Interruption Probability Research Articles

Dynamic deadline constrained multi-objective workflow scheduling in multi-cloud environments

Workflow scheduling becomes difficult and demanding in multi-cloud systems because of the variety of billing models and resource kinds, as well as the susceptibility of processes to time limitations. In which the execution duration of the workflow needs to be flexibly adjusted according to the urgency or otherwise of the real situation, in this work, we model the workflow scheduling problem with deadline constraints as a dynamically constrained multi-objective optimization problem (DCMOP), where the disruption rate of the special cloud resources and the failure probability in different cloud environments are expressed as the disruption probability of the workflow in a comprehensive manner while considering the execution time and cost. Dynamics arise from price changes for specialized cloud resources and changes in the execution duration of workflows. In addition, an algorithm for dynamically constrained multi-objective optimization (DC-MOEA-DPDS) is proposed in this paper. The algorithm based on two-population synergy as well as diversity selection. The auxiliary population ignores constraint limitations to help the main population speed up convergence, and diversity selection enables the auxiliary population to have better diversity to assist the general public in looking for more viable areas. Through dynamic constrained workflow simulation experiments in a multi-cloud environment, our algorithm reduces the execution time by an average of 13.29%, the cost by an average of 32.26%, and the interruption probability by 56.75%. In addition, our algorithm outperforms other algorithms in experiments on a dynamically constrained benchmark set.

Multi-protocol updating for seamless key negotiation in quantum metropolitan networks

Quantum key distribution (QKD) can provide long-term security for numerous users. Currently, quantum networks are still in the early stages of small-scale deployment, most of which can only support a single QKD protocol (QKDP). However, with the advancement of various QKDPs, a single-protocol quantum network is no longer sufficient to meet the demands of multiple users, prompting the emergence of multi-protocol quantum networks. Nevertheless, the transition from a single-protocol to a multi-protocol quantum network still faces many challenging issues, such as key negotiation interruptions due to device initialization and channel calibration during protocol updating. To address the quantum key negotiation interruption problem, we propose a seamless key negotiation oriented multi-protocol updating algorithm in this work, which can fulfill the protocol updating requests of different users in quantum metropolitan networks. Furthermore, to better improve network performance while meeting diverse user demands, we propose four heuristic algorithms for optimal QKDP recommendation, focusing on their applications for multi-protocol updating in different types of typical networks. We perform the simulations with different QKDP recommendation algorithms to analyze the impact of the cache time of the key cache area on the key negotiation interruption probability and the time resource utilization. Simulation results demonstrate that the proposed algorithm can reduce the key negotiation interruption probability by 77.7% while increasing the time resource utilization by 15.3% compared to no key cache area.

Marine Mammal Conflict Avoidance Method Design and Spectrum Allocation Strategy

Underwater wireless sensor networks play an important role in underwater communication systems. Communication through collaborative communication is an effective way to solve critical problems in underwater communication systems. Underwater sensors are often deployed in spaces that overlap with those of marine mammals, which can adversely affect them. For this reason, in this paper, a marine mammal conflict avoidance method that can be dynamically adjusted according to the channel idle time duration and sensor node demand is designed, and the derivation of the maximum occupancy time duration is performed. Meanwhile, in addition, combining the potential of reinforcement learning in adaptive management, efficient resource optimization, and solving complex problems, this study also proposes a reinforcement learning-based relay-assisted spectrum switching method (R2S), which aims to achieve a reasonable allocation of spectrum resources in relay collaborative communication systems. The experimental results show that the method proposed in this study can effectively reduce the disturbance to marine mammals while performing well in terms of conflict probability, interruption probability, and quality of service.

Optimization of off-grid renewable energy systems using a hybrid version of golden search algorithm

Currently, the development of HRESs (hybrid renewable energy systems) in remote areas is of great importance and popularity. However, measuring and optimizing the capacity of these systems faces a difficult challenge. Multiple works had been reported in the literature to optimize such systems, all of which aim to achieve an optimal configuration with minimum annual net cost. Therefore, the significance of providing off-grid electrification to remote areas through HRESs can be highlighted as a crucial case for sustainable growth. Accordingly, the study proposes a modified metaheuristic approach, known as the Hybrid Golden Search Algorithm (HGSA), for long-term application planning and optimization of the off-grid HRES. The aim of this algorithm is to minimize the amount of net cost which is used annually; to reduce the probability of power supply interruption. In order to assess the effectiveness of the proposed algorithm, a simulation study over a long period on a remote area was conducted. From the results, increasing the reliability level from 1 % to 3 % causes a decrease in the total net annual cost by around 7.3 % under the proposed HGSA and also results in a reduction in component size (around 6 % and 21 % reductions for the wind turbine area and storage tanks, respectively). Further, the HGSA technique obtains the lowest value of fitness function for the hybrid system at a reliability level of 3 %, which is 31,539,810$. This result demonstrates that the efficiency of HGSA outperforms Fuzzy Logic and Optimization, Artificial Bee Colony (ABC), and GSA techniques. Based on this, the proposed HGSA could lead to more promising results than the other comparative algorithms. Hence, the proposed HGSA can be a valuable tool for long-term application planning and optimization of off-grid HRES, which can contribute significantly to achieving sustainable development goals.

A robust microgrid formation method for risk-resistant service restoration considering subsequent contingency

Service restoration (SR) is essential for resilience enhancement of distribution systems (DSs) when natural disasters occur. However, a restored DS may face potential outage risks caused by subsequent contingency during the prolonged event. To improve the risk-resistance of SR strategies, this paper proposes a microgrid-based SR method to continuously supply critical loads when considering subsequent contingency. The microgrids are proactively formed to mitigate the influence of subsequent contingencies, which can effectively reduce the load shedding and wind power curtailment during the SR process. To deal with uncertainties of subsequent contingency and wind power, a two-stage robust model is established. Moreover, an improved uncertainty set is established to further reduce the conservatism of robust optimization. Specially, the line interruption probability is considered when constructing the Shannon entropy-based uncertainty set of subsequent contingencies, and the spatial–temporal correlations of wind power is considered when formulating the budget-constrained uncertainty set. Then, the robust model is solved by column-and-constraint generation algorithm efficiently. Numerical results demonstrate that the proposed SR method can effectively enhance the risk-resistance of SR strategy and reduce the conservatism while ensuring the robustness of solutions.

Improving FSO Link Performance using PolSK Modulation

Free Space Optical (FSO) communication systems are based on the use of infrared light to transmit information at high speed through the atmospheric channel. Their performance is therefore affected by the characteristics of the atmospheric channel. One of the most widely used methods of compensating for the effects of atmospheric factors is modulation.The main aim of this research is to demonstrate the improvement in FSO link performance using PolSK modulation in a subtropical environment such as Cˆote d’Ivoire. The performance indicators considered are bit error rate, channel capacity, outage probability and energy efficiency. The mathematical expression of the evolution of each of these indicators as a function of the atmospheric parameters of our environment was determined using the gamma-gamma model. A numerical evaluation of the results obtained was carried out using Matlab software. The results show that PolSK modulation offers the best results in terms of BER reduction, with a BER of the order of 10-11 for an SNR of 50dB, compared with BERs of 10-4 and 10-2 for BPSK and OOK modulations respectively. We obtain a probability of interruption of the order of 10-3 for PolSK modulation compared with 10-2 for BPSK modulation and 10-1 for OOK modulation. As for the channel capacity, we obtain the same value (4:1458bit/s) for PolSK and BPSK modulation compared with 3:8181bit/s for OOK modulation. BPSK modulation, on the other hand, stands out for its excellent energy efficiency.

Characteristics, predictors and consequences of tuberculosis treatment interruption: A multicentre retrospective cohort study.

Treatment interruption is associated with poor tuberculosis (TB) treatment outcomes and increased drug resistance. To address the issue, we aimed to investigate the characteristics, predictors and consequences of treatment interruption. We conducted a retrospective cohort study by retrieving 4 years (2018-2021) of TB patients' records at 10 public health clinics in Sarawak, Malaysia. Adult patients (≥18 years) with drug-susceptible TB were selected. Treatment interruption was defined as ≥2 weeks of cumulative interruption during treatment. The Chi-square test, Mann-Whitney U test, Kaplan-Meier and Cox proportional hazards regression were used to analyse the data, with p < 0.05 being considered statistically significant. Out of 2953 eligible patients, 475 (16.1%) experienced TB treatment interruption. Interruptions were most frequent during the intensive phase (46.9%, n = 223), with the greatest risk within the first 4 weeks of treatment. The median time to interruption was 2 weeks in the intensive phase and the cumulative interruption probability at the end of the intensive phase was 12.9%. Notably, treatment interruption occurred during both intensive and continuation phases for 144 patients (30.3%), while the remaining 108 (22.7%) experienced interruptions only during the continuation phase with a median time to interruption of 16 weeks. Three predictors were identified to increase the risk of treatment interruption: adverse drug reaction (aHR = 8.53, 95% Cl: 6.73-10.82), smoking (aHR = 2.67, 95% Cl: 2.03-3.53) and illicit drug use (aHR = 1.88, 95% Cl: 1.03-3.45). Conversely, underlying diabetes was associated with a reduced likelihood of treatment interruption (aHR = 0.72, 95% Cl: 0.58-0.90). Treatment interruption led to significant differences in treatment restarts (62.3% vs. 0.7%), changes in medications (47.8% vs. 4.9%), prolonged treatment duration (247 days [IQR = 105] vs. 194 days [IQR = 44.3]) and lower successful outcomes (86.5% vs. 99.9%). Understanding the temporal characteristics, predictors and negative consequences of treatment interruption can guide the development of time-relevant approaches to mitigate the problem.

FILTERING OF AN INTERRUPTED SIGNAL ON APPROXIMATION BY GAMMA DISTRIBUTION UNDER THE INFLUENCE OF ADDITIVE MULTIPLICATIVE INTERFERENCE

The problem of constructing an algorithm for recognizing and filtering a continuous-valued Markov process measured in a mixture with random additive and multiplicative interference under conditions of random information interruptions is considered. The Bayes principle and the well-known two-stage filtering method “forecast-correction” are applied, supplemented by procedures for identifying the number of the structure, in which the system is located in the current and next time intervals. At the forecast stage, identification is based on calculating the probabilities of the future state of the system based on a priori information about the probabilities of its transitions from structure to structure, as well as on the current values of estimates of these probabilities. At the correction stage, identification is based on the use of probability prediction results and a priori known information about the reliability of the information of the system status indicator. In addition, the values of the probability densities of the measuring information in each structure are used, the expressions for which are obtained on the basis of a priori known laws of distribution of additive and multiplicative interference, as well as the predicted probability density of the Markov process in each structure at the next step of calculations. To obtain a practically realizable algorithm, expressions for the predicted and a posteriori densities of the Markov process probabilities are obtained based on their approximation by the probability density of the gamma distribution, completely determined by the first two initial moments. This made it possible to obtain a closed system of recurrent equations for estimating the probability of information interruption, mathematical expectations and variances of the Markov process in each structure.

Application of Mass Service Theory to Economic Systems Optimization Problems—A Review

An interdisciplinary approach to management allows for the integration of knowledge and tools of different fields of science into a unified methodology in order to improve the efficiency of resource management of different kinds of systems. In the conditions of global transformations, it is economic systems that have been significantly affected by external destabilizing factors. This determines the focus of attention on the need to develop tools for the modeling and optimization of economic systems, both in terms of organizational structure and in the context of resource management. The purpose of this review study is to identify the current gaps (shortcomings) in the scientific literature devoted to the issues of the modeling and optimization of economic systems using the tools of mass service theory. This article presents a critical analysis of approaches for the formulation of provisions on mass service systems in the context of resource management. On the one hand, modern works are characterized by the inclusion of an extensive number of random factors that determine the performance and efficiency of economic systems: the probability of delays and interruptions in mobile networks; the integration of order, inventory, and production management processes; the cost estimation of multi-server system operation; and randomness factors, customer activity, and resource constraints, among others. On the other hand, controversial points are identified. The analytical study carried out allows us to state that the prevailing majority of mass service models applied in relation to economic systems and resource supply optimization are devoted to Markov chain modeling. In terms of the chronology of the problems studied, there is a marked transition from modeling simple systems to complex mass service networks. In addition, we conclude that the complex architecture of modern economic systems opens up a wide research field for finding a methodology for assessing the dependence of the enterprise performance on the effect of optimization provided by using the provisions of mass service theory. This statement can be the basis for future research.

Modeling and stability analysis of an extended car-following model behavior of the currents vehicle based on delay of response and signal interruption probability

This paper studies the modeling and stability analysis of an extended car-following model based on delay of response and signal interruption probability. First, by linear analysis, we give the stability condition of the model. The result shows that the stability region of the traffic flow will expand with the decrease in the probability p of signal transmission interruption. When the delay of response effect of the driver weakens, the traffic flow will become more and more stable. Second, the mKdV equation is derived based on the nonlinear reduction perturbation method. This result shows that with the decrease of parameter p, the amplitude of the traffic flow density wave decreases, the traffic flow becomes more and more stable, and the traffic congestion is gradually improved. Finally, numerical simulation verifies the correctness of the solution results.

Pricing of fresh agricultural product supply chain under transportation interruption

With the trend of global economic integration and the improvement of logistics, transportation, and storage technology, regional restrictions on the sales of fresh agricultural products have gradually decreased. At the same time, due to traffic accidents, natural disasters, and other factors, the possibility of interruption in the transportation supply chain of fresh agricultural products has been increased. This article examines a three-level fresh supply chain with the possibility of transportation interruption. The Stackelberg method is used to solve the equilibrium solution, and the results under centralized and decentralized models are analyzed. We found that the increase in the probability and duration of transportation interruptions actually leads to less investment by distributors in cold chain services, resulting in increased profits for retailers and decreased profits for distributors and manufacturers.

Demonstration of 120 Gbit/s turbulence-resilient coherent optical communication employing cylindrical vector beam multiplexing

Free space optical (FSO) communication has gained widespread attention due to its advantages, including high confidentiality, high communication capacity, and no limitation of spectrum. One of the great challenges in FSO communication is the transmission performance degradation in atmospheric turbulence channel due to wavefront distortion and scintillation. Here, we proposed and experimentally demonstrated a 120 Gbit/s vector beam multiplexed coherent optical communication system with turbulence-resilient capacity. Four multiplexed vector beams, each carrying a 30 Gbit/s quadrature phase-shift keying signal, propagate through different turbulence conditions. The influence of turbulence channel on the vector beam impairments is experimentally investigated. Under the weaker turbulence conditions, the system bit error rates are below the forward error correction threshold of 3.8 × 10−3. In comparison with the Gaussian mode, the communication interruption probability of the vector beams system decreases from 36% to 12%-18% under stronger turbulence conditions.

INFLUENCE OF DIAGNOSTICS FREQUENCY OF BACKUP POWER SUPPLY ON THE RELIABILITY OF ELECTRICITY SUPPLY

The article is dedicated to studying the impact of the frequency of diagnosing a backup power source on the reliability of electricity supply and assessing the economic risk of power interruptions in cases of backup or its absence. The study was conducted in the context of developing an automatic diagnosis system for power sources based on internal combustion engines, which has gained additional relevance during times of energy instability caused by the war.&#x0D; To justify the necessity of installing a backup power source and its timely diagnosis, the relationship between the probability of power interruption before and after backup on a production line is analyzed. The final product of the line results from a sequence of operations, and any interruption in any of them leads to defective production. Based on input data, the cost of one unit of the product and the time required for its production are estimated, allowing for an hourly income assessment for the production area. The time lost during a power interruption, the economic impact of such an event, and the associated risks are calculated.&#x0D; Similarly, the situation is considered, but with backup in place, taking into account the operational readiness of the backup power source. It is assumed that the technical condition of the backup power source may randomly deteriorate and remain in that state until it is actually restored. The probabilities of power interruption and the associated risks under these conditions are calculated. The obtained data is compared, and recommendations are provided for increasing the reliability of backup.&#x0D; The results of the research reveal that the installation of a backup power source significantly reduces the risk of power interruption. The inspection period for the diesel generator can be reduced to enhance the reliability of backup, with the maximum level achieved through the use of an automatic diagnosis system for the diesel generator's condition.

Patterns of individual compliance with anthelmintic treatment for soil-transmitted helminth infections in southern Ethiopia over six rounds of community-wide mass drug administration.

The mainstay of soil-transmitted helminth (STH) control is repeated mass drug administration (MDA) of anthelmintics to endemic populations. Individual longitudinal compliance treatment patterns are important for identifying pockets of infected individuals who remain untreated and serve as infection reservoirs. The Geshiyaro Project censused the study population in Wolaita, Ethiopia at baseline in 2018. Individual longitudinal compliance was recorded for six rounds of community-wide MDA (cMDA). The probability distribution of treatment frequency was analysed by age and gender stratifications. Probabilities of transmission interruption for different compliance patterns were calculated using an individual-based stochastic model of Ascaris lumbricoides transmission. The never-treated (0.42%) population was smaller than expected from a random positive binomial distribution. The observed compliance frequency was well described by the beta-binomial distribution. Preschool-age children (odds ratio [OR] 10.1 [95% confidence interval {CI} 6.63 to 15.4]) had the highest never-treated proportion of the age groups. Conversely, school-age children (SAC) and adults (OR 1.03 [95% CI 0.98 to 1.09]) had the highest always-treated proportion of the age groups. The study reports the largest dataset of individual longitudinal compliance to cMDA for STH control. Clear pattens are shown in the age-dependent distribution of individual compliance behaviour. The impact of compliance on the probability of elimination is significant, highlighting the importance of recording the full frequency distribution, not just the never-treated proportion.

Drug survival and clinical effectiveness of secukinumab, ixekizumab, brodalumab, guselkumab, risankizumab, tildrakizumab for psoriasis treatment.

Biologics targeting IL-23 and IL-17 show efficacy and safety in the treatment of moderate-to-severe psoriasis. To investigate drug survival in patients with psoriasis treated with biologics. We performed a comparative evaluation of the achievement of PASI90 and PASI ≤ 3 at 16, 28, and 52weeks along with a DS (drug survival) analysis with IL-17 and IL-23 inhibitors brodalumab, ixekizumab, secukinumab, risankizumab, tildrakizumab, and guselkumab on 1,057 patients. IL-17 inhibitors showed a faster achievement of PASI90 and PASI ≤3 with significant superiority over IL-23 inhibitors at week 16 (p<0.001; 56% vs. 42% and 70% vs. 59%, respectively). A difference was shown in favor of IL-23 inhibitors regarding DS (p<0.001), which was 88% at 24 months vs. 75% for IL-17 inhibitors. In multivariate analysis, IL-23 inhibitors (HR 0.54 CI 0.37-0.78, p=0.001), and male sex (HR 0.57 CI 0.42-0.76, p<0.001) were all associated with a lower probability of drug interruption. Risankizumab (HR 0.42 CI 0.26-0.69, p=0.001), guselkumab (HR 0.49 CI 0.24-0.99, p=0.046), and male sex (HR 0.57 CI 0.43-0.77, p<0.001) were associated with a lower probability of drug interruption than secukinumab. IL-23 inhibitors showed the best performance on DS. Overall, the most effective class was IL-17 inhibitors considering the short-term effectiveness, but long-term effectiveness is in favor of anti-IL-23.

Robust beamforming design for UAV communications based on integrated sensing and communication

Integrated sensing and communication (ISAC) has been a promising technique in various wireless communication applications. In this paper, we investigate a beamforming design method based on ISAC waveforms in unmanned aerial vehicle (UAV) communications. An integrated state prediction and beamforming design framework is presented. We utilize the target states from sensing algorithms to improve the prediction performance. Based on the predicted states, we formulate the mathematical form of the communication interruption probability. To enhance the beamforming performance, we propose a design approach that satisfies both sensing and communication metrics and the communication interruption constraints. We show that the proposed method achieves robust communication under the integrated state prediction and beamforming design framework. Simulation results show that by using the ISAC signal, our method significantly lowers the communication interruption probability in the beamforming process and achieves better communication performance.

A trajectory optimization method for UAV cascade relay broadcast communication system

An unmanned aerial vehicle's(UAV) trajectory optimization is an important way to improve the performance of its relay communication system. The trajectory optimization method for the UAV cascade relay broadcast communication system that uses the decoding and forwarding protocols is studied. Firstly, the expressions of the signal-to-noise ratio of the UAV and the user are given. Then, a joint trajectory optimization method and a distributed trajectory optimization method for cascaded UAVs based on the minimized maximum user interruption probability are proposed. The transmission performance of the system link that uses the two trajectory optimization methods is studied; the mathematical expressions of the relay communication system's traverse capacity and the outage probability of a single user are given. Finally, the influence of the relay communication system's characteristic parameters on the optimal trajectory of the cascade relay UAV and its performance are verified with computer simulations. The simulation results show that the performance of the two trajectory optimization methods is basically the same, thus verifying the effectiveness of the trajectory optimization criterion.

Substantiation for the relationship and «closed loop effect» between post-traumatic stress disorder and recurrent pregnancy loss

The objective: to identify and evaluate the changes in immune homeostasis in women with recurrent pregnancy loss (RPL) who had posttraumatic stress disorder (PTSD), and to establish the relationship between psycho-emotional status, the immune system and the role of chronic stress in the pathogenesis of autoimmune disorders as a cause of RPL.Materials and methods. An examination of 150 women of reproductive age was carried out, who were divided into three groups: I group (main group) – 100 patients with RPL and PTSD; II group (comparison one) – patients with RPL without PTSD (30 women) and the III group (control one) – 20 patients with PTSD who are planning pregnancy.Indicators of cellular immunity were studied and antiphospholipid syndrome was diagnosed. The electronic database of primary data was created using the Microsoft Excel 2016 spreadsheet program. Statistical data analysis was performed using the Statistica10.0 statistical analysis package.Results. Based on the results of the screening it was found that there are non-specific antibodies to anionic phospholipids, also known as antiphospholipid antibodies, in some patients of the main group. In the presence of antiphospholipid antibodies, the number of NK cells (CD3-CD16/56+) doubled, increasing the probability of the pregnancy interruption that had already occurred. There was also an increased number of NK cells (CD3-CD16/56+) in the blood of patients with PTSD compared to the control group – the patients with PTSD who are planning pregnancy.Conclusions. The results of the study confirmed the connection between PTSD and RPL and demonstrated significant immune homeostasis disorders, as well as the structural and morphological changes in the reproductive system.Women with RPL may have PTSD, which affects the pathogenesis of autoimmune disorders and RPL. These results lead to more deep understanding of RPL and will help in the development of new preventive and therapeutic measures.

Shadow Effect of Human Obstacles on Indoor Visible Light Communication System with Multiple Light Sources

When the direct visible-light channel is affected by people walking or other obstacles, the shadow effect formed in the receiver space affects communication performance and can even lead to communication interruption. In this paper, two numerical methods for calculating the shadow area of the human body were proposed for an indoor multi-light communication system. The influence of shadows on system performance was analyzed using the mean square errors of illuminance and signal-to-noise ratio, as well as the interrupt probability, as parameters. The results showed that shadows had a great influence on the performance of the visible-light communication system. When the number of light sources was fixed, the shadow effect could be effectively reduced by optimizing the layout of the light sources. These research results can provide a theoretical basis for improving the stability of visible-light communication systems.

Turbulence-resistant high-capacity free-space optical communications using OAM mode group multiplexing.

Twisted light carrying orbital angular momentum (OAM), which features a helical phase front, has shown its potential applications in diverse areas, especially in free-space optical (FSO) communications. Multiple orthogonal OAM beams can be utilized to enable high-capacity FSO communication systems. However, for practical OAM-based FSO communication links, atmospheric turbulence will cause serious power fluctuations and inter-model crosstalk between the multiplexed OAM channels, impairing link performance. In this paper, we propose and experimentally demonstrate a novel OAM mode-group multiplexing (OAM-MGM) scheme with transmitter mode diversity to increase system reliability under turbulence. Without adding extra system complexity, an FSO system transmitting two OAM groups with a total of 144 Gbit/s discrete multi-tone (DMT) signal is demonstrated under turbulence strength D/r0 of 1, 2, and 4. In our experiments, the proposed OAM-MGM scheme helps to achieve bit-error-rate (BER) mostly less than 3.8 × 10-3 under turbulence strength D/r0 of 1 and 2 with a total transmitted power of 10 dBm. Compared with the conventional OAM mode multiplexed system, the system interruption probability decreases from 28% to 4% under moderate turbulence strength D/r0 of 2.