Adaptive Relay Selection Scheme for Minimization of the Transmission Time

As the installation of small cells increases,the use of relay also increases.The relay operates as a base station as well as just an amplifier.As the roles and types of relays become more diverse,appropriate relay selection technology is an effective way to improve communication performance.Many researches for relay selection have been studied to secure the reliability of relay communication.In this paper,the relay selection scheme is proposed for a cooperative system using decode-and-forward(DF)relaying scheme in the mobile communication system.To maintain the transmission rate,the proposed scheme classifies a candidate group considering the outage probability of multiple relays.For the applicable candidate group,the proposed scheme selects the relay considering the amount of data allocated to each user.Therefore,the proposed scheme defines the unit transmission time through each user’s data and relay capacity.Finally,the proposed scheme selects a relay that minimizes the total transmission time through the relay transmission time that calculates the unit transmission time for all users.With this adaptive relay selection scheme,an optimal relay can be assigned for each user.For the same transmission rate and the amount of data,the proposed scheme improves the performance of transmission time and reliability.Simulation results show that the proposed scheme reduces the total transmission time for the same amount of data and signal to noise ratio(SNR).

Transmission time in the reflectionless complex potential

A phase time definition directly obtained from the Schr6dinger equation is used to investigate the time delay of a particle scattered by complex reflectionless potential. The artifacts introduced by truncating in the numerical simulation are clarified. The time delay of the transmitted wave packet is found to be equal to the reflection time of the truncated potential. Both time delays are the same as the traversal time in the free space, but shorter than the time taken by a classical particle to pass the same potential.

Real-time performance of periodic data transmission in EPA industrial Ethernet

To evaluate and improve the real-time performance of Ethernet for plant automation（EPA） industrial Ethernet,the real-time performance of EPA periodic data transmission was theoretically and experimentally studied.By analyzing information transmission regularity and EPA deterministic scheduling mechanism,periodic messages were categorized as different modes according to their entering-queue time.The scheduling characteristics and delivery time of each mode and their interacting relations were studied,during which the models of real-time performance of periodic information transmission in EPA system were established.On this basis,an experimental platform is developed to test the delivery time of periodic messages transmission in EPA system.According to the analysis and the experiment,the main factors that limit the real-time performance of EPA periodic data transmission and the improvement methods were proposed.

Reconstruction and transmission of astronomical image based on compressed sensing

In the process of image transmission, the famous JPEG and JPEG-2000 compression methods need more transmission time as it is difficult for them to compress the image with a low compression rate. Recently the compressed sensing（CS） theory was proposed, which has earned great concern as it can compress an image with a low compression rate, meanwhile the original image can be perfectly reconstructed from only a few compressed data. The CS theory is used to transmit the high resolution astronomical image and build the simulation environment where there is communication between the satellite and the Earth. Number experimental results show that the CS theory can effectively reduce the image transmission and reconstruction time. Even with a very low compression rate, it still can recover a higher quality astronomical image than JPEG and JPEG-2000 compression methods.

Improved Harris Hawks Optimization Algorithm Based Data Placement Strategy for Integrated Cloud and Edge Computing

Cloud computing is considered to facilitate a more cost-effective way to deploy scientific workflows.The individual tasks of a scientific work-flow necessitate a diversified number of large states that are spatially located in different datacenters,thereby resulting in huge delays during data transmis-sion.Edge computing minimizes the delays in data transmission and supports the fixed storage strategy for scientific workflow private datasets.Therefore,this fixed storage strategy creates huge amount of bottleneck in its storage capacity.At this juncture,integrating the merits of cloud computing and edge computing during the process of rationalizing the data placement of scientific workflows and optimizing the energy and time incurred in data transmission across different datacentres remains a challenge.In this paper,Adaptive Cooperative Foraging and Dispersed Foraging Strategies-Improved Harris Hawks Optimization Algorithm(ACF-DFS-HHOA)is proposed for optimizing the energy and data transmission time in the event of placing data for a specific scientific workflow.This ACF-DFS-HHOA considered the factors influencing transmission delay and energy consumption of data centers into account during the process of rationalizing the data placement of scientific workflows.The adaptive cooperative and dispersed foraging strategy is included in HHOA to guide the position updates that improve population diversity and effectively prevent the algorithm from being trapped into local optimality points.The experimental results of ACF-DFS-HHOA confirmed its predominance in minimizing energy and data transmission time incurred during workflow execution.

Analysis of SIRVI model with time dependent coefficients and the effect of vaccination on the transmission rate and COVID-19 epidemic waves

COVID-19 epidemic models with constant transmission rate cannot capture the patterns of the infection data in the presence of pharmaceutical and non-pharmaceutical interventions during a pandemic.Because of this,a new modification of SIR model that contain the vaccination compartment with time dependent coefficients and weak/lossimmunity is explored.Literature review confirms that the effect of vaccination on the time dependent transmission rate is still an open problem.This study answers this open problem.In this study,we first prove the well-posedness and investigate the model dynamics to show their continuous dependence on the model parameters.We then provide an algorithm to derive the time-dependent transmission function for the epidemiologic model and the data of the infected cases.The derived coupled nonlinear differential equations show the effect of vaccination on the transmission rate.Unlike previous studies,we first filter the published data and solve the nonlinear coupled differential equations using the finite difference technique,where the coefficient of the coupled nonlinear differential equations is a function of given data.We then show that time-dependent transmission function can be represented by linear combinations of Gaussian radial base function.We then validate the prediction of our models using numerical simulations,where we used the published data of COVID-19 confirmed cases by the Ministries of Health in Saudi Arabia and Poland.Finally,the numerical solutions of a SIRVI model with time dependent transmission rate show that the waves for currently active cases are in good agreement with the data of Saudi Arabia and Poland.

Finite-time non-fragile filtering for nonlinear networked control systems via a mixed time/event-triggered transmission mechanism

This paper is aimed at investigating the problem of mixed time/event-triggered finite-time non-fragile filtering for nonlinear networked control systems with delay.First,a fuzzy nonlinear networked control system model is established by interval type-2(IT2)Takagi-Sugeno(T-S)fuzzy model,the designed non-fragile filter resolves the filter parameter uncertainties and uses different membership functions from the IT2 T-S fuzzy model.Second,a novel mixed time/event-triggered transmission mechanism is proposed,which decreases the waste of network resources.Next,Bernoulli random variables are used to describe the cases of random switching mixed time/event-triggered transmission mechanism.Then,the error filtering system is designed by considering a Lyapunov function and a sufficient condition of finite-time boundedness.In addition,the existence conditions for the finite-time non-fragile filter are given by the linear matrix inequalities(LMIs).Finally,two simulation results are presented to prove the effectiveness of the obtained method.

Analytical model for describing ion guiding through capillaries in insulating polymers

An analytical description for guiding of ions through nanocapillaries is given on the basis of previous work. The current entering into the capillary is assumed to be divided into a current fraction transmitted through the capillary, a current fraction flowing away via the capillary conductivity and a current fraction remaining within the capillary, which is responsible for its charge-up. The discharging current is assumed to be governed by the Frenkel–Poole process. At higher conductivities the analytical model shows a blocking of the ion transmission, which is in agreement with recent simulations.Also, it is shown that ion blocking observed in experiments is well reproduced by the analytical formula. Furthermore, the asymptotic fraction of transmitted ions is determined. Apart from the key controlling parameter(charge-to-energy ratio), the ratio of the capillary conductivity to the incident current is included in the model. Differences resulting from the nonlinear and linear limits of the Frenkel–Poole discharge are pointed out.

SYSTEM RELIABILITY OF ASSURED ACCURACY RATE FOR MULTI-STATE COMPUTER NETWORKS FROM SERVICE LEVEL AGREEMENTS VIEWPOINT

From the viewpoint of service level agreements, the transmission accuracy rate is one of critical performance indicators to assess internet quality for system managers and customers. Under the assumption that each arc＇s capacity is deterministic, the quickest path problem is to find a path sending a specific of data such that the transmission time is minimized. However, in many real-life networks such as computer networks, each arc has stochastic capacity, lead time and accuracy rate. Such a network is named a multi-state computer network. Under both assured accuracy rate and time constraints, we extend the quickest path problem to compute the probability that d units of data can be sent through multiple minimal paths simultaneously. Such a probability named system reliability is a performance indicator to provide to managers for understanding the ability of system and improvement. An efficient algorithm is proposed to evaluate the system reliability in terms of the approach of minimal paths.

Adaptive TTI bundling with self-healing scheme for 5G

The flexibility of the media access control(MAC) layer has always been an important concern in the existing communication architecture. To meet the more stringent requirements under large-scale connections, the MAC layer structure needs to be optimized carefully. This paper proposes a new architecture of the MAC layer to optimize the complex communication backhaul link structure, which will increase the flexibility of the system and decrease the transmission delay. Moreover, an adaptive transmission time interval(TTI) bundling with self-healing scheme is proposed to further decrease the transmission delay and improve the quality of service(QoS). The simulation results show that the average transmission delay is greatly reduced with our proposed scheme. The bit error rate(BER) and the block error rate are also improved even if the channel changes drastically.