Network Survivability Research Articles

Medical therapy, radiofrequency ablation or cryoballoon ablation as first-line treatment for paroxysmal atrial fibrillation: interpreting efficacy through restricted mean survival time and network meta-analysis.

When multiple treatments are available, network meta-analysis can evaluate data to rank the relative effectiveness. We applied this approach to first-line treatments for paroxysmal atrial fibrillation (medical therapy, radiofrequency ablation or cryoballoon ablation). Individual trials were analysed based on the restricted mean survival time (RMST). Randomised controlled trials (RCT) assessing first-line treatments for paroxysmal atrial fibrillation were referenced from PubMed and the websites of regulatory agencies. The primary end-point was atrial fibrillation recurrence-free survival at 12 months. The treatments assessed for their relative effectiveness were medical therapy, radiofrequency ablation and cryoballoon ablation. Individual trials were examined based on RMST. A Bayesian network meta-analysis was conducted to comparatively evaluate these treatments. Five trials were included in the analysis: two compared radiofrequency with medical treatment and three cryoballoon ablation with medical treatment. The indirect comparison of radiofrequency ablation vs cryoballoon ablation was assessed in the absence of RCTs. Differences in RMST (with 95% credible intervals) were estimated for all binary comparisons (direct or indirect). Radiofrequency and cryoballoon ablation showed significantly increased effectiveness compared with medical treatment. In the indirect comparison, radiofrequency showed a non-significant advantage over cryoballoon ablation. The ranking of effectiveness was as follows: (1) radiofrequency; (2) cryoballoon ablation; (3) medical treatment. In conclusion, we found that radiofrequency was the most effective treatment for paroxysmal atrial fibrillation according to a Bayesian probabilistic model.

ADVERSITIES AND COPPING MECHANISMS OF SLUM AREA RESIDENTS IN GONDAR CITY; NORTH WEST ETHIOPIA

The expansion of slum areas have been one of the critical challenges manifested with the rapid urbanization of the global south countries. As one of the metropolitan cities in Ethiopia, Gondar city experienced this problem for long time. This study aimed at investigating the adversities related to physical environment, means of survival, health situation and social network of residents in Gojjo sefer slum area in Gondar city. Qualitative phenomenological research design was employed to understand the real life experience of slum dweller in the study area. A total of 35 participants were purposively recruited in the study area. Accordingly, data was collected by in-depth interview, key informant interview and field observation. The findings show that, congested and poorly constructed housing, inadequate infrastructure and poor social service provision characterize the area. Most of the dwellers are immigrants from rural area. They have being suffered from varieties of problems such as low income, lack of health care services and are exposed to frequent disease such as diarrhea, fever and chronic illnesses. As copping strategy, dwellers in this area are mainly engaged in petty economic activities-small and informal business, daily labor, street vending and paid domestic works. Thus, the local government and nongovernmental organization should intervene to the area with appropriate urban planning and sustainable livelihood strategies.

An Optimized Method of Packet Loss Rate under Backup Path Protection in OBS Network

In order to calculate the packet loss rate in OBS network, this paper proposes a method, which performs good in both accuracy and rapidity, based on Erlang B formula to estimate the packet loss probability in OBS network using backup path protection mechanism. This method can be used to optimize the design of OBS network protocol, and it also provides an accurate and efficient approximate calculation method of packet loss rate in OBS network and can be conductive to the study of using copy transmission to enhance the network survivability. Based on the formula of Erlang B, this paper briefly introduces the derivation process and principle of this method. The basic experimental principles of simulation and estimation processes are designed in this paper, and the experimental results of the proposed method under a typical network topology (ARPA network) with no protection mechanism and 1 and 2 backup paths protection mechanisms are analyzed to verify its rapidity and accuracy. The results of experiments show the accuracy and efficiency of this method.

Investigation of possibilities of replacement of cable lines by radio relays in difficult­-accessible and «problem» areas

The article considers the routes of cable systems of the telecommunication network, for each its advantages and features are determined. The key trends and prospects for the development of radio relay communication in Ukraine are noted. The analysis of the current state of digital radio relay communication systems in the market of information and telecommunication services is given, indicating their tactical and technical characteristics, their peculiarities of use are given. A detailed analysis of the possibilities of replacing cable communication lines in hard-to-reach and «problematic» environments with the latest digital radio relays and replacing the «problem» area with other promising wireless transmission systems. Promising systems of wireless information transmission are analyzed. The analysis showed that the decision to partially replace certain network components with more convenient ones should be implemented. To address the goal set in the article, the following steps are considered, namely: reducing maintenance costs, increasing the simplicity and speed of construction of the communication network, increasing network survivability to the detriment of simplicity, clarifying the possibility of compensating the data exchange rate, autonomy of the network structure from other public or private institutions. Recommendations for the use of the obtained results are the expediency of replacing cable communication lines with radio relays in hard-to-reach and problem areas and as an alternative, laser data transmission is chosen, which allows to significantly speed up information exchange between two stations on the «problem» area. any network flow. Laser receivers, due to their low power, do not pose a health hazard.

Survivability-Enhanced Virtual Network Embedding Strategy in Virtualized Wireless Sensor Networks.

With the widespread application of wireless sensor networks (WSNs), WSN virtualization technology has received extensive attention. A key challenge in WSN virtualization is the survivable virtual network embedding (SVNE) problem which efficiently maps a virtual network on a WSN accounting for possible substrate failures. Aiming at the lack of survivability research towards physical sensor node failure in the virtualized sensor network, the SVNE problem is mathematically modeled as a mixed integer programming problem considering resource constraints. A heuristic algorithm—node reliability-aware backup survivable embedding algorithm (NCS)—is further put forward to solve this problem. Firstly, a node reliability-aware embedding method is presented for initial embedding. The resource reliability of underlying physical sensor nodes is evaluated and the nodes with higher reliability are selected as mapping nodes. Secondly, a fault recovery mechanism based on resource reservation is proposed. The critical virtual sensor nodes are recognized and their embedded physical sensor nodes are further backed up. When the virtual sensor network (VSN) fails caused by the failure physical node, the operation of the VSN is restored by backup switching. Finally, the experimental results show that the strategy put forward in this paper can effectively guarantee the survivability of the VSN, reduce the failure penalty caused by the physical sensor nodes failure, and improve the long-term operating income of infrastructure provider.

Hybrid grey wolf sunflower optimisation algorithm for energy‐efficient cluster head selection in wireless sensor networks for lifetime enhancement

Wireless sensor networks (WSNs) are expected to find extensive applicability and accelerating deployment in the future. However, the main challenge faced in WSN is its perishing lifetime. The process of clustering a network is a popular mechanism employed for the purpose of extending the lifespan of WSNs and thereby making efficient data transmission. The main aim of a clustering algorithm is to elect an optimal cluster head (CH). The recent research trend suggests meta-heuristic algorithms for the selection of optimal CHs. Meta-heuristic algorithms possess the advantages of being simple, flexible, derivation-free, and avoids local optima. This research proposes a novel hybrid grey wolf optimiser-based sunflower optimisation (HGWSFO) algorithm for optimal CH selection (CHS) under certain factor constraints such as energy spent and separation distance, such that the network lifetime is enhanced. Sunflower optimisation (SFO) is employed for a broader search (exploration) where the variation of the step-size parameter brings the plant closer to the sun in search of global refinement, thus increasing the exploration efficiency. Grey wolf optimisation (GWO) is employed for a narrow search (exploitation), where the parameter coefficient vectors are deliberately required to emphasise exploitation. This balances the exploration-exploitation trade-off, prolongs the network lifetime, increases the energy efficiency, and enhances the performance of the network with respect to overall throughput, residual energy of nodes, dead nodes, alive nodes, network survivability index, and convergence rate. The superior characteristic of the suggested HGWSFO is validated by comparing its performance with various other existing CHS algorithms. The overall performance of the proposed HGWSFO is 28.58%, 31.53%, 48.8%, 49.67%, 54.95%, 70.76%, and 87.10%, better than that of GWO, SFO, particle swarm optimisation (PSO), improved PSO, low-energy adaptive clustering hierarchy (LEACH), LEACH-centralised, and direct transmission, respectively.

Dysregulation of the Immune Microenvironment Contributes to Malignant Progression and Has Prognostic Value in Bladder Cancer.

ObjectiveThe malignant progression from non-muscle-invasive bladder cancer (NMIBC) to muscle-invasive bladder cancer (MIBC) is common and has detrimental effect on patients. We aimed to elucidate the underlying mechanisms of the malignant progression from an immunological perspective and establish a reliable signature for prognostic prediction and immunotherapeutic strategies.MethodsThe Cell Type Identification by Estimating Relative Subsets of RNA Transcripts algorithm was applied to the GSE32894 data set to identify the different tumor-infiltrating immune cells involved in NMIBC and MIBC. Using weighted gene correlation network analysis, survival analysis and least absolute shrinkage and selection operator Cox analysis, we established an immune prognostic signature (IPS) based on 14 overall survival-associated immune genes in The Cancer Genome Atlas (TCGA). Functional enrichment analyses and nomogram were performed to explore the potential effects and prognostic performance of the IPS. Furthermore, the RNA-sequence data from our center were used to validate the expression levels of the selected immune genes in BLCA samples.ResultsDiverse proportions of macrophage subtypes were observed between NMIBC and MIBC. Patients with high risk scores had a worse prognosis than patients with low risk scores in training (TCGA) and validation data sets (GSE32894, GSE13507, and GSE48277). The IPS was a useful prognostic factor for patients treated with immunotherapy in the IMvigor210 trial. Hallmarks of multiple oncogenic pathways were significantly enriched in the high risk group. A novel nomogram model was established for prognostic predictions. The dysregulated expression of the selected immune genes between NMIBC and MIBC was also validated in BLCA samples.ConclusionDysregulation of the immune microenvironment promoted the malignant progression from NMIBC to MIBC. The IPS can stratify patients into different risk groups with distinct prognoses and immunotherapeutic susceptibility, thus facilitating personalized immunotherapy.

Negative density-dependent parasitism in a group-living carnivore.

Animals living at high population densities commonly experience greater exposure to disease, leading to increased parasite burdens. However, social animals can benefit immunologically and hygienically from cooperation, and individuals may alter their socio-spatial behaviour in response to infection, both of which could counteract density-related increases in exposure. Consequently, the costs and benefits of sociality for disease are often uncertain. Here, we use a long-term study of a wild European badger population (Meles meles) to investigate how within-population variation in host density determines infection with multiple parasites. Four out of five parasite taxa exhibited consistent spatial hotspots of infection, which peaked among badgers living in areas of low local population density. Combined movement, survival, spatial and social network analyses revealed that parasite avoidance was the likely cause of this negative density dependence, with possible roles for localized mortality, encounter-dilution effects, and micronutrient-enhanced immunity. These findings demonstrate that animals can organize their societies in space to minimize parasite infection, with important implications for badger behavioural ecology and for the control of badger-associated diseases.

Impact of colored motif characteristics on the survivability of passenger airline networks in China

Passenger airline networks are an important agent of social and economic connections between cities, and embody characteristics of complex networks. The study on the survivability of passenger airline networks has positive significance on their healthy and safe development. There have been several in-depth empirical studies on the impact of macrostructural characteristics of complex networks on network survivability, however few studies have focused on the impact of microstructure on network survivability, which is the focus of this paper. As the basic building blocks of the network, colored motifs can distinguish the different functions of nodes or edges in the motif, and then comprehensively depict the network microstructure. We used this characteristic to study the impact of microstructure on network survivability, in this paper. Passenger airline networks of different airlines in China during 2018, were studied, and the three-node and four-node colored motifs of different airline networks were identified. Complex network indexes were used to measure the survivability of airline networks under intentional and random attacks. Multiple linear regression analysis was conducted between the survivability coefficient of each airline network and the concentration of colored motifs to explore the impact of colored motif characteristics on network survivability. The results show that: (1) microscopic topological structures represented by colored motifs in airline networks are closely related to the macro spatial structural modes of airline networks (such as hub and spoke model); (2) vast majority of passenger airline networks in China are more vulnerable to intentional attacks and are robust in the face of random attacks; (3) from the perspective of topological structures of network motifs, motifs with radial and loop structures have positive impacts on network survivability under intentional attacks, while motifs with loop structures had negative impacts on network survivability under random attacks; (4) from the perspective of the type of colored motifs, motifs with a large number of hub nodes, high degree of agglomeration, and strong hub-and-spoke effect can enhance the ability of the network to resist intentional attacks. The agglomeration of non-hub nodes has a positive effect on network survivability under intentional attacks, and a linear structure with hub nodes at both ends can enhance the ability of airline networks to resist random attacks. In actual route planning, adjusting the type of colored motif from the microstructural perspective can be a good means to enhance the survivability of the entire airline network.

Resource dependency and survivability in complex networks

Components in many real-world complex systems depend on each other for the resources required for survival and may die of a shortage. These patterns of dependencies often take the form of a complex network whose structure potentially affects how the resources produced in the system are efficiently shared among its components, which in turn decides a network's survivability. Here we present a simple threshold model that provides insight into this relationship between the network structure and survivability. We show that, as a combined effect of local sharing and finite lifetime of resources, many components in a complex system may die of lack of resources even when a sufficient amount is available in the system. We also obtain a surprising result that although the scale-free networks exhibit a significantly higher survivability compared to their homogeneous counterparts, a vertex in the latter survives longer on average. Finally, we demonstrate that the system's survivability can be substantially improved by changing the way vertices distribute resources among the neighbors. Our work is a step towards understanding the relationship between intricate resource dependencies present in many real-world complex systems and their survivability.

Integration of fiber and FSO network with fault-protection for optical access network

In this paper, we proposed and experimentally demonstrated the integration of optical fiber and free-space optic (FSO) with fault protection for the optical access network. The proposed architecture has a fault protection or self-healing function when a link failure is occurred in the network. Thus, the proposed self-healing architecture is a promising network for improved reliability and survivability of optical network especially for the remote area when the fiber is broken or cut between each remote node (RN) and optical network unit (ONU). Moreover integration of optical fiber with the FSO network is used to increase the coverage range of the broadband wireless network and improve the flexibility of the network. In the experiment, the signal is generated by using the signal generator, and propagates through a hybrid of 25 km SMF, and FSO link and then transmitted into each ONU. Finally, we compare and evaluate the signal transmission performance of channels in terms of bit error rate (BER) and error vector magnitude (EVM) after back-to-back (BTB) transmission, 25 km SMF transmission, and after a hybrid of 25 km SMF with FSO link transmission. The experimental result proves that the hybrid of 25 km SMF with FSO link increases the communication coverage range with a reasonable performance.

Identification of potential prognostic biomarkers for breast cancer using WGCNA and PPI integrated techniques

In this study, we aimed to detect promising prognostic factors of breast cancer and interpreted the relevant mechanisms using an integrated bioinformatics analysis. RNA sequencing profile of breast cancer was downloaded from The Cancer Genome Atlas (TCGA) and the Genotype-Tissue Expression (GTEx) databases, which were combined as a group (TCGA_GTEx). GSE70947 dataset was from Gene Expression Omnibus. Blue and turquoise modules, respectively identified in TCGA_GTEx database and GSE70947 dataset using weighted co-expression network analysis (WGCNA), were both notably associated with breast cancer. By comparing genes in the two significant modules with differentially expressed genes (DEGs), we obtained a set of 40 shared genes, which were mainly enriched in chromosome segregation and mismatch repair pathway. After protein-protein interaction (PPI) network and overall survival analysis, two hub genes EXO1 and KIF4A were extracted from the set of 40 shared genes, which were up-regulated and associated with the dismal outcome of breast cancer patients. There was a notable negative correlation between EXO1 and KIF4A expression and age of breast cancer patients, whereas a positive relationship with two another clinical traits stage and tumor category was detected. Univariate and multivariate Cox regression analysis revealed that the two hub genes could be independent prognostic factors of breast cancer. Mechanistically, gene correlation analysis suggested that EXO1 and KIF4A exerted their oncogenic role via promoting breast cancer cell proliferation. Overall, our findings identify two promising individual prognostic predictors of breast cancer and pave the new way for diagnosis and therapy strategy of breast cancer.

Neuro‐fuzzy and fuzzy schemes for cooperative communication in wireless sensor network: a military battlefield scenario

In the military battlefield, maintaining high survivability of energy constraint wireless sensor network (WSN) when some nodes are destroyed by the foe troops is one of the prominent issues for the researchers. This study proposes the fuzzy and neuro-fuzzy based relay selection schemes for cooperative WSN which reduce the bit error rate (BER) while improving the network lifetime. Meanwhile, the proposed model maintains the uninterrupted communication between military nodes in a warfare situation. The proposed proposed strategies are compared with the maximum residual energy-based relay selection (MRERS), minimum energy consumption-based relay selection (MECRS), and random relay selection (RRS) strategies. The performance of the proposed and existing strategies is evaluated on the basis of BER, network lifetime, number of dead nodes, and average energy of nodes in the network. The simulation results demonstrate that proposed schemes has 13.19–19.28% improvement in BER than the existing strategies. Moreover, 76.00–90.88% network lifetime improves when compared with the MECRS and RRS strategies. However, 6–7.76% is less than MRERS strategy. Furthermore, the results show that network survivability and average network energy is also better when the number of dead nodes in the network increases.

Disintegration of Operational Capability of Heterogeneous Combat Networks Under Incomplete Information

The combat system-of-systems (CSoSs) in high-tech information warfare, composed of different types of combat systems connected through multiple interconnections, can be abstracted as a type of complex heterogeneous network. Research on the disintegration of the operational capability of a heterogeneous combat network (HCN) is of significant military value for optimizing the planning of operation process and improving network survivability in a complex electromagnetic battlefield. Accordingly, this paper presents an integrated framework called HCN operational capability disintegration based on link prediction (OCDLP) for modeling and solving the disintegration problem regarding the operational capability of an HCN. More specifically, a heterogeneous network model of a combat network under incomplete information is first established, considering different types of functional entities and information flows. Based on this model, a link prediction model is then applied to recover the original combat network structure while taking advantage of the observed information. Next, a disintegration evaluation metric of the operational capability of an HCN is elicited to evaluate the attack efficiency after a link prediction. Last, the reliability and effectiveness of the OCDLP are illustrated through a case study. The results provide useful insight into the operation guidance and design of a more resilient CSoSs.

Certain Investigations on Energy-Efficient Fault Detection and Recovery Management in Underwater Wireless Sensor Networks

In recent years, underwater wireless sensor networks (UWSNs) have been widely applied to aquatic and military applications. Network survivability is an essential attribute to be considered in UWSN circumstance and various stratifications like node survivability, connectivity and rapid fault node detection and recovery. However, efficient and accurate fault tolerance mechanisms are required to prolong the network survivability in UWSN. In this research work, the energy-efficient fault detection and recovery management (EFRM) approach is proposed for the UWSN with relatively better network survivability. The hidden Poisson Markov model has been incorporated in EFRM to achieve efficient fault detection throughout the whole network. Thereafter, the recovered node can be selected by using the analytical network process model which facilitates to recover the larger number of nodes in the damaged region. The simulation results manifest that when the fault probability is 40%, the detection accuracy of the proposed EFRM is over 99%, and the false positive rate is below 2%. The detection accuracy is improved by up to 12% when compared with the existing state-of-the-art schemes.

Novel approach to jointly optimize working and spare capacity of survivable optical networks

Abstract As technology advancing day by day, the data rate of optical network is moving towards Tb/s speed. The minimum capacity utilization and survivability are the crucial requirement in such high speed optical networks. This research work presents a new approach to calculate both working and spare capacity with the help of single mathematical programming model named as joint capacity planning model. The working traffic and restored traffic are routed jointly in proposed joint capacity planning model. Therefore the joint capacity planning model required minimum capacity in as compare to other optimization models. To evaluate our model, three example networks are proposed i.e., network A (6 node), network B (8 node) & National science foundation network (14 node). Results of these networks are analyzed and compared. The capacity utilization is optimized by increasing the backup paths of the optical networks. It has also been proved in this manuscript that capacity requirement is dependent on the backup path. The proposed joint capacity model provides fast restoration speed and guaranteed protection for optical network.

Network Survival Strategies of Migrant Entrepreneurs in Large Cities: Analysis of Albanian Firms in Milan

ABSTRACT This paper addresses the role of cultural bias (preference for what is culturally more akin) in the entrepreneurial choice regarding different types of social networks in the context of urban mixed embeddedness. We test empirically the presence and aftermaths of this cultural bias, drawing on evidence from a natural experiment with regard to Albanian ethnic entrepreneurs in the city of Milan, Italy. Namely, these entrepreneurs are exposed to the same mixed urban embeddedness and, when we control for firm characteristics, the only discriminating component explaining their success is their choice of social network. We focus on the choice over three types of social networks, classified according to varying degrees of cultural distance between the network and the entrepreneur: (a) the indigenous population, (b) the local Albanian diaspora, and (c) fellow citizens residing in the country of origin, Albania (i.e., transnational networking). We employ a novel method for reverse engineering of preferences for networking by using a Kaplan-Meier estimator and a propensity-score matching technique. We find that strategic network liaisons with locals is actually the most beneficial social network for ethnic firm performance. However, it is social networking within the culturally closer local Albanian diaspora that is the most common behaviour.

Impact of Mitophagy and Mitochondrial Unfolded Protein Response as New Adaptive Mechanisms Underlying Old Pathologies: Sarcopenia and Non-Alcoholic Fatty Liver Disease.

Mitochondria are the first-line defense of the cell in the presence of stressing processes that can induce mitochondrial dysfunction. Under these conditions, the activation of two axes is accomplished, namely, (i) the mitochondrial unfolded protein response (UPRmt) to promote cell recovery and survival of the mitochondrial network; (ii) the mitophagy process to eliminate altered or dysfunctional mitochondria. For these purposes, the former response induces the expression of chaperones, proteases, antioxidant components and protein import and assembly factors, whereas the latter is signaled through the activation of the PINK1/Parkin and BNIP3/NIX pathways. These adaptive mechanisms may be compromised during aging, leading to the development of several pathologies including sarcopenia, defined as the loss of skeletal muscle mass and performance; and non-alcoholic fatty liver disease (NAFLD). These age-associated diseases are characterized by the progressive loss of organ function due to the accumulation of reactive oxygen species (ROS)-induced damage to biomolecules, since the ability to counteract the continuous and large generation of ROS becomes increasingly inefficient with aging, resulting in mitochondrial dysfunction as a central pathogenic mechanism. Nevertheless, the role of the integrated stress response (ISR) involving UPRmt and mitophagy in the development and progression of these illnesses is still a matter of debate, considering that some studies indicate that the prolonged exposure to low levels of stress may trigger these mechanisms to maintain mitohormesis, whereas others sustain that chronic activation of them could lead to cell death. In this review, we discuss the available research that contributes to unveil the role of the mitochondrial UPR in the development of sarcopenia, in an attempt to describe changes prior to the manifestation of severe symptoms; and in NAFLD, in order to prevent or reverse fat accumulation and its progression by means of suitable protocols to be addressed in future studies.

Joint coding bit‐rate and activity rate optimisation in wireless visual sensor networks

Optimising the coding bit-rates and activity rates of sensor nodes is essential for the functionality and survival of wireless sensor networks as these rates not only affect the amount of information collected by the network, but also affect its power consumption. This study proposes a framework for joint coding bit-rates and activity rates optimisation (CARO) of sensor nodes in wireless visual sensor networks under limited energy constraints. The framework uses the concept of accumulative visual information (AVI) as a measure of the amount of visual information collected from a sensor node. The authors propose two optimisation algorithms for the following two cases: (I) networks with predetermined operation time, where algorithm CARO I maximises the AVI of the network over its predetermined operation time. (II) Best effort networks, where algorithm CARO II maximises the network operation time under constraints on the collected visual information. Simulations show that optimising the rates using CARO maximises the AVI of the network and extends its operation time compared to the straightforward solution when all nodes have equal activity rates. This is because the authors' framework takes into consideration that different nodes in different locations may operate under different conditions and collect information of different significance.

A Pareto frontier for node survivable computer network design problem

A Pareto frontier for node survivable computer network design problem