| 1. |
- Ackelh, A.S., et al.
(author)
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Preface to "modeling with measures"
- 2015
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In: Mathematical Biosciences and Engineering. - : American Institute of Mathematical Sciences (AIMS). - 1547-1063 .- 1551-0018. ; 12:2
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Journal article (peer-reviewed)
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| 2. |
- Ackleh, Azmy S., et al.
(author)
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High resolution finite difference schemes for a size structured coagulation-fragmentation model in the space of radon measures
- 2023
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In: Mathematical Biosciences and Engineering. - : American Institute of Mathematical Sciences. - 1547-1063 .- 1551-0018. ; 20:7, s. 11805-11820
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Journal article (peer-reviewed)abstract
- In this paper, we develop explicit and semi-implicit second-order high-resolution finite difference schemes for a structured coagulation-fragmentation model formulated on the space of Radon measures. We prove the convergence of each of the two schemes to the unique weak solution of the model. We perform numerical simulations to demonstrate that the second order accuracy in the Bounded-Lipschitz norm is achieved by both schemes.
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| 3. |
- Ackleh, Azmy S., et al.
(author)
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Special issue: Mathematical modeling with measures
- 2020
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In: Mathematical Biosciences and Engineering. - : American Institute of Mathematical Sciences. - 1547-1063 .- 1551-0018. ; :3, s. 2451-2452
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Journal article (peer-reviewed)
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| 4. |
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| 5. |
- Bronstein, Samuel, et al.
(author)
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Bayesian inference in epidemics : linear noise analysis
- 2023
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In: Mathematical Biosciences and Engineering. - : American Institute of Mathematical Sciences. - 1547-1063 .- 1551-0018. ; 20:2, s. 4128-4152
-
Journal article (peer-reviewed)abstract
- This paper offers a qualitative insight into the convergence of bayesian parameter inference in a setup which mimics the modeling of the spread of a disease with associated disease measurements. Specifically, we are interested in the Bayesian model’s convergence with increasing amounts of data under measurement limitations. Depending on how weakly informative the disease measurements are, we offer a kind of ‘best case’ as well as a ‘worst case’ analysis where, in the former case, we assume that the prevalence is directly accessible, while in the latter that only a binary signal corresponding toa prevalence detection threshold is available. Both cases are studied under an assumed so-called linear noise approximation as to the true dynamics. Numerical experiments test the sharpness of our results when confronted with more realistic situations for which analytical results are unavailable.
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| 6. |
- Cirillo, Emilio, et al.
(author)
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A lattice model for active–passive pedestrian dynamics : a quest for drafting effects
- 2020
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In: Mathematical Biosciences and Engineering. - : American Institute of Mathematical Sciences. - 1547-1063 .- 1551-0018. ; 17:1, s. 460-477
-
Journal article (peer-reviewed)abstract
- We study the pedestrian escape from an obscure room using a lattice gas model with twospecies of particles. One species, called passive, performs a symmetric random walk on the lattice,whereas the second species, called active, is subject to a drift guiding the particles towards the exit.The drift mimics the awareness of some pedestrians of the geometry of the room and of the location ofthe exit. We provide numerical evidence that, in spite of the hard core interaction between particles –namely, there can be at most one particle of any species per site – adding a fraction of active particlesin the system enhances the evacuation rate of all particles from the room. A similar effect is alsoobserved when looking at the outgoing particle flux, when the system is in contact with an externalparticle reservoir that induces the onset of a steady state. We interpret this phenomenon as a discretespace counterpart of the drafting effect typically observed in a continuum set–up as the aerodynamicdrag experienced by pelotons of competing cyclists.
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| 7. |
- Corbetta, Alessandro, et al.
(author)
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Parameter estimation of social forces in pedestrian dynamics models via a probabilistic method
- 2015
-
In: Mathematical Biosciences and Engineering. - : American Institute of Mathematical Sciences. - 1547-1063 .- 1551-0018. ; 12:2, s. 337-356
-
Journal article (peer-reviewed)abstract
- Focusing on a specific crowd dynamics situation, including real life experiments and measurements, our paper targets a twofold aim: (1) we present a Bayesian probabilistic method to estimate the value and the uncertainty (in the form of a probability density function) of parameters in crowd dynamic models from the experimental data; and (2) we introduce a fitness measure for the models to classify a couple of model structures (forces) according to their fitness to the experimental data, preparing the stage for a more general model-selection and validation strategy inspired by probabilistic data analysis. Finally, we review the essential aspects of our experimental setup and measurement technique.
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| 8. |
- Dootio, Mazhar Ali, et al.
(author)
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Secure and failure hybrid delay enabled a lightweight RPC and SHDS schemes in Industry 4.0 aware IIoHT enabled fog computing
- 2021
-
In: Mathematical Biosciences and Engineering. - 1547-1063 .- 1551-0018. ; 19:1, s. 513-536
-
Journal article (peer-reviewed)abstract
- These days, the Industrial Internet of Healthcare Things (IIT) enabled applications have been growing progressively in practice. These applications are ubiquitous and run onto the different computing nodes for healthcare goals. The applications have these tasks such as online healthcare monitoring, live heartbeat streaming, and blood pressure monitoring and need a lot of resources for execution. In IIoHT, remote procedure call (RPC) mechanism-based applications have been widely designed with the network and computational delay constraints to run healthcare applications. However, there are many requirements of IIoHT applications such as security, network and computation, and failure efficient RPC with optimizing the quality of services of applications. In this study, the work devised the lightweight RPC mechanism for IIoHT applications and considered the hybrid constraints in the system. The study suggests the secure hybrid delay scheme (SHDS), which schedules all healthcare workloads under their deadlines. For the scheduling problem, the study formulated this problem based on linear integer programming, where all constraints are integer, as shown in the mathematical model. Simulation results show that the proposed SHDS scheme and lightweight RPC outperformed the hybrid for IIoHT applications and minimized 50% delays compared to existing RPC and their schemes.
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| 9. |
- Dootio, Mazhar Ali, et al.
(author)
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Secure and failure hybrid delay enabled a lightweight RPC and SHDS schemes in Industry 4.0 aware IIoHT enabled fog computing
- 2021
-
In: Mathematical Biosciences and Engineering. - : Arizona State University. - 1547-1063 .- 1551-0018. ; 19:1, s. 513-536
-
Journal article (peer-reviewed)abstract
- These days, the Industrial Internet of Healthcare Things (IIT) enabled applications have been growing progressively in practice. These applications are ubiquitous and run onto the different computing nodes for healthcare goals. The applications have these tasks such as online healthcare monitoring, live heartbeat streaming, and blood pressure monitoring and need a lot of resources for execution. In IIoHT, remote procedure call (RPC) mechanism-based applications have been widely designed with the network and computational delay constraints to run healthcare applications. However, there are many requirements of IIoHT applications such as security, network and computation, and failure efficient RPC with optimizing the quality of services of applications. In this study, the work devised the lightweight RPC mechanism for IIoHT applications and considered the hybrid constraints in the system. The study suggests the secure hybrid delay scheme (SHDS), which schedules all healthcare workloads under their deadlines. For the scheduling problem, the study formulated this problem based on linear integer programming, where all constraints are integer, as shown in the mathematical model. Simulation results show that the proposed SHDS scheme and lightweight RPC outperformed the hybrid for IIoHT applications and minimized 50% delays compared to existing RPC and their schemes.
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| 10. |
- Du, Xiaoyu, et al.
(author)
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The porous cantilever beam as a model for spinal implants : Experimental, analytical and finite element analysis of dynamic properties
- 2023
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In: Mathematical Biosciences and Engineering. - : American Institute of Mathematical Sciences. - 1547-1063 .- 1551-0018. ; 20:4, s. 6273-6293
-
Journal article (peer-reviewed)abstract
- Investigation of the dynamic properties of implants is essential to ensure safety and compatibility with the host's natural spinal tissue. This paper presents a simplified model of a cantilever beam to investigate the effects of holes/pores on the structures. Free vibration test is one of the most effective methods to measure the dynamic response of a cantilever beam, such as natural frequency and damping ratio. In this study, the natural frequencies of cantilever beams made of polycarbonate (PC) containing various circular open holes were investigated numerically, analytically, and experimentally. The experimental data confirmed the accuracy of the natural frequencies of the cantilever beam with open holes calculated by finite element and analytical models. In addition, two finite element simulation methods, the dynamic explicit and modal dynamic methods, were applied to determine the damping ratios of cantilever beams with open holes. Finite element analysis accurately simulated the damped vibration behavior of cantilever beams with open holes when known material damping properties were applied. The damping behavior of cantilever beams with random pores was simulated, highlighting a completely different relationship between porosity, natural frequency and damping response. The latter highlights the potential of finite element methods to analyze the dynamic response of arbitrary and complex structures, towards improved implant design.
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| 11. |
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| 12. |
- Gerlee, Philip, 1980, et al.
(author)
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Diffusion-limited tumour growth: Simulations and analysis.
- 2010
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In: Mathematical Biosciences and Engineering. - : American Institute of Mathematical Sciences (AIMS). - 1551-0018 .- 1547-1063. ; 7:2, s. 385-400
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Journal article (peer-reviewed)abstract
- The morphology of solid tumours is known to be affected by the background oxygen concentration of the tissue in which the tumour grows, and both computational and experimental studies have suggested that branched tumour morphology in low oxygen concentration is caused by diffusion-limited growth. In this paper we present a simple hybrid cellular automaton model of solid tumour growth aimed at investigating this phenomenon. Simulation results show that for high consumption rates (or equivalently low oxygen concentrations) the tumours exhibit branched morphologies, but more importantly the simplicity of the model allows for an analytic approach to the problem. By applying a steady-state assumption we derive an approximate solution of the oxygen equation, which closely matches the simulation results. Further, we derive a dispersion relation which reveals that the average branch width in the tumour depends on the width of the active rim, and that a smaller active rim gives rise to thinner branches. Comparison between the prediction of the stability analysis and the results from the simulations shows good agreement between theory and simulation.
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| 13. |
- Khamnei, Hossein Jabbari, et al.
(author)
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Modeling income distribution : An econophysics approach
- 2023
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In: Mathematical Biosciences and Engineering. - : AIMS Press. - 1547-1063 .- 1551-0018. ; 20:7, s. 13171-13181
-
Journal article (peer-reviewed)abstract
- This study aims to develop appropriate models for income distribution in Iran using the econophysics approach for the 2006–2018 period. For this purpose, the three improved distributions of the Pareto, Lognormal, and Gibbs-Boltzmann distributions are analyzed with the data extracted from the target household income expansion plan of the statistical centers in Iran. The research results indicate that the income distribution in Iran does not follow the Pareto and Lognormal distributions in most of the study years but follows the generalized Gibbs-Boltzmann distribution function in all study years. According to the results, the generalized Gibbs-Boltzmann distribution also properly fits the actual data distribution and could clearly explain the income distribution in Iran. The generalized Gibbs-Boltzmann distribution also fits the actual income data better than both Pareto and Lognormal distributions
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| 14. |
- Lakhan, Abdullah, et al.
(author)
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Cost-Efficient Service Selection and Execution and Blockchain-Enabled Serverless Network for Internet of Medical Things
- 2021
-
In: Mathematical Biosciences and Engineering. - : American Institute of Mathematical Sciences (AIMS). - 1547-1063 .- 1551-0018. ; 18:6, s. 7344-7362
-
Journal article (peer-reviewed)abstract
- These days, healthcare applications on the Internet of Medical Things (IoMT) network have been growing to deal with different diseases via different sensors. These healthcare sensors are connecting to the various healthcare fog servers. The hospitals are geographically distributed and offer different services to the patients from any ubiquitous network. However, due to the full offloading of data to the insecure servers, two main challenges exist in the IoMT network. (i) Data security of workflows healthcare applications between different fog healthcare nodes. (ii) The cost-efficient and QoS efficient scheduling of healthcare applications in the IoMT system. This paper devises the Cost-Efficient Service Selection and Execution and Blockchain-Enabled Serverless Network for Internet of Medical Things system. The goal is to choose cost-efficient services and schedule all tasks based on their QoS and minimum execution cost. Simulation results show that the proposed outperform all existing schemes regarding data security, validation by 10%, and cost of application execution by 33% in IoMT.
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| 15. |
- Lakhan, Abdullah, et al.
(author)
-
Cost-efficient service selection and execution and blockchain-enabled serverless network for internet of medical things
- 2021
-
In: Mathematical Biosciences and Engineering. - 1547-1063 .- 1551-0018. ; 18:6, s. 7344-7362
-
Journal article (peer-reviewed)abstract
- These days, healthcare applications on the Internet of Medical Things (IoMT) network have been growing to deal with different diseases via different sensors. These healthcare sensors are connecting to the various healthcare fog servers. The hospitals are geographically distributed and offer different services to the patients from any ubiquitous network. However, due to the full offloading of data to the insecure servers, two main challenges exist in the IoMT network. (i) Data security of workflows healthcare applications between different fog healthcare nodes. (ii) The cost-efficient and QoS efficient scheduling of healthcare applications in the IoMT system. This paper devises the Cost-Efficient Service Selection and Execution and Blockchain-Enabled Serverless Network for Internet of Medical Things system. The goal is to choose cost-efficient services and schedule all tasks based on their QoS and minimum execution cost. Simulation results show that the proposed outperform all existing schemes regarding data security, validation by 10%, and cost of application execution by 33% in IoMT.
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| 16. |
- Niu, Qinwang, et al.
(author)
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Toward the Internet of Medical Things : Architecture, trends and challenges
- 2024
-
In: Mathematical Biosciences and Engineering. - : American Institute of Mathematical Sciences. - 1547-1063 .- 1551-0018. ; 21:1, s. 650-678
-
Journal article (peer-reviewed)abstract
- In recent years, the growing pervasiveness of wearable technology has created new opportunities for medical and emergency rescue operations to protect users' health and safety, such as cost-effective medical solutions, more convenient healthcare and quick hospital treatments, which make it easier for the Internet of Medical Things (IoMT) to evolve. The study first presents an overview of the IoMT before introducing the IoMT architecture. Later, it portrays an overview of the core technologies of the IoMT, including cloud computing, big data and artificial intelligence, and it elucidates their utilization within the healthcare system. Further, several emerging challenges, such as cost-effectiveness, security, privacy, accuracy and power consumption, are discussed, and potential solutions for these challenges are also suggested.
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| 17. |
- Singh, Sachin Kumar, et al.
(author)
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Soil erosion control from trash residues at varying land slopes under simulated rainfall conditions
- 2023
-
In: Mathematical Biosciences and Engineering. - : American Institute of Mathematical Sciences. - 1551-0018. ; 20:6, s. 11403-11428
-
Journal article (peer-reviewed)abstract
- Trash mulches are remarkably effective in preventing soil erosion, reducing runoff-sediment transport-erosion, and increasing infiltration. The study was carried out to observe the sediment outflow from sugar cane leaf (trash) mulch treatments at selected land slopes under simulated rainfall conditions using a rainfall simulator of size 10 m × 1.2 m × 0.5 m with the locally available soil material collected from Pantnagar. In the present study, trash mulches with different quantities were selected to observe the effect of mulching on soil loss reduction. The number of mulches was taken as 6, 8 and 10 t/ha, three rainfall intensities viz. 11, 13 and 14.65 cm/h at 0, 2 and 4% land slopes were selected. The rainfall duration was fixed (10 minutes) for every mulch treatment. The total runoff volume varied with mulch rates for constant rainfall input and land slope. The average sediment concentration (SC) and sediment outflow rate (SOR) increased with the increasing land slope. However, SC and outflow decreased with the increasing mulch rate for a fixed land slope and rainfall intensity. The SOR for no mulch-treated land was higher than trash mulch-treated lands. Mathematical relationships were developed for relating SOR, SC, land slope, and rainfall intensity for a particular mulch treatment. It was observed that SOR and average SC values correlated with rainfall intensity and land slope for each mulch treatment. The developed models' correlation coefficients were more than 90%.
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| 18. |
- Turova, Tatyana
(author)
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Structural phase transitions in neural networks.
- 2014
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In: Mathematical Biosciences and Engineering. - : American Institute of Mathematical Sciences (AIMS). - 1547-1063 .- 1551-0018. ; 11:1, s. 139-148
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Journal article (peer-reviewed)abstract
- A model is considered for a neural network that is a stochastic process on a random graph. The neurons are represented by "integrate-and-fire" processes. The structure of the graph is determined by the probabilities of the connections, and it depends on the activity in the network. The dependence between the initial level of sparseness of the connections and the dynamics of activation in the network was investigated. A balanced regime was found between activity, i.e., the level of excitation in the network, and inhibition, that allows formation of synfire chains.
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| 19. |
- Tyrcha, Joanna, et al.
(author)
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NETWORK INFERENCE WITH HIDDEN UNITS
- 2014
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In: Mathematical Biosciences and Engineering. - : American Institute of Mathematical Sciences (AIMS). - 1547-1063 .- 1551-0018. ; 11:1, s. 149-165
-
Journal article (peer-reviewed)abstract
- We derive learning rules for finding the connections between units in stochastic dynamical networks from the recorded history of a visible subset of the units. We consider two models. In both of them, the visible units are binary and stochastic. In one model the hidden units are continuous-valued, with sigmoidal activation functions, and in the other they are binary and stochastic like the visible ones. We derive exact learning rules for both cases. For the stochastic case, performing the exact calculation requires, in general, repeated summations over an number of configurations that grows exponentially with the size of the system and the data length, which is not feasible for large systems. We derive a mean field theory, based on a factorized ansatz for the distribution of hidden-unit states, which offers an attractive alternative for large systems. We present the results of some numerical calculations that illustrate key features of the two models and, for the stochastic case, the exact and approximate calculations.
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| 20. |
- Yu, Huangjing, et al.
(author)
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Enhanced Aquila optimizer algorithm for global optimization and constrained engineering problems
- 2022
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In: Mathematical Biosciences and Engineering. - : AIMS Press. - 1547-1063 .- 1551-0018. ; 19:12, s. 14173-14211
-
Journal article (peer-reviewed)abstract
- The Aquila optimizer (AO) is a recently developed swarm algorithm that simulates the hunting behavior of Aquila birds. In complex optimization problems, an AO may have slow convergence or fall in sub-optimal regions, especially in high complex ones. This paper tries to overcome these problems by using three different strategies: restart strategy, opposition-based learning and chaotic local search. The developed algorithm named as mAO was tested using 29 CEC 2017 functions and five different engineering constrained problems. The results prove the superiority and efficiency of mAO in solving many optimization issues.
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| 21. |
- Zahid, Noman, et al.
(author)
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AI-driven adaptive reliable and sustainable approach for internet of things enabled healthcare system
- 2022
-
In: Mathematical Biosciences and Engineering. - : Arizona State University. - 1547-1063 .- 1551-0018. ; 19:4, s. 3953-3971
-
Journal article (peer-reviewed)abstract
- Artificial Intelligence (AI) driven adaptive techniques are viable to optimize the resources in the Internet of Things (IoT) enabled wearable healthcare devices. Due to the miniature size and ability of wireless data transfer, Body Sensor Networks (BSNs) have become the center of attention in current medical media technologies. For a long-term and reliable healthcare system, high energy efficiency, transmission reliability, and longer battery lifetime of wearable sensors devices are required. There is a dire need for empowering sensor-based wearable techniques in BSNs from every aspect i.e., data collection, healthcare monitoring, and diagnosis. The consideration of protocol layers, data routing, and energy optimization strategies improves the efficiency of healthcare delivery. Hence, this work presents some key contributions. Firstly, it proposes a novel avant-garde framework to simultaneously optimize the energy efficiency, battery lifetime, and reliability for smart and connected healthcare. Secondly, in this study, an Adaptive Transmission Data Rate (ATDR) mechanism is proposed, which works on the average constant energy consumption by varying the active time of the sensor node to optimize the energy over the dynamic wireless channel. Moreover, a Self-Adaptive Routing Algorithm (SARA) is developed to adopt a dynamic source routing mechanism with an energy-efficient and shortest possible path, unlike the conventional routing methods. Lastly, real-time datasets are adopted for intensive experimental setup for revealing pervasive and cost-effective healthcare through wearable devices. It is observed and analysed that proposed algorithms outperform in terms of high energy efficiency, better reliability, and longer battery lifetime of portable devices.
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| 22. |
- Zardari, Nawaz Ali, et al.
(author)
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Adaptive mobility-aware and reliable routing protocols for healthcare vehicular network
- 2022
-
In: Mathematical Biosciences and Engineering. - : Arizona State University. - 1547-1063 .- 1551-0018. ; 19:7, s. 7156-7177
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Journal article (peer-reviewed)abstract
- Healthcare vehicles such as ambulances are the key drivers for digital and pervasive remote care for elderly patients. Thus, Healthcare Vehicular Ad Hoc Network (H-VANET) plays a vital role to empower the digital and Intelligent Transportation System (ITS) for the smart medical world. Quality of Service (QoS) performance of vehicular communication can be improved through the development of a robust routing protocol having enhanced reliability and scalability. One of the most important issues in vehicular technology is allowing drivers to make trustworthy decisions, therefore building an efficient routing protocol that maintains an appropriate level of Quality of Service is a difficult task. Restricted mobility, high vehicle speeds, and continually changing topologies characterize the vehicular network environment. This paper contributes in four ways. First, it introduces adaptive, mobility-aware, and reliable routing protocols. The optimization of two routing protocols which are based on changing nature topologies of the network used for vehicular networks has been performed, amongst them, Optimized Link State Routing (Proactive) and Ad-hoc on Demand Distance Vector (Reactive) are considered for Packet Delivery Ratio (PDR) and throughput. Furthermore, Packet Loss Ratio (PLR), and end-to-end (E2E) delay parameters have also been calculated. Second, a healthcare vehicle system architecture for elderly patients is proposed. Third, a Platoon-based System model for routing protocols in VANET is proposed. Fourth, a dynamic channel model has been proposed for the vehicle to vehicle communication using IEEE8011.p. To optimize the QoS, the experimental setup is conducted in a discrete Network Simulator (NS-3) environment. The results reveal that the AODV routing protocol gives better performance for PDR as well as for PLR and the communication link established is also reliable for throughput. Where OLSR produces a large average delay. The adoptive mobility-aware routing protocols are potential candidates for providing Intelligent Transportation Systems with acceptable mobility, high reliability, high PDR, low PLR, and low E2E delay.
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