Network Disconnection Research Articles

Cluster-based location service schemes in VANETs: current state, challenges and future directions

Vehicular Ad hoc Networks (VANETs) have drawn incredible interest in both academic and industrial sectors due to their potential applications and services. Vehicles’ position plays a significant role in many location-based applications and services such as public emergency, vehicles tracking, resource discovery, traffic monitoring and position-based routing. A location service is used to keep up-to-date records of current positions of vehicles. However, locating vehicles’ positions and maintaining an accurate view of the entire network are quite challenging tasks due to the high number of nodes, and high and fast nodes mobility which results in rapid topological changes and sudden network disconnections. In the past literature, various location-based services have been proposed to solve the above mentioned issues. Moreover, the cluster-based location service schemes have gained a growing interest due to their advantages over non-cluster-based schemes. The cluster-based schemes improve the network scalability, reduce the communications overhead and resolve the mobility issues within the clusters preventing them from propagating in the whole network. Therefore, this paper presents the taxonomy of the existing location service schemes, inspects the cluster-based location service by highlighting their strengths and limitations, and provides a comparison between location-based clustering and application specific clustering such as the one used in routing, information dissemination, channel access management and security. In addition, the existing clustering schemes, challenges and future directions for efficient cluster-based location service are also discussed.

Framework for calculating seismic fragility function of urban road networks: A case study on Tangshan City, China

The aim of this work is to present a method for calculating seismic fragility function of urban road network. In this paper, urban road system is simplified to a planar network. The spatial correlation of seismic ground motions is considered. The damage probability of network edge is determined by the fragility function of single road section. By repeating simulation, a large number of samples of post-earthquake road network are obtained. Their damage states are classified as minor, moderate, extensive and complete by piece number and diameter of the maximal piece. The seismic fragility function of road network is assumed in the form of lognormal cumulative distribution function and its parameters are identified by fitting the fragility function to the exceeding probability of the damage states. To demonstrate the practicality of the proposed method, an application to the urban road network of Tangshan City is performed. The case study indicates that the rare earthquake may cause the disconnection and fragmentation of the road network with high probability. The proposed framework is a valuable contribution to the seismic performance evaluation of urban road system and provides engineers and practitioners with a tool to design road network in high seismic hazard zone.

PMCAR: proactive mobility and congestion aware route prediction mechanism in IoMT for delay sensitive medical applications to ensure reliability in COVID-19 pandemic situation

PurposeInclusion of mobile nodes (MNs) in Internet of Things (IoT) further increases the challenges such as frequent network disconnection and intermittent connectivity because of high mobility rate of nodes. This paper aims to propose a proactive mobility and congestion aware route prediction mechanism (PMCAR) to find the congestion free route from leaf to destination oriented directed acyclic graph root (DODAG-ROOT) which considers number of MNs connected to a static node. This paper compares the proposed technique (PMCAR) with RPL (OF0) which considers the HOP-COUNT to determine the path from leaf to DODAG-ROOT. The authors performed a simulation with the proposed technique in MATLAB to present the benefits in terms of packet loss and energy consumption.Design/methodology/approachIn this pandemic situation, mobile and IoT play major role in predicting and preventing the CoronaVirus Disease of 2019 (COVID-19). Huge amount of computations is happening with the data generated in this pandemic with the help of mobile devices. To route the data to remote locations through the network, it is necessary to have proper routing mechanism without congestion. In this paper, PMCAR mechanism is introduced to achieve the same. Internet of mobile Things (IoMT) is an extension of IoT that consists of static embedded devices and sensors. IoMT includes MNs which sense data and transfer it to the DODAG-ROOT. The nodes in the IoMT are characterised by low power, low memory, low computing power and low bandwidth support. Several challenges are encountered by routing protocols defined for IPV6 over low power wireless personal area networks to ensure reduced packet loss, less delay, less energy consumption and guaranteed quality of service.FindingsThe results obtained shows a significant improvement compared to the existing approach such as RPL (OF0). The proposed route prediction mechanism can be applied largely to medical applications which are delay sensitive, particularly in pandemic situations where the number of patients involved and the data gathered from them flows towards a central root for analysis. Support of data transmission from the patients to the doctors without much delay and packet loss will make the response or decisions available more quickly which is a vital part of medical applications.Originality/valueThe computational technologies in this COVID-19 pandemic situation needs timely data for computation without delay. IoMT is enabled with various devices such as mobile, sensors and wearable devices. These devices are dedicated for collecting the data from the patients or any objects from different geographical location based on the predetermined time intervals. Timely delivery of data is essential for accurate computation. So, it is necessary to have a routing mechanism without delay and congestion to handle this pandemic situation. The proposed PMCAR mechanism ensures the reliable delivery of data for immediate computation which can be used to make decisions in preventing and prediction.

Structural Disconnection of the Tool Use Network after Left Hemisphere Stroke Predicts Limb Apraxia Severity.

Producing a tool use gesture is a complex process drawing upon the integration of stored knowledge of tools and their associated actions with sensory–motor mechanisms supporting the planning and control of hand and arm actions. Understanding how sensory–motor systems in parietal cortex interface with semantic representations of actions and objects in the temporal lobe remains a critical issue and is hypothesized to be a key determinant of the severity of limb apraxia, a deficit in producing skilled action after left hemisphere stroke. We used voxel-based and connectome-based lesion-symptom mapping with data from 57 left hemisphere stroke participants to assess the lesion sites and structural disconnection patterns associated with poor tool use gesturing. We found that structural disconnection among the left inferior parietal lobule, lateral and ventral temporal cortices, and middle and superior frontal gyri predicted the severity of tool use gesturing performance. Control analyses demonstrated that reductions in right-hand grip strength were associated with motor system disconnection, largely bypassing regions supporting tool use gesturing. Our findings provide evidence that limb apraxia may arise, in part, from a disconnection between conceptual representations in the temporal lobe and mechanisms enabling skilled action production in the inferior parietal lobule.

Chronic inflammation and stress-hormones: a common pathway of cognitive disorders in ageing

Here we present the data on examining inter-connections cytokine network and stress hormones in senile vascular dementia by assessing systemic cytokine levels for IL-1β, IL-6, IL-10, TNFα, IFNγ as well as hormones cortisol, adrenocorticotropic hormone (ACTH), epinephrine, norepinephrine and dopamine in 23 subjects with vascular dementia and 40 individuals without overt cognitive impairment. It was found, that the concentrations of IL-6, TNFα, epinephrine and dopamine were significantly increased, whereas those for IL-1β, IL-10, ACTH and norepinephrine were decreased in elderly people with dementia compared to healthy aging. In addition, virtually no inter-connection between cytokine, sympathoadrenal and hypothalamicpituitary (HPA-axis) axis was observed in vascular dementia highlighted by no significant correlation within the cytokine network. However, a single positive intrahormonal link for cortisol-ACTH and two positive links between IFNγ and cortisol/adrenaline level were detected. In general, vascular dementia was featured by marked inflammatory reaction, excessive activation of stress hormone production and disconnection of cytokine network, HPA-axis and the sympathoadrenal medullary system.

A Generic Scenario on Urban Sustainability of a Historical City Center

In discussion on modern urban development issues, many researches have focused on those newly expanded areas, yet few researches have scrutinized what contributes to the vibrant life of the historical Central Business District (CBD) in inner cities. This research has examined a declined old city centre in central Taiwan by deploying Space Syntax analysis to verify possible contributions of parts-whole street network disconnection to the death of CBD in inner cities. The research findings suggest that linearity and critical street segments being properly integrated with the whole arterial street network could be crucial for future city planning.

Network disconnection games: A game theoretic approach to checkpoint evaluation in networks

We study a Network Security question that consists of learning where are the most important checkpoints to intercept an adversary traveling from an origin to a destination. For that we define a cooperative game where every player controls an arc, and is able to place a checkpoint on it. We assume that the adversary is trying to travel from s to t. If the adversary crosses a checkpoint there is no certainty that he will be detected, therefore the value of a coalition should reflect the number of checkpoints, in the coalition, that the adversary has to cross (the more, the better). This suggests defining the value of a coalition S as the maximum number of disjoint st-cuts included in S; this is a lower bound for the number of checkpoints in S that the adversary has to cross. The adversary can choose any shortest path (minimum cardinality) from s to t, so in any particular coalition one cannot know the exact number of checkpoints that he will cross, and thus we propose to work with a lower bound instead. We give a polynomial combinatorial algorithm for computing the nucleolus of this game. The nucleolus is an allocation of resources to each arc that reflects the contribution of each checkpoint to the common objective of detecting the adversary. The larger values in the nucleolus indicate the more important locations.

A delay analysis for the delivery of downstream messages in a sparse VANET

ABSTRACT In this paper, we analyze the delay of the message delivery from a vehicle to a downstream vehicular gateway in a sparse vehicle ad hoc network (VANET). Several research efforts have previously been devoted to the calculations of the rehealing delay in the restoration of a network disconnection; however, most of them focus only on the delivery of upstream messages. In this paper, we analyze the end-to-end delay of downstream message deliveries. This analysis is essential for many applications, e.g., aggressive driving identification, that requires regular collection of vehicle data, such as speed, location, etc. In our analysis, we calculate the first two moments of the rehealing delay, then utilize the central limit theorem (CLT) to derive the end-to-end delay distribution. Simulation results confirm that our analysis is very accurate for both the mean and the variance of the rehealing delay. It is observed from numerical results that opposite-directional traffic intensity plays a more important role in deciding the end-to-end delay than same-directional traffic intensity, and that comparing between up- and down-stream message deliveries, the former has a slightly shorter delay than the latter when traffic intensity is low, but they are comparable when it is high.

Staged Magnetic Resonance-Guided Laser Interstitial Thermal Therapy for Hypothalamic Hamartoma: Analysis of Ablation Volumes and Morphological Considerations.

Hypothalamic hamartomas (HH) are a challenging pathology that cause gelastic seizures. Magnetic Resonance Imaging-guided Laser Interstitial Thermal Therapy (MRgLITT) offers a safe and effective treatment for HHs via a minimally invasive technique. To determine how clinical outcome correlates to residual tumor volume and surgical strategy by analyzing radiographic data and reconstructing volumetric imaging. Clinical and radiographic information of 58 pediatric patients who underwent MRgLITT for HH with at least 6 mo of follow-up were retrospectively reviewed. MR imaging was volumetrically reconstructed to analyze the impact of hamartoma and ablation volumes on outcome. Primary outcome measure was freedom from gelastic seizures. Eighty-one percent of patients were completely free of gelastic seizures at last follow-up; of 22 patients with secondary nongelastic epilepsy, 15 were free of additional seizures. Postoperative complication rate was low. There was no significant difference in gelastic seizure outcome related to pre- or postoperative hamartoma size. Residual hamartoma percentage in those free of gelastic seizures was 43% compared to 71% in those with continued seizures (P=.021). Larger hamartomas required multiple ablations to achieve seizure freedom. This large series of patients confirms the safety and efficacy of MRgLITT for pediatric HH and describes morphological considerations that predict success. Our data suggest that complete ablation of the lesion is not necessary, and that the focus should be on appropriate disconnection of the epileptogenic network. We have found that a staged approach to hamartoma ablation allows adequate disconnection of the hamartoma while mitigating risk to surrounding structures.

Task-Oriented Intelligent Networking Architecture for the Space–Air–Ground–Aqua Integrated Network

As one of the most promising networks, the space–air–ground–aqua integrated network (SAGAIN) has the characteristics of wide coverage and large information capacity, which can meet various requests from users in different domains. With the rapid growth of data and information generated by the Internet of Things (IoT), SAGAIN has received much attention in recent years. However, the existing network architectures are not capable of providing personalized network services according to different task types in SAGAIN. Besides, they cannot deal with many problems in SAGAIN well, such as heterogeneous network disconnection, high network delay, intermittent interruption, and unbalanced network load. In this article, in order to solve the abovementioned problems, we propose a novel architecture for SAGAIN named task-oriented intelligent networking architecture (TOINA). First, we apply the edge-cloud computing technology and network domain division in TOINA to realize intelligent networking and reduce the latency. Second, the task-oriented networking method is proposed to provide personalized network services and increase network intelligence. Third, we intend to leverage the information center network (ICN) paradigm to build the SAGAIN and optimize the content naming rules. Furthermore, a preprocessing layer was added in the network protocol stack to perform the heterogeneous network convergence in SAGAIN. In addition, some security technologies related to network architecture are considered in SAGAIN. This article presents the background, rationale, and benefits of the TOINA for SAGAIN. Besides, a specific case is studied to illustrate the network architecture work process further.

Changes in PGC-1α/SIRT1 Signaling Impact on Mitochondrial Homeostasis in Amyloid-Beta Peptide Toxicity Model.

Alzheimer's disease (AD) is a neurodegenerative disorder characterized by cognitive impairment that increasingly afflicts the elderly population. Soluble oligomers (AβOs) has been implicated in AD pathogenesis: however, the molecular events underlying a role for Aβ are not well understood. We studied the effects of AβOs on mitochondrial function and on key proteins that regulate mitochondrial dynamics and biogenesis in hippocampal neurons and PC-12 cells. We find that AβOs treatment caused a reduction in total Mfn1 after a 2 h exposure (42 ± 11%); while DRP1 increased at 1 and 2 h (205 ± 22% and 198 ± 27%, respectively), correlating to changes in mitochondrial morphology. We also observed that SIRT1 levels were reduced after acute and chronic AβOs treatment (68 ± 7% and 77 ± 6%, respectively); while PGC-1α levels were reduced with the same time treatments (68 ± 8% and 67 ± 7%, respectively). Interestingly, we found that chronic treatment with AβOs increased the levels of pSIRT1 (24 h: 157 ± 18%), and we observed changes in the PGC-1α and p-SIRT1 nucleus/cytosol ratio and SIRT1-PGC-1α interaction pattern after chronic exposure to AβOs. Our data suggest that AβOs induce important changes in the level and localization of mitochondrial proteins related with the loss of mitochondrial function that are mediated by a fast and sustained SIRT1/PGC-1α complex disruption promoting a “non-return point” to an irreversible synaptic failure and neuronal network disconnection.

Multiple Network Disconnection in Anosognosia for Hemiplegia.

Anosognosia for hemiplegia (AHP) is a complex syndrome whose neural correlates are still under investigation. One hypothesis, mainly based on lesion mapping studies, is that AHP reflects a breakdown of neural systems of the right hemisphere involved in motor function. However, more recent theories have suggested that AHP may represent a disorder of cognitive systems involved in belief updating, self-referential or body processing. Two recent studies, using a method to estimate the degree of white matter disconnection from lesions, have indeed shown that patients with AHP suffer from damage of several long-range white matter pathways in association cortex. Here, we use a similar indirect disconnection approach to study a group of patients with motor deficits without anosognosia (hemiparesis or hemiplegia, HP, n = 35), or motor deficits with AHP (n = 28). The HP lesions came from a database of stroke patients, while cases of AHP were selected from the published literature. Lesions were traced into an atlas from illustrations of the publications using a standard method. There was no region in the brain that was more damaged in AHP than HP. In terms of structural connectivity, AHP patients had a similar pattern of disconnection of motor pathways to HP patients. However, AHP patients also showed significant disconnection of the right temporo-parietal junction, right insula, right lateral and medial prefrontal cortex. These associative cortical regions were connected through several white matter tracts, including superior longitudinal fasciculus III, arcuate, fronto-insular, frontal inferior longitudinal, and frontal aslant. These tracts connected regions of different cognitive networks: default, ventral attention, and cingulo-opercular. These results were not controlled for clinical variables as concomitant symptoms and other disorders of body representation were not always available for co-variate analysis. In conclusion, we confirm recent studies of disconnection demonstrating that AHP is not limited to dysfunction of motor systems, but involves a much wider set of large-scale cortical networks.

Adaptive fault-tolerant control for nonlinear multi-agent systems with DoS attacks

This paper studies the fault tolerant control (FTC) problem for nonlinear multi-agent systems (MASs), in the presence of denial-of-service (DoS) attacks and actuator faults. In order to compensate for the effect of actuator faults, nonlinear dynamics and uncertainties, a distributed control strategy is presented by designing adaptive schemes and state-feedback control gains. The uncertainties are assumed to satisfy the integral quadratic constraints (IQCs), which is a more general presentation than the norm-bounded conditions. The aim of DoS attacks is to impede the communication among agents. A switching mechanism is proposed to ensure the tolerance to network disconnections. Based on Lyapunov stability theory and the average dwell time (ADT) approach, it is proved that the MASs can achieve mean square consensus by using the proposed controller. Finally, two illustrative examples are provided to verify the effectiveness of this method.

Metabolic lesion-deficit mapping of human cognition

In theory the most powerful technique for functional localization in cognitive neuroscience, lesion-deficit mapping is in practice distorted by unmodelled network disconnections and strong 'parasitic' dependencies between collaterally damaged ischaemic areas. High-dimensional multivariate modelling can overcome these defects, but only at the cost of commonly impracticable data scales. Here we develop lesion-deficit mapping with metabolic lesions-discrete areas of hypometabolism typically seen on interictal 18F-fluorodeoxyglucose PET imaging in patients with focal epilepsy-that inherently capture disconnection effects, and whose structural dependence patterns are sufficiently benign to allow the derivation of robust functional anatomical maps with modest data. In this cross-sectional study of 159 patients with widely distributed focal cortical impairments, we derive lesion-deficit maps of a broad range of psychological subdomains underlying affect and cognition. We demonstrate the potential clinical utility of the approach in guiding therapeutic resection for focal epilepsy or other neurosurgical indications by applying high-dimensional modelling to predict out-of-sample verbal IQ and depression from cortical metabolism alone.

Research on the Low Voltage Ride Through Capability of Hybrid Modular Multilevel Converters

With the increase of the penetration rate of wind power in the power system, the latest grid-connection rules require that the inverter of Wind Turbine should have the capability of low voltage ride through (LVRT). This paper aims at a Wind Turbine based on hybrid modular multilevel converter (MMC). Firstly, the mathematical model of the system is established in the stationary coordinate system. In order to ensure that the Wind Turbine can operate without network disconnection during grid fault, this paper adopts a corresponding hierarchical control strategy, the strategy applies to hybrid modular multilevel converter and provide control flexibility, and realize the LVRT of a Wind Turbine, an electromagnetic transient model of the hybrid MMC based Wind Turbine is simulated in PSCAD/EMTDC and the results verify the feasibility and effectiveness of the proposed scheme and control strategy.

Surgical disconnection of epilepsy network correlates with improved outcomes

PurposeA novel software algorithm combining non-invasive EEG and resting state functional MRI data to map networks of cortex correlated to epileptogenic tissue was used to map an epilepsy network non-invasively. The relationship between epilepsy network connectivity and outcomes after surgery was investigated using this non-invasive and non-concurrent modeling algorithm. MethodScalp EEG and resting state functional MRI were acquired for nineteen patients with temporal lobe epilepsy. The hypothetical irritative zone was mapped, and resting state functional MRI data was used to model regions functionally correlated with the irritative zone. Epilepsy network connectivity was measured in patient with temporal lobe epilepsy (n = 19) both pre- and post-operatively. Temporal networks were also mapped in healthy control participants (n = 6). ResultsThirteen of nineteen patients (68 %) were seizure free after 20.3 ± 4.8 months. Epilepsy network connectivity within the temporal lobe was significantly higher among patients with temporal lobe epilepsy compared to the healthy control patients (p < 0.05). Disconnection of the epilepsy network was significantly higher in patients who were seizure free. Using spearman rho analyses, neuropsychological function after surgery was found to be relatively better in patients with higher degree of epilepsy network disconnection. ConclusionsThe magnitude of network disconnection after surgery was strongly associated with increased rates of seizure freedom and relatively better neuropsychological measures of memory and naming function. It was shown that seizure-free outcomes and relatively improved neuropsychological function correlated with surgical disconnection of a highly synchronous epilepsy network.

A Survey on Routing Protocols for Delay and Energy-Constrained Cognitive Radio Networks

The ever-growing demand for higher network data rates, lower delay, and conservative energy consumption at reduced costs, to support Internet-of-things (IoT) communications, has pushed wireless technologies into a new frontier. The growing demand for such technologies can be attributed to several factors, such as the massive number of the upcoming bandwidth-hungry IoT applications and the enormous number of - often battery-powered - devices expected to connect to the network. Cognitive Radio Networks (CRNs) can play a significant role in future generations of mobile-communication technologies by providing dynamic access to underutilized licensed bands. However, battery-operated devices, which communicate delay-sensitive data over multihop links, impose serious energy-delay limits. In such CRN-based IoT communications, as one device depletes its energy, network disconnectivity may arise, which can degrade the network efficiency. Therefore, building a reactive routing protocol to recover from any sudden link breakage is necessary to maintain prolonged network connectivity. This paper provides a comprehensive survey of CRN routing protocols that are based on two essential metrics, namely, packet delay, energy consumption, or both, while excluding all other CRN routing protocols. The survey is meant to support the designers of future CRN-based IoT communication frameworks with a detailed comparative survey, which targets the most relevant proposed routing protocols, including the specifics of the routing metrics, implemented spectrum awareness strategy, and employed medium-access control standard along with the simulator tool used for performance evaluation. In addition, this survey finds that the majority of cognitive radio routing protocols address either delay or energy consumption, but only a few consider a joint delay-energy metric, which suits delay-sensitive IoT applications running on energy-constrained devices.

Secure and Energy-Aware Heuristic Routing Protocol for Wireless Sensor Network

Wireless Sensor Networks (WSNs) achieve much attention from various domains because of its easy maintenance, self-configuration, and scalability characteristics. It is comprised of small-sized sensors that interact with the Internet of Things (IoT) for observing and recording the physical conditions. The sensor nodes are autonomous and construct inter-communication topology with each other in an ad-hoc manner. However, the main restrictions of sensor nodes are their finite resources for energy management, data storage, transmission, and processing power. Different solutions have been addressed by researchers to overcome network performance due to bounded limitations of such battery-powered nodes, however, equalize the energy consumption and maintain the network throughput are the main research problems. Furthermore, due to the compromised nodes, the data is more prone to security vulnerabilities. Therefore, their security over the unpredictable network is other research concerns. Thus, the aim of this research article to propose a secure and energy-aware heuristic-based routing (SEHR) protocol for WSN to detect and prevent compromising data with efficient performance. Firstly, the proposed protocol makes use of an artificial intelligence-based heuristic analysis to accomplish a reliable, and intellectual learning scheme. Secondly, it protects the transmissions against adversary groups to attain security with the least complexity. Moreover, the route maintenance strategy is also achieved by using traffic exploration to reduce link failures and network dis-connectivity. The simulation results demonstrated the SEHR protocol improves the efficacy for network throughput by an average of 18%, packet drop ratio by 42%, end-to-end delay by 26%, energy consumption by 36%, faulty routes by 38%, network overhead by 44%, and computational overhead by 43% in dynamic scenarios as compared to existing work.

Enhancing Rescue Operations With Virtualized Mobile Multimedia Services in Scarce Resource Devices

The aim of this article is to present an architecture to support reconfigurable multimedia services for a practical emergency environment use case of rescue operations. Specifically, radio communication and video surveillance services are provided by means of a small device carried by a mobile vehicle. This solution is validated by implementing a digital mobile radio (DMR) standard radio hotspot and a video streaming server in an unmanned aerial vehicle (UAV) that conveys a device with scarce resources in order to minimize power consumption. To achieve a fast and flexible deployment of the envisioned services, a virtualization-based approach is proposed. Namely, a Kubernetes orchestrator is used to manage the life-cycle of services deployed on a small resource device, endowing the architecture with scalability and management flexibility. This article describes the executed performance tests that measured key parameters such as deployment time and recovery time after disconnection. Highly promising results were obtained, showing that the proposed architecture can be deployed in less than 4 minutes and can recover from network disconnections in less than 10 seconds. Thus, the performance, reliability and flexibility of the overall solution are demonstrated.

A security routing algorithm against selective forwarding attacks in scale-free networks

Abstract Scale-free networks are vulnerable to the selective forwarding attacks where the legitimated data packet is discarded by malicious nodes. And it is easy for non-balanced energy consumption to happen and prematurely make the network disconnection. This paper proposes the multiple attribute decision making model, which has the balanced characteristic of various factors. In the model, the node’s energy transmission efficiency, load and packet loss rate are defined as node attributes, and the weight value of each attribute is calculated by relative entropy. Furthermore, according to the decision values of the forward neighbors, the optimal routing node is determined. The simulation experiment results show that the routing algorithm based on decision model can effectively avoid the nodes suffered from selective forward attacks, improve the energy utilization and prolong the lifetime.