Reliability Evaluation Of Networks Research Articles

Network reliability evaluation and management science applications in resource allocation for police organizations

The effective allocation of resources within police patrol departments is crucial for maintaining public safety and operational efficiency. Traditional methods often fail to account for uncertainties and variabilities in police operations, such as fluctuating crime rates and dynamic response requirements. This study introduces a fuzzy multi-state network (FMSN) model to evaluate the reliability of resource allocation in police patrol departments. The model captures the complexities and uncertainties of patrol operations using fuzzy logic, providing a nuanced assessment of system reliability. Virtual data were generated to simulate various patrol scenarios. The model’s performance was analyzed under different configurations and parameter settings. Results show that resource sharing and redundancy significantly enhance system reliability. Sensitivity analysis highlights critical factors affecting reliability, offering valuable insights for optimizing resource management strategies in police organizations. This research provides a robust framework for improving the effectiveness and efficiency of police patrol operations under conditions of uncertainty.

Remote Monitoring, AI, Machine Learning and Mobile Ultrasound Integration upon 5G Internet in the Prehospital Care to Support the Golden Hour Principle and Optimize Outcomes in Severe Trauma and Emergency Surgery.

Feasibility and reliability evaluation of 5G internet networks (5G IN) upon Artificial Intelligence (AI)/Machine Learning (ML), of telemonitoring and mobile ultrasound (m u/s) in an ambulance car (AC)- integrated in the pre-hospital setting (PS)- to support the Golden Hour Principle (GHP) and optimize outcomes in severe trauma (TRS). (PS) organization and care upon (5G IN) high bandwidths (10 GB/s) mobile tele-communication (mTC) experimentation by using the experimental Cobot PROMETHEUS III, pn:100016 by simulation upon six severe trauma clinical cases by ten (N1=10) experts: Four professional rescuers (n1=4), three trauma surgeons (n2=3), a radiologist (n3=1) and two information technology specialists (n4=2) to evaluate feasibility, reliability and clinical usability for instant risk, prognosis and triage computation, decision support and treatment planning by (AI)/(ML) computations in (PS) of (TRS) as well as by performing (PS) (m u/s). A. Trauma severity scales instant computations by the Cobot PROMETHEUS III, pn 100016) ) based on AI and ML complex algorithms and Cloud Computing, telemonitoring and r showed very high feasibility and reliability upon (5GIN) under specific, technological, training and ergonomic prerequisites B. Measured be-directional (m u/s) images data sharing between (AC) and (ED/TC) showed very high feasibility and reliability upon (5G IN) under specific, technological and ergonomic conditions in (TRS). Integration of (PS) tele-monitoring with (AI)/(ML) and (PS) (m u/s) upon (5GIN) via the Cobot PROMETHEUS III, (pn 100016) in severe (TRS/ES), seems feasible and under specific prerequisites reliable to support the (GHP) and optimize outcomes in adult and pediatric (TRS/ES).

Network reliability of a stochastic flow network by wrapping linear programming models into a Monte-Carlo simulation

A stochastic flow network (SFN) serves as a fundamental framework for real-life network-structured systems and various applications. Network reliability NRd is defined as the probability that an SFN can successfully send at least d units of demand from a source to a terminal. Current analytical algorithms for the network reliability evaluation are classified into an NP-hard problem. This limitation hinders the ability of decision-makers to monitor and manage decisions for an SFN flexibly and immediately. Therefore, this paper develops an algorithm to estimate network reliability by wrapping developed linear programming (LP) models based on minimal paths (MPs) into a Monte-Carlo simulation. The developed LP models present satisfaction of the demand d in the SFN in terms of minimal paths. The effectiveness and efficiency of the proposed algorithm are verified using a series of numerical investigations. Contributions are manifold: (1) an integrated model with the simulation and LP models is provided to estimate network reliability in terms of the MPs, thereby filling a crucial gap in existing research; (2) the scalability and efficiency of the proposed method are shown for the complex SFNs; (3) decision-making capabilities can be provided under real-time reliability predictions.

A parallel algorithm for reliability assessment of multi-state flow networks based on simultaneous finding of all multi-state minimal paths and performing state space decomposition

This article presents a new efficient method for reliability evaluation of two-terminal Multi-state Flow Networks (MFNs). Indirect State Space Decomposition (SSD) methods are usually more efficient than direct SSD methods. However, indirect SSD methods require searching for all d-MPs/d-MCs. The presented method requires only an MFN, a system demand requirement d, and the probability distributions of states of components as an input. The presented algorithm uses a partition technique to decompose a state space into smaller and distinct subspaces. The algorithm tries to determine a d-flow with a lower bound for each subspace. If a flow exists and it is a d-MP, the algorithm computes the probability that a capacity vector belongs to this subspace and is bounded below by the d-MP and decomposes this subspace into smaller subspaces. For all subspaces without d-MP, the presented algorithm uses parallel computations and the SSD method to compute the probability that a capacity vector belongs to this subspace and is bounded below by a d-MP. The numerical experiments show that the efficiency of the presented method improves in comparison with other indirect SSD methods if the number of available logical processes and the number of d-MPs increase.

Reliability Evaluation of Distribution Networks Considering Natural Gas Network Integration

Abstract With the transformation of energy structure, the distribution network in the form of multi-energy interconnection is gradually emphasized. The access of gas turbines to the distribution network puts high requirements on the reliability assessment of the distribution network counting and natural gas network access. Models of distribution network components and natural gas network equipment are established. Based on the traditional sequential MC reliability assessment, the calculation of reliability indexes for the distribution network with gas turbine access is accomplished by identifying the islanded areas under fault conditions and judging the gas turbine output state, taking into account the energy flow constraints. The results of the calculations show that the reliability of the distribution network with natural gas network access is improved, and the reliability of the load nodes near the gas turbine is improved significantly.

A Framework for the Evaluation of Network Reliability Under Periodic Demand

A Framework for the Evaluation of Network Reliability Under Periodic Demand

Super (Edge-)connectivity of the Folded Petersen Network

Reliability evaluation of an interconnection network is of great significance for construction and maintenance of the network. The super (edge-)connectivity, restricted (edge-)connectivity and cyclic (edge-)connectivity are important parameters to evaluate network reliability. Compared with the hypercube [Formula: see text], the folded Petersen network [Formula: see text] has better properties, including strong connectivity, symmetry. Besides, it has smaller diameter and more vertices than [Formula: see text] with the same degree and connectivity. In this paper, based on the symmetric properties of [Formula: see text], we prove that [Formula: see text] is super (edge-)connected, super restricted edge-connected and super cyclically edge-connected. In addition, we obtain the restricted edge-connectivity and the cyclic edge-connectivity of [Formula: see text].

Network reliability evaluation of a supply chain under supplier sustainability

The United Nations’ sustainable development goals have brought attention to the pressing issue of enhancing supply chain sustainability and ensuring equitable order allocation. In contrast to the previous research, this study involves sustainability in network reliability evaluation. A new algorithm is proposed for computing network reliability, the probability that the current supply chain not only meets demand, budget, and suppliers’ production capacity but also considers the level of supplier sustainability. In the constructed multistate supply chain network (MSCN), a node represents a supplier, warehouse, assembler, or market, and a route connecting the nodes represents a carrier. The capacity of each carrier, represented by the available delivery containers, should not be deterministic as they may be partially reserved by other markets. Grounded in the Method Based on the Removal Effects of Criteria (MEREC) and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), the supplier sustainability can be assessed, facilitating the selection of sustainable suppliers and the determination of feasible order allocations, which are essential for various industries. An audio production cooperation is used as a case study to demonstrate the utility of the proposed algorithm.

Recognizing Critical Stations in Urban Rail Transit Networks Based on the PCA‐TPE Method: Shanghai Metro as an Example

The identification of core stations in urban rail transit (URT) networks remains a vital issue in network structure organization analysis and an integral part of network reliability evaluation. However, the identification of critical stations with a single centrality metric has limitations and the varying interactions between stations cannot be ignored. In this paper, a novel integrated approach is proposed by using the principal component analysis and topological potential considering entropy (PCA‐TPE) method. Taking the Shanghai metro (SHM) network as a case study, a Space L network model is constructed and the network topology characteristics are analyzed. Moreover, the susceptible‐infected (SI) model and the network failure simulation are employed to demonstrate the effectiveness of the proposed method. The results show that the SHM network exhibits characteristics of both small‐world networks and scale‐free networks. According to the experiments of the SI model, the nodes obtained by the PCA‐TPE method have stronger spreading influence than those derived by other methods, especially in the initial stage. The failure simulations illustrate that attacks against the nodes detected by the PCA‐TPE method will lead to devastating network failures. Hence, the proposed method is effective for identifying critical nodes in URT networks, and the findings of the research can provide theoretical evidence for the development planning and emergency management of the public traffic system.

An Improved Method to Search All Minimal Paths in Networks

Minimal paths (MPs) play an important role in system reliability analysis, such as binary network reliability evaluation and multistate network reliability evaluation. Searching all MPs is an NP-hard problem. The direct-search-based algorithm implements the depth-first search (DFS) mechanism to find all MPs, which is a simple and efficient method. The current efficient DFS algorithm is based on backtracking and linked list by nodes. In this article, we propose several improvements to speed up the current algorithm. First, we find that the relative positional information of the network can be used to avoid visiting some unnecessary nodes. Thus, we improve the algorithm by incorporating the point in the polygon algorithm to avoid visiting nodes surrounded by other nodes in a network. Second, we further improve the current backtracking condition in which the time complexity of implementing each backtrack is reduced. In addition, we find that different search branches from a similar node are independent and can be executed in parallel. A parallel search mechanism is proposed and incorporated to speed up the searching process. Through computational experiments on several benchmark networks and real transportation networks, we demonstrate that the improved algorithm is more efficient than the existing algorithm. The proposed algorithm becomes more advantageous as the size of the network grows.

Feeder Capacity Planning and Reliability Evaluation Model of Distribution Network Based on Support Vector Machine

Capacity planning and reliability evaluation models of the traditional distribution network feeder mainly use multi-option balance constraints for multi-objective solutions, which are prone to capacity constraints, resulting in lower reliability indicators for planning and evaluation. Therefore, a brand-new distribution network feeder capacity planning and reliability evaluation model based on a support vector machine is designed. By using support vector machines to design the reliability evaluation process of distribution network feeder capacity planning, we establish an optimization model for reliability evaluation of distribution network feeder capacity planning. The experimental results show that the designed feeder capacity planning and reliability evaluation model based on a support vector machine has good evaluation results, high-reliability indicators for planning and evaluation, reliability, and certain application values.

Reliability evaluation for time-based stochastic manufacturing networks with time-dependent reliability

ABSTRACT This study aims to evaluate the system reliability for a time-based stochastic manufacturing network (TSMN). The architecture of a TSMN includes arcs and nodes where each node is an inspection station and each arc is a workstation of identical machines. Due to the possibility of partial or complete maintenance and machine failures, the reliability should be time-dependent and the arcs could be considered as stochastic capacities. To consider time factor, the Weibull reliability function is utilized to characterize the time-dependent reliability of each machine. Then, based on the reliability of each machine, the workstation reliability can be derived, where the workstation reliability is the probability that a workstation can provide sufficient number of machines to complete a demand until a given time. Focusing on a given TSMN with the specified demand and constrained operating time, the performance for a TSMN, which is referred to as TSMN reliability, can be calculated in terms of workstation reliability. In addition, the situation for machines having different times under operation is analyzed for TSMN reliability. A step-by-step procedure for evaluating the TSMN reliability is developed, and a printed circuit board manufacturing system is discussed for the proposed TSMN reliability procedure.

Transmission reliability evaluation of wireless sensor networks considering channel capacity randomness and energy consumption failure

The reliable transmission of data packets is the basis of ensuring the Internet of Things applications. Therefore, how to ensure the transmission reliability of wireless sensor networks has already become a hotspot. However, the existing researches ignore the effects of multiple fault modes and random factors on transmission reliability. Firstly, in the node reliability modeling, few studies have considered the effects of random failure and energy consumption failure comprehensively. Secondly, in the link reliability modeling, existing studies ignore the effect of the channel capacity randomness, which can lead to the erroneous estimation of transmission reliability. To overcome the above shortcomings, we propose a more realistic transmission reliability model. Firstly, considering the comprehensive effects of two failure modes, we establish a new node reliability model to better characterize the node performance. Secondly, considering the channel capacity randomness, we propose an improved SNR-Capacity connection model by deriving the one-hop connectivity probability, which can better characterize the link reliability. Then, we propose a transmission reliability evaluation model, and give the corresponding exact and approximate algorithms for its solution. Finally, taking the military Internet as an example, the effectiveness of the proposed method is verified.

Reliability evaluation for bijection-connected networks based on the super Pk-connectivity

With the need for large-scale networks evolving in a variety of fields, such as cloud/edge computing, social networks, privacy protection, etc., the network's robustness against faulty clusters has recently gained more attention. The family of bijection-connected networks includes numerous instances of remarkable network topologies, for example, hypercubes, Möbius cubes, crossed cubes, etc. For a network whose underlying topology is modeled by a graph G, its node-connectivity, κ(G), is a key performance index of network robustness, which is formalized as the total number of nodes in the smallest node-cut of G. Apparently, κ(G) happens to be bounded above by G's minimum degree. A node-cut is trivial if it is nothing but an arbitrary node's neighborhood. Then, G can be r-connected if 1≤r≤κ(G). To say the least, if each smallest node-cut of G is trivial, G is super connected. The super Pk-connectivity is an innovative assessment to quantify the connectedness level of G, where Pk notates a path consisting of k nodes (k≥1). This article aims to investigate the super Pk-connectivity for the bijection-connected networks. With regard to some specific instances, such as hypercubes, locally twisted cubes, etc., a sufficient and necessary condition is established to identify whether they are really super Pk-connected.

Tensor and Confident Information Coverage Based Reliability Evaluation for Large-Scale Intelligent Transportation Wireless Sensor Networks

Wireless sensor network (WSN) plays an important role in information collection and processing in Intelligent Transportation Systems (ITS) recently. With rapid development of ITS, the size and complexity of WSN is rapidly increasing. Thus, how to evaluate the reliability of large-scale WSN has attracted more and more attention. In this paper, reliability is defined as the probability that the WSN is functional. A confident information coverage (CIC) model-based reliability algorithm (CICRA) is proposed to comprehensively consider coverage reliability and connectivity reliability. Especially, to determine the impact of failing nodes on connectivity in large-scale WSN, a grid clustering connectivity algorithm (GCCA) is proposed to reduce the complexity of computing the connectivity between large-scale wireless sensor nodes, which transforms the connectivity problem between nodes into a grid connectivity problem. In addition, a 3-order tensor modeling is proposed to uniformly represent and model node states, node combinations, and coverage patterns. Furthermore, the network reliability combines coverage reliability and connectivity reliability is evaluated by tensor modeling. Simulation results indicate that the proposed CICRA can improve the network reliability and accuracy of reliability evaluation.

Holistic Resilience and Reliability Measures for Cellular Telecommunication Networks

Nowadays, our lives have become increasingly inseparable from the services facilitated by telecommunication networks. Disruption of this service may result in a significant detrimental effect, especially in smart manufacturing, remote surgery, and harbor logistic. With the development and deployment of the new generation of telecommunication, i.e., 5G mobile networks, reliability has been repeatedly emphasized as a critical issue. Contemporary telecommunication networks often have a large scale. Evaluating network reliability is a challenging issue related to the spatiotemporal characteristics of the network and of the connection principles. In this paper, we bring together concepts from computational geometry and reliability engineering to forge a new approach to address the challenging issue. We first formulate a Voronoi-based Graphic network (VGN) model with a novel built-in dependence, coverage dependence, that manifests the resilience of the network. Based on the VGN model, we propose two new measures for holistically assessing the resilience and reliability of telecommunication networks in a large region. Ultimately, we employ the designed approach to telecommunication networks. The result indicates that coverage dependence and resilience are important factors for delivering ultra-reliable service to users promised by the 5G.

Reliability evaluation of half hypercube networks

With the increase of the number of processors in the interconnection network, the failure of processors is inevitable. When the processor fails, the information passing through the failed processor will be unreliable, which may cause fatal consequences. Therefore, the research on the reliability of interconnection networks is an important topic, and the reliability of networks can be characterized by connectivity and diagnosability. In this paper, we first establish that the h-extra connectivity of the n-dimensional half hypercube network HHn is κh(HHn)=−12h2+(⌈n/2⌉−12)h+⌈n/2⌉+1 for n≥7 and 0≤h≤⌈n/2⌉−4, and then determine that the h-extra diagnosability of the HHn under the PMC model (n≥7 and 0≤h≤⌈n/2⌉−4) and the MM* model (n≥7 and 0≤h≤⌈n/2⌉4−1) is th(HHn)=−12h2+(⌈n/2⌉+12)h+⌈n/2⌉+1. Finally, we obtain that HHn is [−12k2+(⌈n/2⌉−12)k+⌈n/2⌉+1]/k-diagnosable under the PMC model.

Retracted: Establishment and Optimization of College Students Physical Health Standard Test System Based on Neural Network Reliability Evaluation Model

Retracted: Establishment and Optimization of College Students Physical Health Standard Test System Based on Neural Network Reliability Evaluation Model

On Network Reliability Evaluation by Monte Carlo Method Using High-Performance Computing

On Network Reliability Evaluation by Monte Carlo Method Using High-Performance Computing

Survey of multistate network reliability and resilience evaluation methods

Survey of multistate network reliability and resilience evaluation methods