The Impact of Healthcare Traffic Over H2H and M2M Networks During the Spread Phase of Pandemic Diseases

Recently, the coronavirus pandemic has caused widespread panic around the world. Modern technologies can be used to monitor and control this highly contagious disease. A plausible solution is to equip each patient who is diagnosed with or suspected of having COVID-19 with sensors that can monitor various healthcare and location parameters and report them to the desired facility to control the spread of the disease. However, the simultaneous communication of numerous sensors installed in the majority of an area’s population results in a huge burden on existing Long-Term Evolution (LTE) networks. The existing network becomes oversaturated because it has to manage two kinds of traffic in addition to normal traffic (text, voice, and video): healthcare traffic generated by a large number of sensors deployed over a huge population, and extra traffic generated by people contacting their family members via video or voice calls. In pandemics, e-healthcare traffic is critical and should not suffer packet loss or latency due to network overload. In this research, we studied the performance of existing networks under various conditions and predicted the severity of network degradation in an emergency. We proposed and evaluated three schemes (doubling bandwidth, combining LTE-A and LTE-M networks, and request queuing) for ensuring quality of service (QoS) of healthcare sensor (HCS) network traffic without perturbation from routine human-to-human or machine-to-machine communications. Finally, we simulated all proposed schemes and compared them with existing network scenarios. The results have showed that when we have doubled the bandwidth the SCR of all traffic was 100% as same as the Queue strategy. However, when we prioritized the HCS traffic the SCR has recorded 100%, while H2H and M2M traffic has recorded 73%. When we used hybrid network LTE-A and LTE-M network, the HCS and H2H traffic has recorded 100% and M2M traffic has recorded 70%. After analyzing the results, we conclude that our proposed queuing schemes performed well in all conditions and provide the best QoS for HCS traffic.

A Machine Learning Approach to Interpolating Indoors Trajectories

In this article we propose a machine learning-based modeling to solve network overload problems caused by continuous monitoring of the trajectories of multiple tracked devices indoors. The proposed modeling was evaluated with hundreds of object coordinate locations tracked in three synthetic environments and one real environment. We show that it is possible to solve the problem of network overload increasing latency in sending data and predicting as server-side trajectories with ensemble models, such as the Random Forest, and using Artificial Neural Networks. We also show that it is possible to predict at least fifteen intermediate coordinates of the paths of the tracked objects with R2 greater than 0.95.

Reliability Analysis of Communication Network Service Quality For Internet of Vehicles (IoV)

The development of the Internet of Vehicle (IoV) is overgrowing toward driving comfort, safety, and efficiency. Autopilot or a car without a driver is one implementation of IoT. To run the full function of IoV, a reliable communication network is needed because the risk will be substantial due to the low quality of network infrastructure services. In this research, we will analyze the quality of network infrastructure services. The analysis can be done through two approaches: direct measurement in the field using a GPS Tracker-based system and modeling using the mathematical function of transmit power of mobile communication transmitting devices. The test is carried out in a specific area with a sample of high traffic and low-density areas. This method was chosen to find the right pattern in measuring the quality of communication network services. The tests carried out produce dynamic data on service quality in certain areas. For areas of low density, the service quality tends to be below as well, and many areas without signal are found, while for areas with high density, the quality of service is found to be good, but network overload conditions often occur.

DEFENSE STRATEGY AGAINST SELFISH NODES TAKING INTO ACCOUNT TRAFFIC DIFFERENTIATION IN VEHICULAR DELAY-TOLERANT NETWORKS

Vehicular Delay-Tolerant Networks (VDTNs) are vehicle networks where there is no end-to-end connectivity between source and destination. As a result, VDTNs rely on cooperation between the different nodes to improve its performance. However, the presence of selfish nodes that refuse to participate in the routing protocol causes a deterioration of the overall performance of these networks. In order to reduce the impact of these selfish nodes, proposed strategies, on the one hand, use the nodes transmission rate that does not take into account the message priority class of service, and on the other hand, are based on traditional buffer management systems (FIFO, Random). As a result, quality of service is not guaranteed in this type of network where different applications are derived from messages with different priorities. In this paper, we propose a strategy for detecting selfish nodes and taking action against them in relation to priority classes in order to reduce their impacts. The operation of this strategy is based, on a partitioned memory management system taking into account the priority and the lifetime of messages, on the calculation of the transmission rate of the node with respect to the priority class of the node with the highest delivery predictability, on a mechanism for calculating the nodes degree of selfishness with respect to the priority class, and on the monitoring mechanism. . The simulations carried out show that the proposed model can detect selfish nodes and improve network performance in terms of increasing the delivery rate of high-priority messages, reducing the delivery delay of high-priority messages, and reducing network overload.

ASSESSMENT OF THE PERFORMANCE OF A BUFFER MANAGEMENT SYSTEM TO IMPROVE HIGH PRIORITY MESSAGE DELIVERY TIME LIMIT

In vehicular delay-tolerant networks, buffer management systems are developed to improve overall performance. However, these buffer memory management systems cannot simultaneously reduce network overload, reduce high priority message delivery time limit, and improve all priority class message delivery rates. As a result, quality of service is not guaranteed. In this paper, we propose a drop policy based on the constitution of two queues according to message weight, the position of the node in relation to the destination and the comparison of the oldness between the high-priority message and the messages in the low-priority queue. The results of the simulations show that compared to the existing buffer management policy based on time-to-live and priority, our strategy simultaneously reduces network overload, reduces the delivery time limit of high-priority messages and allows for an increase in the delivery rate of messages regardless of their priority.

An orderly charge and discharge control method of considering electric vehicle V2G and photovoltaic complementation in residential area

In order to resolve the problems of distribution network overload and increased peak-valley difference caused by large-scale electric vehicles’ disordered charging, taking the residential community as the research object, an orderly charging method of electric vehicles (EVs) based on power line carrier communication was proposed, and a model of ordered charge and discharge control and load peak regulation considering the complementary of EVs V2G and photovoltaic (PV) was established. It makes full use of the ability of EVs to cut peaks and valleys and restrain the fluctuation of PV output, alleviates the load pressure of the distribution network and reduces the cost of network transformation, which not only brings great benefits to the owners of EVs and power supply operators, but also promotes the consumption of new energy.

Principles of Transformation in an Integrated Energy System when Applying the Concept of an Energy Hub

The cost of electricity and heat for the population, enterprises and organizations in Russia has increased several times in recent years. An urgent issue for consumers was the search for opportunities to save money when paying for energy. The heating fee is about a quarter of the total amount of the utility bill. The tariff, the cost of one unit of energy (Gcal/m2) spent on heating a room, increases annually. Accordingly, the amount of expenses for public services in each individual family or organization also increases. The principles of transformation of various forms of energy in an integrated energy system based on the concept of an energy hub are considered. It is proposed to use the capabilities of the MATLAB/Simulink software. The MATLAB/Simulink software library does not contain complex elements with a structure with multiple inputs and multiple outputs. Complex models of energy hub blocks form a special additional library. These models implement such functions as energy storage, energy conversion and summation of various types of energy. There are two types of energy transformation elements presented in the article. An illustrative example is presented that shows the economic effect of converting electricity into heat energy at preferential tariffs during the night period. The calculation of the quantitative potential of electricity for conversion is performed. Studies have shown that a flexible combination of various energy carriers using conversion and storage technologies preserves the potential for various system improvements: the total cost of energy can be reduced, the reliability of the power system is increased, network overload can be reduced, transmission losses are reduced.

Assessing the Retention Capacity of an Experimental Green Roof Prototype

Cities with high urbanization produce impervious areas. Drainage network overload results in recurring flooding. Much of the damage could be prevented through proper urban planning and good drainage practices. While Low Impact Development techniques have been known for several years, it is essential to encourage the association of this type of technology with conventional micro-drainage structures to increase rainfall runoff at the source where it is generated. Thus, the present work aims to analyze the efficiency of the use of the green roof technique in reducing the peak of the flow and the retention capacity when subjected to heavy rains at the building scale, and also explores its effects in tropical climatic zones with measurements during the summer and fall. The method used was experimental analysis of the Green Roof prototype with bromeliad’s at CESA-UFRJ, whose main results are the hydrogram of each rain event and the runoff coefficient for rainfall in the range of 100 mm/h and 150 mm/h.

Mediation of Lazy Update Propagation in a Replicated Database over a Decentralized P2P Architecture

While replicating data over a decentralized Peer-to- Peer (P2P) network, transactions broadcasting updates arising from different peers run simultaneously so that a destination peer replica can be updated concurrently, that always causes transaction and data conflicts. Moreover, during data migration, connectivity interruption and network overload corrupt running transactions so that destination peers can experience duplicated data or improper data or missing data, hence replicas remain inconsistent. Different methodological approaches have been combined to solve these problems: the audit log technique to capture the changes made to data; the algorithmic method to design and analyse algorithms and the statistical method to analyse the performance of new algorithms and to design prediction models of the execution time based on other parameters. A Graphical User Interface software as prototype, have been designed with C #, to implement these new algorithms to obtain a database synchronizer-mediator. A stream of experiments, showed that the new algorithms were effective. So, the hypothesis according to which “The execution time of replication and reconciliation transactions totally depends on independent factors.” has been confirmed.