International Journal of Modeling, Simulation, and Scientific Computing

One of the well-known issues in the field of network routing is the Shortest Path Routing (SPR). The objective is to find the least-cost path with minimum delay and link breaks. Even though there are many algorithms to solve SPR, the cost, as well as link breaks, are indeed more thought-provoking in the real-time application. This paper intends to develop a routing approach that solves the challenges like route establishment and route recovery. The selection of the optimal route is done by adopting a generalized multi-purpose optimization algorithm named Grey Wolf Optimizer. Along with this, this paper adopts Neural Network (NN) to predict the node movements in the ad hoc network. The proposed routing algorithm is compared to the conventional approaches, and the significance of the approach is described clearly.

ScalaLab is a MATLAB-like environment for the Java Virtual Machine (JVM). ScalaLab is based on the Scala programming language. It utilizes an extensive set of Java and Scala scientific libraries and also has access to many native C/C$++$ scientific libraries by using mainly the Java Native Interface (JNI).

The performance of the JVM platform is continuously improved at a fast pace. Today JVM can effectively support demanding high-performance computing and scales well on multicore platforms. However, sometimes optimized native C/$\mathrm{\text{C}}++$ code can yield even better performance, by exploiting low-level programming issues, such as optimization of caches and architecture-dependent instruction sets.

The present work reports some of the experiences that we gained with experiments with both Just in Time (JIT) JVM code and native code. We compare some aspects of Scala and C$++$ that concern the requirements of scientific computing and highlight some strong features of the Scala language that facilitate the implementation of scientific scripting. This paper describes how ScalaLab tries to combine the best features of the JVM with those of the C/C$++$ technology, in order to implement an effective scientific computing environment.

This paper presents a general 3D method to simulate a rotting process in fruits using a visual model for the digital design of the fruits. The global rot parameter and rot resistance parameter are used to control a dynamic simulation of a rotting process. The rot resistance parameters of every point of a 3D fruit model are generated by an interactive designing method that is similar to the traditional sketch drawing tools. We construct a texture of a rot region on a fruit surface by resistance parameters. The degree of rot that is used to control both shape and appearance of rotten fruit surface can be computed by tuning the resistance parameters and global rot parameters. We derive an exponential function to calculate the depression displacement of geometric shape caused by the rot. In order to render a wrinkle on the rot region, we use a normal noise map to modify a normal vector of fruit model and use an isotropic ward BRDF model to represent an appearance of fruit in which the time-varying diffuse reflectance is derived from the real photos. We utilize a linear function to control the dynamic simulation processes including shape deformation and aging appearance. We have evaluated our method by simulating the rotten apple and moldy orange. The results have shown that our method provides a dynamic, real-time and realistic simulation, and it is flexible, fast and of a general character for digital fruit design as a visualization model.

The finite-time convergence problem of an $n$th nonlinear system with unmatched disturbance is primarily studied in this paper. During the recursive procedure, a new finite-time controller is designed and proven by adding a sign function and a power integrator. Meanwhile, a $C^{\mathrm{\text{1}}}$ positive definite and proper Lyapunov function, which satisfies the finite-time Lyapunov stability law, is designed. Finally, the designed finite-time controller is applied to some examples and an application of integrated guidance and control system to test and verify its advantage and practicability.

In order to deal with the dynamic production environment with frequent fluctuation of processing time, robotic cell needs an efficient scheduling strategy which meets the real-time requirements. This paper proposes an adaptive scheduling method based on pattern classification algorithm to guide the online scheduling process. The method obtains the scheduling knowledge of manufacturing system from the production data and establishes an adaptive scheduler, which can adjust the scheduling rules according to the current production status. In the process of establishing scheduler, how to choose essential attributes is the main difficulty. In order to solve the low performance and low efficiency problem of embedded feature selection method, based on the application of Extreme Gradient Boosting model (XGBoost) to obtain the adaptive scheduler, an improved hybrid optimization algorithm which integrates Gini impurity of XGBoost model into Particle Swarm Optimization (PSO) is employed to acquire the optimal subset of features. The results based on simulated robotic cell system show that the proposed PSO-XGBoost algorithm outperforms existing pattern classification algorithms and the newly learned adaptive model can improve the basic dispatching rules. At the same time, it can meet the demand of real-time scheduling.

In this paper, a novel evolutionary algorithm (EA), called pseudo-derivative EA (called PDEA), is proposed. The basic idea of PDEA is to use pseudo-derivative, which is obtained based on the information produced during the evolution, and to help search the solution of optimization problem. The pseudo-derivative drives the search process in a more informed direction. That makes PDEA different from the random optimization methods. The convergence of PDEA is first analyzed based on systems theory. The convergence condition of PDEA is then derived though this condition is too strong to be satisfied. Next, this condition is relaxed based on the entropy theory. Finally, performances of PDEA are evaluated on the benchmark functions and an adaptive liquid level control system of a surge tank. The numeric simulation results show that PDEA is capable of finding the solutions to the optimization problems with good accuracy, reliability, and speed.

Only a small amount of work has been published on the topic of exploiting existing Long-Term Evolution-Advanced (LTE) cellular communication network infrastructure for Unmanned Aerial Vehicles (UAV) data links. This paper documents a modeling and simulation (m&s) framework that has been developed utilizing the powerful OMNeT$++$ simulation tool for assessing the feasibility and effectiveness of this prospect in various UAV scenarios. Using multiple scenarios, we have studied the data rate requirements for communications between small and medium-sized UAVs and base stations. Using this framework, we have shown that the data rate requirements for the links are within the data throughput achieved by LTE networks. The developed framework implements a propagation model endorsed by the 3GPP LTE project team and also accurately models the high mobility of UAVs. The framework is highly configurable and extensible and boasts of automatic aggregation of results and chart plotting. The outcomes of this research may be utilized by industry for rapidly deploying highly mobile, low-cost UAVs in a wide range of applications and scenarios.

In this paper, we studied a two-parameter transmuted model of Log-logistic distribution (LLD) using the quadratic rank transmutation map technique studied by Shaw and Buckley¹ as a new survival model in medical sciences and other applied fields. Statistical properties of Transmuted LLD (TLLD) are discussed comprehensively. Robust measures of skewness and kurtosis of the proposed model have also been discussed along with graphical overview. The estimation of the model parameters is performed by Maximum Likelihood (ML) method followed by a Monte Carlo (MC) simulation procedure to investigate the performance of the ML estimators and the asymptotic confidence intervals of the parameters. Applications of the proposed model to real-life data are also presented.

To make a rapid comfort assessment and a reasonable dynamic parameters choice of wheelchair robots, this paper proposes a dynamic comfort coefficient $\kappa$ and analytically optimizes the cushion damping. Firstly, a traveling vibration model of the occupant-wheelchair system for wheelchair robots running on random roads was created. Secondly, the analytic formula of the occupant RMS (root mean square) acceleration was deduced. Moreover, the dynamic coefficient $\kappa$ was proposed and its influence laws were revealed. Finally, the cushion system optimal damping ratio was calculated based on $\kappa$. The results show that the $\kappa$ value is only determined by the parameters of the occupant-wheelchair system. The smaller the $\kappa$ value is, the better the dynamic comfort is for wheelchair robots running on random roads. By minimizing $\kappa$, the occupant-wheelchair system can achieve a statistically optimal dynamic comfort effect.

Cloud computing supports multitenancy to satisfy the users’ demands for accessing resources and simultaneously it increases revenue for cloud providers. Cloud providers adapt multitenancy by virtualizing the resources, like CPU, network interfaces, peripherals, hard drives and memory using hypervisor to fulfill the demand. In a virtualized environment, many virtual machines (VMs) can run on the same core with the help of the hypervisor by sharing the resources. The VMs running on the same core are the target for the malicious or abnormal attacks like side channel attacks. Among various side channel attacks in cloud computing, cache-based side channel attack is one that leaks private information of the users based on the shared resources. Here, as the shared resource is the cache, a process can utilize the cache usage of another by cache contention. Cache sharing provides a way for the attackers to gain considerable information so that the key used for encryption can be inferred. Discovering this side channel attack is a challenging task. This requires identification of a feature that influences the attack. Even though there are various techniques available in the literature to mitigate such attacks, an effective solution to reduce the cache-based side channel attack is still an issue. Therefore, a novel fuzzy rule-based mechanism is integrated to detect the cache side channel attackers by monitoring the cache data access (CDA). The factor that determines the attack is CDA in a log file created by the framework during authorization. The proposed framework also utilizes certain security properties including ECC and hashing for the privacy preservation and the decision is made with the aid of a fuzzy logic system.

We study a subclass of the May–Leonard stochastic model with an arbitrary, even number of species, leading to the rise of two competing partnerships where individuals are indistinguishable. By carrying out a series of accurate numerical stochastic simulations, we show that alliances compete each other forming spatial domains bounded by interfaces of empty sites. We solve numerically the mean field equations associated with the stochastic model in one and two spatial dimensions. We demonstrate that the stationary interface profile presents topological properties which are related to the asymptotic spatial distribution of species of enemy alliances far away from the interface core. Finally, we introduce a theoretical approach to model the formation of stable interfaces using spontaneous breaking of a discrete symmetry. We show that all the results provided by the soliton topological model, presented here for the very first time, are in agreement with the stochastic simulations and may be used as a tool for understanding the complex biodiversity in nature.

It is well known that Vehicular Adhoc Network (VANET) plays the major role in the field of Intelligent Transport System (ITS) to enhance road safety as well. The entire communication among vehicles is covered in VANETs. Since the number of researches is in progress for the enhancement of VANET model. Usually, the issues arising with this field is the achievement of multi-constrained Quality of Service (QoS) measures. To solve this issue, our paper intends to propose a cost model that considers certain network quality measures like travel, collision, congestion and the awareness about the QoS. Moreover, this paper adopts a renowned algorithm named Water Wave Optimization algorithm (WWO) to find the optimal route. The proposed method analyses its performance over other conventional methods like Lion Algorithm (LA), Genetic Algorithm (GA) and LA with Adaptive Mutation (LAAM) in terms of cost analysis, Convergence analysis and Computational time. Then the analytical results prove the superiority of proposed work in terms of decreased routing cost.

By reaching the first wall of a fusion reactor, charged plasma particles, electrons and ions are recombined into neutral molecules and atoms of hydrogen isotopes. These species recycle back into the plasma volume and participate, in particular, in charge–exchange (cx) collisions with ions. As a result, hot atoms with chaotically directed velocities are generated and some of them hit the wall. Statistical Monte Carlo methods often used to model the behavior of cx atoms are too time-consuming for comprehensive parameter studies. Recently¹ an alternative iteration approach to solve one-dimensional kinetic equation² has been significantly accelerated, by a factor of 30–50, by applying a pass method to evaluate the arising integrals from functions, involving the ion velocity distribution. Here, this approach is used by solving a two-dimensional kinetic equation, describing the transport of cx atoms in the vicinity of an opening in the wall, e.g., the entrance of a duct guiding to a diagnostic installation. To assess the erosion rate and lifetime of the installation, one need to know the energy spectrum of hot cx atoms escaping from the plasma into the duct. Calculations are done for a first mirror of molybdenum under plasma conditions expected in a fusion reactor like DEMO.^3,4 The results of kinetic modeling are compared with those found by using a diffusion approximation⁵ relevant for cx atoms if the time between cx collisions with ions is much smaller than the time till the ionization of atoms by electrons. The present more exact kinetic consideration predicts a mirror erosion rate by a factor of 2 larger than the approximate diffusion approach.