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In this article, we present least fractional nonlinearity for exhibiting chaos in a memristor-based hyper-chaotic multi-stable hidden system. When implementing memristor-based systems, distinct dimensions/order define the memristor nonlinearity. In this work, the memristor dimension has been changed fractionally to identify the lowest order of nonlinearity required to induce chaos in a proposed system. The two-parameter frequency scanning helps in understanding both oscillation and non-oscillation regimes. The system fractional nonlinearity strength will help in deeper understanding of mathematical modelling and control. In addition, multistability and hidden oscillations were thoroughly investigated in the proposed system. The current work combines analytical, numerical, and experimental methods to demonstrate the system dynamics. [ABSTRACT FROM AUTHOR]

The device was invented to sense the variations in the deployed Environment, which takes different dimensions in its functionality. The basic operation does not change; it is the same surveillance, gathering and alert. Human intervention in all places is not possible and efficient monitoring in all circumstances cannot be done manually. Wireless Sensor Networks give the solution for the above-specified problem, continuous efficient monitoring and alerting on time without human intervention in any circumstances. Deploying WSNs and extracting efficient performance requires a strong technology backup. However, it's a machine in logical connectivity that may face several technical issues while transferring the gathered data. It has to be rectified, and efficient service to be provided in the deployed application. Finding the safest and fastest path is one of the critical tasks in the WSN. To achieve that, Bio-Inspired Computing will be used as a tool for designing the protocol to attain the fastest reliable network, even if it deals with the other problems in WSN, such as efficient energy utilization from the battery. In such a way, the Paper is proposed based on the exceptional and exciting behavior of one of the living things, which shook the entire world for almost two years in all aspects, and even a few countries are still seeking a way to come back from its impact, the reason for global lockdown, born with the crown, founder of social distancing, which is popularly known as "Corona" the virus. [ABSTRACT FROM AUTHOR]

This article discusses the utilisation of a Chua oscillator with a memristor to produce chaos with minimal nonlinearity. The memristor, a device that changes its flux or charges over time, has its nonlinear strength altered fractionally to determine the lowest-order memristor nonlinearity for generating chaos. An experimental analog circuit in real-time has been constructed. A linear parameter varying (LPV) approach, incorporating a suitable Lyapunov functional (LK) method, has been introduced to find new sufficient conditions for the robust stability of the resulting closed-loop system through linear matrix inequalities (LMIs). By observing the behaviour of the system without control, it is possible to understand the basic characteristics of chaotic oscillations and how they are affected by changes in the fractional order. These results can then be used as a starting point to study the effectiveness of various control techniques, such as feedback control, in reducing chaos and stabilising the system of this article. The efficiency of the cost-function-based control scheme is evaluated using the simulation results and relevant applications are addressed. [ABSTRACT FROM AUTHOR]

This article addresses the study of a photovoltaic system for type-2 interval fuzzy models via event-triggered control (ETC). Compared to similar works initiated in the references, the necessary part of modeling the ETC for the photovoltaic system ( P V ) is to produce the maximum path which should be followed to guarantee the most extreme power activity. The system models are expected to depend on uncertain parameters, which are mostly experienced in the real dynamical system. To describe the P V system with event-triggered communication delay, the behavior of a nonlinear system can be addressed by using the interval type-2 (IT2) Takagi–Sugeno (T–S) fuzzy rules with lower and upper membership functions. In this regard, we construct the suitable Lyapunov– Krasovskii functional (LKF) and integral inequalities to achieve the stability conditions and expand the maximum sampling period of the closed-loop system. The main purpose of this study is to design the event-triggered mechanism such that the resulting closed-loop system is asymptotically stable and to reduce the communication burdens of the P V system. For this, a sufficient condition is derived for the proposed system in the form of linear matrix inequalities (LMIs). Finally, simulation results are given to demonstrate the suitability and merits of the newly suggested techniques. [ABSTRACT FROM AUTHOR]

Cloud computing technology helps to resolve the problem in storage management by providing virtual resources to the end users. But, the overloading of virtual machines results in degradation of performances as well as it increases in the energy consumption of the virtual machines. Several techniques were used to determine the workloads of the cloud and then apply the migration algorithm for efficient utilization of resources. But, the process depends on the past outputs and only few step ahead predictions. Most of the techniques allocate the resources based on all the attributes. This results in higher processing time for the allocation. Hence, in this, an attribute based resource allocation is proposed to allocate and utilize the resources effectively based on the user demands. The concept of virtualization is to reduce the cost of individual hardware setups to run processes. In cloud computing, virtualization processes effectively utilize resources and improve services. The modified Principal component analysis and relief is used for the attribute selection. Then, the selected attribute is processed with the hybrid Cauchy particle swarm algorithm for the allocation of resources. The proposed method is tested google cluster dataset and its performance is evaluated in terms of migration count and power consumption. The proposed method performance is compared with the automated migration technique (ALM) and forecast based migration technique (CF-LA). The proposed method outperforms both the existing technique by reducing the power consumption and the migration count between the virtual machines. Hence, the proposed MPCA and relief based CPSO is best for allocating the resources dynamically in the cloud. [ABSTRACT FROM AUTHOR]

This paper focuses on the reachable set estimation for synchronizing of complex-valued neural networks (CVNNs) using an event-triggered (ET) approach and cyber-attacks. The system parameters are set up using Markovian switching rules. The proposed controller effectively saves the communication resources for the designed CVNNs. The main objective of this paper is to find an ellipsoid that can contain the state trajectory of the system as small as possible in the presence of control. From a physics point of view, the system can be likened to a dynamic system subjected to external perturbations, where the goal is to contain the trajectory of the system’s state within a bounded region, similar to confining particle motion in phase space. To achieve this objective, we propose a novel approach based on the reachable set technique, which allows us to obtain an ellipsoid that contains the state trajectory of the system while minimizing its size. Utilizing the standard Lyapunov–Krasovskii functional (LKF), integral inequality approaches, some sufficient stability formed in terms of linear matrix inequalities (LMIs) are derived for the synchronization of CVNNs under the ET scheme, which can be solved using MATLAB’s YALMIP toolbox. These conditions ensure that the states of the CVNNs converge to zero and that the synchronization error is bounded. Finally, numerical simulation results are provided to demonstrate the practicality and effectiveness of the proposed theoretical results. [ABSTRACT FROM AUTHOR]

Broadcasting on Vehicular Ad Hoc Networks (VANET) is quickly becoming a hot topic. One of the complications presented by this topic is that it is limited to Vehicle-to-Vehicle (V2V) situations rather than employing communications networks (such as broadband connections). Intelligent Transportation Systems (ITS) are primarily focused on the distribution of emergency messages as well as basic information. The IEEE has recognized Wireless Access in Vehicular Environment (WAVE) as the standard for this message distribution. IEEE 802.11p and Dedicated Short Range Communication (DSRC) are two Medium Access Control (MAC) layer protocols supported by this WAVE. At high vehicle density scenarios, the increasing rate of broadcasting will slow down the performance of the broadcasting method and increase the packet loss ratio. In this paper, various broadcasting algorithms are compared in terms of Quality of Service (QoS) to analyze the best algorithm which achieves high packet delivery ratio and improve the performance at high vehicle density scenario. A new broadcasting algorithm Traffic Condition Aware Customized Beacon Broadcasting (TCA-CBB) method is introduced and compared with other methods. At the end of the performance evaluation between the broadcasting methods, it is proved that the proposed TCA-CBB algorithms shows best results. [ABSTRACT FROM AUTHOR]

Internet of Things (IoT) based applications are being evolved in multiple fields to provide enhanced service to the world. IoT is a recent computing concept interconnecting the wired and wireless networks through the internet. Most mobile devices function only in an ad-hoc manner. Infrastructureless networks are called ad-hoc networks. IoT is an effective technology to utilize in Cognitive Radio Mobile Ad-hoc Network (CRMANET) instantaneously. The protocols that are developed for common ad-hoc networks will never suit for IoT-based-CRMANET because the delay they face is inversely proportional with real-time applications. Hence, there exists a need for designing and developing a better routing protocol that suits IoT-based ad-hoc networks. Multi adaptive route indicates the optimum cum efficient path which is selected when the priority of the node gets changed or failed, it may be due to problems that arise in nodes or network components. Multi-adaptive routes make sure the connectivity of the network and its operations before sending the data packet. This paper focuses on developing a Multi-Adaptive Routing Protocol (MARP) inspired by natural characteristics of fish for IoT-based ad-hoc networks to minimize the delay and the energy consumption to extend a network lifetime. NS3 simulation results indicate that MARP gives its best performance than other routing protocols in terms of Throughput, Packet Delivery Ratio, Packet Drop Ratio, Delay and Energy Consumption. [ABSTRACT FROM AUTHOR]

In this article, we discuss the dynamics of a Leslie–Gower ratio-dependent predator–prey model incorporating fear in the prey population. Moreover, the Allee effect in the predator growth is added into account from both biological and mathematical points of view. We explore the influence of the Allee and fear effect on the existence of all positive equilibria. Furthermore, the local stability properties and possible bifurcation behaviors of the proposed system about positive equilibria are discussed with the help of trace and determinant values of the Jacobian matrix. With the help of Sotomayor's theorem, the conditions for existence of saddle-node bifurcation are derived. Also, we show that the proposed system admits limit cycle dynamics, and its stability is discussed with the value of first Lyapunov coefficient. Moreover, the numerical simulations including phase portrait, one- and two-parameter bifurcation diagrams are performed to validate our important findings. [ABSTRACT FROM AUTHOR]

In recent times, the foremost challenging task in implementing software defined networking is to choose appropriate locations for controllers to reduce latency amongst switches and controllers in wide area networks. Based on the existing investigations, most of the studies concentrate on reduction of packet propagation latency, however propagation latency is an essential contributor of overall latency amongst switches and associated controllers. In this research work, investigation is carried out on most significant contributor of latency, such as end-to-end latency and queuing based latency of controllers. So as to reduce end-to-end delay, the network partitioning idea is anticipated and an efficient node balancing cluster with partitioner algorithm using Markov decision process (NB-PAMDP) is modeled for network partitioning. NB-PAMDP can ensure that every partition is competent to reduce maximum amount of end-to-end delay amongst switches and controllers. In order to diminish queuing delay of controllers, an appropriate multiple controller placement are then designed for sub networks. Extensive simulation was carried out in NS-3 simulator under a network topology from Internet topology. Results demonstrate that the anticipated model can resourcefully diminish maximum latency or delay amongst switches and corresponding controllers. [ABSTRACT FROM AUTHOR]

This paper investigates singularly perturbed parabolic partial differential equations with delay in space, and the right end plane is an integral boundary condition on a rectangular domain. A small parameter is multiplied in the higher order derivative, which gives boundary layers, and due to the delay term, one more layer occurs on the rectangle domain. A numerical method comprising the standard finite difference scheme on a rectangular piecewise uniform mesh (Shishkin mesh) of N r × N t elements condensing in the boundary layers is suggested, and it is proved to be parameter-uniform. Also, the order of convergence is proved to be almost two in space variable and almost one in time variable. Numerical examples are proposed to validate the theory. [ABSTRACT FROM AUTHOR]

This study is concerned about the stabilization for delayed fuzzy neutral-type system (DFNTS) with uncertain parameters under intermittent control. Firstly, by constructing the augmented Lyapunov-Krasovskii functional (LKF) about different time delays along with single and double auxillary function-based integral inequalities (SAFBII, and DAFBII, respectively), a new class of delay-dependent adequate conditions are proposed, so that the robust fuzzy neutral-type system under consideration is guaranteed to be globally asymptotically stable (GAS). Secondly, the intermittent control (IC) is introduced to stabilize the system with mixed time-varying delays. In the view of inferred adequate conditions, the IC parameters are determined as for the arrangement of linear matrix inequalities (LMIs). It is noted that the strategies exploited in this work are apart from the other methods engaged in the literature, and the proposed conditions are less conservative. Finally, numerical examples are given to demonstrate the effectiveness of the developed techniques in this work. One of the practical applications is single-link robot arm (SLRA) model to show the viability and benefits of the structured intermittent control. [ABSTRACT FROM AUTHOR]

Dynamical analysis of a delayed tri-trophic food chain consisting of prey, an intermediate, and a top predator is investigated in this paper. The additive Allee effect is introduced in the prey population, and it is assumed that there is a time lag due to the gestation effect in the intermediate predator. The interference among the prey and the intermediate predator is according to Holling type II, while the interaction between the intermediate and top predators follows the Crowley–Martin functional response. The local stability and bifurcation analysis of the proposed model at the interior equilibrium point are studied. Numerical simulations are provided to ensure the mathematical results. [ABSTRACT FROM AUTHOR]

This paper concentrates on the extended dissipativity and event-triggered synchronization for T–S fuzzy Markovian jumping delayed stochastic neural networks with leakage delays and fault-tolerant control. We present an event-triggered communication scheme, which utilizes the effect of transmission delay with different failure rates. After giving a foundation to the stochastic model, the paper establishes some fundamental results on quadratically stable and extended dissipativity utilizing the Lyapunov functional, free-weight matrices, as well as the relationship between time-varying delay and leakage delays. The explicit expression of the desired controller gains and event-triggered parameters can be obtained by solving the established LMIs. The novel extended dissipative inequality contains several weighting matrices, by converting the weighting matrices in a new performance index, and the extended dissipativity will be degraded to the H ∞ performance, L 2 - L ∞ performance, passivity and dissipativity, respectively. Finally, interesting numerical examples are given to show the effectiveness of the theoretical results. [ABSTRACT FROM AUTHOR]

This paper is concerned with the problem of event triggered finite time H ∞ boundedness of uncertain Markov jump neural networks with distributed time varying delays. To reduce the limited network bandwidth, an event triggered scheme is proposed in this paper. The main objective of this paper is to design the event triggered scheme, such that the proposed neural networks have finite time boundedness with admissible uncertainties. The integral terms in the derivative of the Lyapunov–Krasovskii functional are handled by the Wirtinger and Auxillary function based inequality techniques. The proposed conditions are represented by linear matrix inequalities to determine the finite time stability. The advantage of the method in this paper over some existing ones is shown by comparing the results with the existing results. At the end, numerical examples are given to verify the efficiency of the proposed method among them one example was supported by real-life application of the benchmark problem. [ABSTRACT FROM AUTHOR]

In this paper, we are concerned with the robust H∞ problem for a class of discrete-time neural networks with uncertainties. Under a weak assumption on the activation functional, some novel summation inequality techniques and using a new Lyapunov-Krasovskii (L-K) functional, a delay-dependent condition guaranteeing the robust asymptotically stability of the concerned neural networks is obtained in terms of a Linear Matrix Inequality(LMI). It is shown that this stability condition is less conservative than some previous ones in the literature. The controller gains can be derived by solving a set of LMIs. Finally, two numerical examples result are given to illustrate the effectiveness of the developed theoretical results. [ABSTRACT FROM AUTHOR]

This paper investigates decentralized event-triggered stability analysis of neutral-type BAM neural networks with Markovian jump parameters and mixed time varying delays. We apply the decentralized event triggered approach to the bidirectional associative memory (BAM) neural networks to reduce the network traffic and the resource of computation. A bidirectional associative memory neural networks is constructed with the mixed time varying delays and Markov process parameters. The criteria for the asymptotically stability are proposed by using with the Lyapunov-Krasovskii functional method, reciprocal convex property and Jensen’s inequality. Stability condition of neutral-type BAM neural networks with Markovian jump parameters and mixed delays is established in terms of linear matrix inequalities. Finally three numerical examples are given to demonstrate the effectiveness of the proposed results [ABSTRACT FROM AUTHOR]

This paper is concerned with the stability problem for a class of decentralized event-triggered exponential stability for uncertain delayed genetic regulatory networks (GRNs) with Markov jump parameters and distributed delays. In order to reduce the information communication burden, the decentralized event-triggered mechanism is proposed in this paper. Exponential stability for the proposed GRNs are studied by the Lyapunov method and the matrix inequality techniques. Some new sufficient conditions are obtained to ensure the global exponential stability of the proposed GRNs. Furthermore, the proposed LMI results are computationally efficient which are easy to be verified via the Matlab LMI toolbox. In addition, four numerical examples are provided to illustrate the effectiveness of the theoretical results. [ABSTRACT FROM AUTHOR]

Segmentation plays vital role in speech recognition systems. An automatic segmentation of Tamil speech into syllable has been carried out using Vowel Onset Point (VOP) and Spectral Transition Measure (STM). VOP is a phonetic event used to identify the beginning point of the vowel in speech signals. Spectral Transition Measure is performed to find the significant spectral changes in speech utterances. The performance of the proposed syllable segmentation method is measured corresponding to manual segmentation and compared with the exiting syllable method using VOP and Vowel Offset Point (VOF). The result of the experiments shows the effectiveness of the proposed system. [ABSTRACT FROM AUTHOR]

In mobile ad hoc networks (MANETs), the packet loss can be caused either by link failure or by node failure. Moreover, the techniques for selecting the bypass route and avoiding congestion in the bypass route are rarely handled. To overcome these, in this paper, we propose an adaptive reliable and congestion control routing protocol to resolve congestion and route errors using bypass route selection in MANETs. The multiple paths are constructed. Among which, the shortest paths are found for efficient data transmission. The congestion is detected on the basis of utilization and capacity of link and paths. When a source node detects congestion on a link along the path, it distributes traffic over alternative paths by considering the path availability threshold and using a traffic splitting function. If a node cannot resolve the congestion, it signals its neighbors using the congestion indication bit. By using simulation, we show that that the proposed protocol is reliable and achieves more throughput with reduced packet drops and overhead. [ABSTRACT FROM AUTHOR]

In the current study, we conduct an investigation into the Hyers–Ulam stability of linear fractional differential equation using the Riemann–Liouville derivatives based on fractional Fourier transform. In addition, some new results on stability conditions with respect to delay differential equation of fractional order are obtained. We establish the Hyers–Ulam–Rassias stability results as well as examine their existence and uniqueness of solutions pertaining to nonlinear problems. We provide examples that indicate the usefulness of the results presented. [ABSTRACT FROM AUTHOR]