain time. It's possible that some packets may collide during transmission. We're going to undertake this project to get around this collision. As a prototype, this project is divided into two parts. The first uses RTOS and the LPC2148 as a master node, while the second serves as a standard data collection node to which sensors are attached. Any controller may be used in the second part, depending on the situation. Wireless HART allows two nodes to communicate with each other.

Wireless HART stack using multiprocessor technique with laxity algorithm

The advent of the automated technological revolution has enabled the Internet of Things to rejuvenate, revolutionize, and redeem the services of sensors. The recent development of microsensor devices is distributed in a real-world terrestrial environment to sense various environmental changes. The energy consumption of the remotely deployed microsystems depends on its utilization efficiency. Improper utilization of sensor nodes’ heterogeneity could lead to uneven energy consumption and load imbalance across the network, which will degrade the performance of the network. The proposed heterogeneous energy and traffic aware (HETA) considers the key parameters such as delay, throughput, traffic load, energy consumption, and life span. The residual energy and a minimum distance between the base station and cluster members are taken into consideration for the cluster head selection. The probability of hitting data traffic has been utilized to analyse energy and traffic towards the base station. The role of the sensor node has been realized and priority-based data forwarding are also proposed. As a result, the heterogeneous energy and traffic aware perform well in balancing traffic towards the base station, which is analysed in terms of maximum throughput and increase in a lifetime of heterogeneous energy networks more than 5000 rounds, and the algorithm outperforms 34.5% of nodes are alive with transmissible energy. The proposed research also endorses unequal clustering and minimum energy consumption. We have modeled our proposed research using various p-type junctionless nanowire FET without doping injunctions. The materials used in this analysis were silicon (Si), germanium (Ge), indium phosphide (InP), gallium arsenide (GaAs), and Al(x)Ga(1−x)As. The dimensions of the p-type cylindrical nanowire channel were 25 nm long and 10 nm in diameter.

/pdf/effects-of-novel-material-field-effect-transistor-for-23ivgdddpr.pdf

Effects of Novel Material Field Effect Transistor for Heterogeneous Energy and Traffic-Aware Secure Applications

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Wireless HART stack using multiprocessor technique with laxity algorithm

Effects of Novel Material Field Effect Transistor for Heterogeneous Energy and Traffic-Aware Secure Applications