Search

In an Underwater Wireless Sensor Network (UWSN), extreme energy loss is carried out by the early expiration of sensor nodes and causes a reduction in efficiency in the submerged acoustic sensor system. Systems based on clustering strategies, instead of each node sending information by itself, utilize cluster heads to collect information inside the clusters for forwarding collective information to sink. This can effectively minimize the total energy loss during transmission. The environment of UWSN is 3D architecture-based and follows a complex hierarchical clustering strategy involving its most effecting unique parameters such as propagation delay and limited transmission bandwidth. Round base clustering strategy works in rounds, where each round comprises three fundamental stages: cluster head selection, grouping or node association, and data aggregation followed by forwarding data to the sink. In UWSN, the energy consumed during the formation of clusters has been considered casually or completely evaded in the previous works. In this paper, the cluster head setup period has been considered the main contributor to extra energy utilizer. A numerical channel model is proposed to compute extra energy. It is performed by using a UWSN broad model. The results have shown that extra maximum energy consumption is approximately 12.9 percent of the system total energy consumed in information transmissions. [ABSTRACT FROM AUTHOR]

This study presents the current state of research on multi-factor authentication. Authentication is one of the important traits in the security domain as it ensures that legitimate users have access to the secure resource. Attacks on authentication occur even before digital access is given, but it becomes quite challenging with remote access to secure resources. With increasing threats to single authentication schemes, 2Factor and later multi-factor authentication approaches came into practice. Several studies have been done in the multi-factor authentication discipline, and most of them proposed the best possible approaches, but there are very limited studies in the area that can comprehend all these innovative and effective approaches. Using Web of Science data of the research publications on the topic, the study adopted the bibliometric approach to find the evolution of authentication in the security domain, especially multi-factor authentication. This study finds the impact of the research in the selected domain using bibliometric analysis. This research also identifies the key research trends that most of the researchers are paying attention to. The highest number of publications on multi-factor authentication were published in 2019 while the highest number of citations were received in 2014. United States, India, and China are the leading countries publishing the most on multi-factor authentication. [ABSTRACT FROM AUTHOR]

In existing meta-heuristic algorithms, population initialization forms a huge part towards problem optimization. These calculations can impact variety and combination to locate a productive ideal arrangement. Especially, for perceiving the significance of variety and intermingling, different specialists have attempted to improve the presentation of meta-heuristic algorithms. Particle Swarm Optimization (PSO) algorithm is a populace-based, shrewd stochastic inquiry strategy that is motivated by the inherent honey bee swarm food search mechanism. Population initialization is an indispensable factor in the PSO algorithm. To improve the variety and combination factors, rather than applying the irregular circulation for the introduction of the populace, semi-arbitrary successions are more helpful. This examination presents a thorough overview of the different PSO initialization approaches which are dependent on semi-arbitrary successions systems. In this precise review, the best in class in the populace instatement is uncovered. The procedures are classified by utilizing a theoretical model that parts the cycle of populace introduction into two phases: that is, right now expressly or certainly utilized for reinstatement in every single present approach. The deliberate investigation unveils the potential examination zones of populace introduction and, furthermore, research holes, despite the fact that the fundamental center is to give the headings to future upgrade and advancement around there. This paper gives a deliberate study identified with this calculated model for the cutting edge of exploration, which is talked about in the predefined writing to date. The study is envisioned to be useful in examining the PSO algorithm in detail for the specialist. Likewise, the paper finds the proficiency of numerous quasi-random sequences (QRS) based on initialization approaches by looking at their exhibition analyzed for sixteen notable benchmark test problems. [ABSTRACT FROM AUTHOR]

CSTR (Continuous stirred tank reactor) is employed in process control and chemical industries to improve response characteristics and system efficiency. It has a highly nonlinear characteristic that includes complexities in its control and design. Dynamic performance is compassionate to change in system parameters which need more effort for planning a significant controller for CSTR. The reactor temperature changes in either direction from the defined reference value. It is important to note that the intensity of chemical actions inside the CSTR is dependent on the various levels of temperature, and deviation from reference values may cause degradation of biomass quality. Design and implementation of an appropriate adaptive controller for such a nonlinear system are essential. In this paper, a conventional Proportional Integral Derivative (PID) controller is designed. The conventional techniques to deal with constraints suffer severe limitations like it has fixed controller parameters. Hence, A novel method is applied for computing the PID controller parameters using a swarm algorithm that overcomes the conventional controller’s limitation. In the proposed technique, PID parameters are tuned by Particle Swarm Optimization (PSO). It is not easy to choose the suitable objective function to design a PID controller using PSO to get an optimal response. In this article, a multi-objective function is proposed for PSO based controller design of CSTR. [ABSTRACT FROM AUTHOR]

Bat algorithm (BA) is an eminent meta-heuristic algorithm that has been widely used to solve diverse kinds of optimization problems. BA leverages the echolocation feature of bats produced by imitating the bats' searching behavior. BA faces premature convergence due to its local search capability. Instead of using the standard uniform walk, the Torus walk is viewed as a promising alternative to improve the local search capability. In this work, we proposed an improved variation of BA by applying torus walk to improve diversity and convergence. The proposed. Modern Computerized Bat Algorithm (MCBA) approach has been examined for fifteen well-known benchmark test problems. The finding of our technique shows promising performance as compared to the standard PSO and standard BA. The proposed MCBA, BPA, Standard PSO, and Standard BA have been examined for well-known benchmark test problems and training of the artificial neural network (ANN). We have performed experiments using eight benchmark datasets applied from the worldwide famous machine-learning (ML) repository of UCI. Simulation results have shown that the training of an ANN with MCBA-NN algorithm tops the list considering exactness, with more superiority compared to the traditional methodologies. The MCBA-NN algorithm may be used effectively for data classification and statistical problems in the future. [ABSTRACT FROM AUTHOR]

In the design and planning of next-generation Internet of Things (IoT), telecommunication, and satellite communication systems, controller placement is crucial in software-defined networking (SDN). The programmability of the SDN controller is sophisticated for the centralized control system of the entire network. Nevertheless, it creates a significant loophole for the manifestation of a distributed denial of service (DDoS) attack straightforwardly. Furthermore, recently a Distributed Reflected Denial of Service (DRDoS) attack, an unusual DDoS attack, has been detected. However, minimal deliberation has given to this forthcoming single point of SDN infrastructure failure problem. Moreover, recently the high frequencies of DDoS attacks have increased dramatically. In this paper, a smart algorithm for planning SDN smart backup controllers under DDoS attack scenarios has proposed. Our proposed smart algorithm can recommend single or multiple smart backup controllers in the event of DDoS occurrence. The obtained simulated results demonstrate that the validation of the proposed algorithm and the performance analysis achieved 99.99% accuracy in placing the smart backup controller under DDoS attacks within 0.125 to 46508.7 s in SDN. [ABSTRACT FROM AUTHOR]

In software-defined networks (SDNs), controller placement is a critical factor in the design and planning for the future Internet of Things (IoT), telecommunication, and satellite communication systems. Existing research has concentrated largely on factors such as reliability, latency, controller capacity, propagation delay, and energy consumption. However, SDNs are vulnerable to distributed denial of service (DDoS) attacks that interfere with legitimate use of the network. The ever-increasing frequency of DDoS attacks hasmade it necessary to consider them in network design, especially in critical applications such as military, health care, and financial services networks requiring high availability. We propose a mathematical model for planning the deployment of SDN smart backup controllers (SBCs) to preserve service in the presence of DDoS attacks. Given a number of input parameters, our model has two distinct capabilities. First, it determines the optimal number of primary controllers to place at specific locations or nodes under normal operating conditions. Second, it recommends an optimal number of smart backup controllers for use with different levels of DDoS attacks. The goal of the model is to improve resistance to DDoS attacks while optimizing the overall cost based on the parameters. Our simulated results demonstrate that the model is useful in planning for SDN reliability in the presence of DDoS attacks while managing the overall cost. [ABSTRACT FROM AUTHOR]