International Journal of Computer Network and Information Security @ijcnis
Статьи журнала - International Journal of Computer Network and Information Security
Все статьи: 1148
Optimization of Maintenance Task Interval of Aircraft Systems
Статья научная
Maintenance accounts for approximately 20% of the operational cost of aircraft; a margin higher than cost associated with fuel, crew, navigation, and landing fees. A significant percentage of maintenance cost is attributed to failures of aircraft components and systems. These failures are random and provide a database which can further be analyzed to aid decision-making for maintenance optimization. In this paper, stochastic mathematical models which can potentially be used to optimize maintenance task intervals of aircraft systems are developed. The initial data for this research are diagnostic variables and reliability parameters which formed the basis for selecting the probability density function for time between failures according to the exponential and Erlang models. Based on the probability density functions, the efficiency of the maintenance processes was calculated using average operational cost per unit time. The results of the analysis were further tested using the Monte Carlo simulation method and the findings are highlighted in this paper. The simulation results compared favorably with analytical results obtained using already existing Monte Carlo techniques to about 82% accuracy. The proposed mathematical optimization models determine the optimal aircraft maintenance task interval which is cost effective while considering safety and reliability requirements; our results can also be applied during the development, design, and operation phases of aircraft systems.
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Optimization of Routing in Distributed Sensor Networks Using Heuristic Technique Approach
Статья научная
Distributed Sensor Network consists set of distributed nodes having the capability of sensing, computation and wireless communications. Power management, various routing and data dissemination protocols have been specifically designed for DSN, where energy consumption is an essential design issues for routing. Optimization of routing method is an essential for routing of DSN because of long communication distances between distributed sensor nodes and sink node in a network can greatly drain the energy of sensors and decrease the lifetime of the network. In this paper, simulation is carried out for optimization of routing in DSNs using MATLAB software. The objective is to maximize the network life time and improve the energy efficiency using heuristic technique. A proposed Genetic Algorithm based routing protocol is used for solving an optimization through the evolution of genes parameters, which are coded by strings of characters or numbers and genetic operations (selection, crossover and mutation) are iterated. Finally, the performance parameters for the proposed scheme are evaluated and are shown in terms of energy and routing efficiency, time computation and network lifetime.
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Статья научная
Vehicular Ad-hoc Networks is one of the emerging research areas of Mobile ad- hoc network. One of the key problems of VANET is changing topology of vehicles which leads to frequent disconnections. Therefore, for communication among the running vehicles, routing of the message becomes a challenging problem. Although, many routing protocols have been proposed in the literatures, but the performance of these protocols, in different scenarios, depends on the value of parameters used in. The objective of our work is to find best fitness function value for Ad-hoc on demand multipath distance vector routing protocol, in real scenario map by obtaining an optimal value of parameters using Magnetic Optimization Algorithm. Therefore, in this paper, we have proposed an algorithm based on Magnetic Optimization Algorithm which finds the optimal value of parameters for Ad-hoc on demand multipath distance vector routing protocol in a given scenario. The fitness function guides Magnetic Optimization Algorithm to achieve the best fitness value. The experimental results, using the optimal value of parameters obtained by Magnetic Optimization Algorithm, show 81.41% drop in average end-to-end delay, 39.24 % drop in Normalized Routing Loads, and slight rise (0.77%) in the packet delivery ratio as compared to using default value of parameters in Ad-hoc on demand multipath distance vector routing protocol.
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Optimization of different queries using optimization algorithm (DE)
Статья научная
The biggest challenge in modern web is to tackle tremendous growth of data, scattered and continuously updating in nature. Processing of such unscattered data by human or machine remains a tedious task. Semantic Web; as a solution has already been invented. But, still there are some other challenges, like as optimization of the query. We introduce a new approach for real–time SPARQL query optimization with different forms and different triple patterns. The strategy introduces rearrangement of order of triple pattern using Differential Evolution(DE). The experimental study focus on main-memory model of RDF data and ARQ query engine of Jena. We compare the result of proposed approach with the Ant Colony Optimization(ACO) different versions and some other approaches. Results shows that proposed approach provides better execution time as compare to the other approaches.
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Optimized Communication of Group Mobility in WPAN
Статья научная
ZigBee is a low cost, low-power consumption and long battery life network that is based on the IEEE 802.15.4 standard; which is most usually used to transfer low data rates information in the Wireless Personal Area Network (WPAN). In the Wireless Personal Area Network (WPAN) network, capability of sensor network and mobile network are combined that have energy limit and sensing range limits. Here a network is composed of a number of Sub-Network or groups with the selection of group leader. Group formation is defined under sensing range limit, density limit and type of nodes. The selection of group leader is defined under velocity analysis, energy and average distance after that inter group and intra group communication is performed and then Handoff mechanism is performed when nodes switch the group or group switch the base station.
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Статья научная
Transmission control protocol (TCP) is the most common protocol found in recent networks to maintain reliable communication. The most popular transport protocol in use today is TCP that cannot fully utilize the ability of the network because of the constraints of its conservative congestion control algorithm and favors reliability over timeliness. Despite congestion is the most frequent cause of lost packets, transmission defects can also result in packet loss. In response to packet loss, end-to-end congestion control mechanism in TCP limits the amount of remarkable, unacknowledged data segments that are permitted in the network. To overcome the drawback, Optimized Extreme Gradient Boosting Algorithm is proposed to predict the congestion. Initially, the data is collected and given to data preprocessing to improve the data quality. Min-Max normalization is used to normalize the data in the particular range and KNN-based missing value imputation is used to replace the missing values in the original data in the preprocessing section. Then the preprocessed data is fed into the Optimized Extreme Gradient Boosting Algorithm to predict the congestion. Remora optimization is used in the designed model for optimally selecting the learning rate to minimize the error for enhancing the prediction accuracy in machine learning. For validating the proposed model, the performance metrics attained by the proposed and existing model are compared. Accuracy, precision, recall and error values for the proposed methods are 96%, 97%, 96% and 3% values are obtained. Thus, the proposed optimized extreme gradient boosting with the remora algorithm for congestion prediction in the transport layer method is the best method than the existing algorithm.
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Статья научная
In fog computing, computing resources are deployed at the network edge, which can include routers, switches, gateways, and even end-user devices. Fog computing focuses on running computations and storing data directly on or near the fog devices themselves. The data processing occurs locally on the device, reducing the reliance on network connectivity and allowing for faster response times. However, the conventional intrusion detection system (IDS) failed to provide security during the data transfer between fog nodes to cloud, fog data centres. So, this work implemented the optimized IDS in fog computing environment (OIDS-FCE) using advanced naturally inspired optimization algorithms with extreme learning. Initially, the data preprocessing operation maintains the uniform characteristics in the dataset by normalizing the columns. Then, comprehensive learning particle swarm based effective seeker optimization (CLPS-ESO) algorithm extracts the intrusion specific features by analyzing the internal patterns of all rows, columns. In addition, automatic termination-based whale optimization algorithm (ATWOA) selects the best intrusion features from CLPS-ESO resultant features using correlation analysis. Finally, the hybrid extreme learning machine (HELM) classifies the varies instruction types from ATWOA optimal features. The simulation results show that the proposed OIDS-FCE achieved 98.52% accuracy, 96.38% precision, 95.50% of recall, and 95.90% of F1-score using UNSW-NB dataset, which are higher than other artificial intelligence IDS models.
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Статья научная
The optoelectronic Biswapped-Hyper Hexa-Cell is a recently reported recursive and a symmetrical architecture of Biswapped Family. This symmetrical network has claimed and proved to be advantageous in terms of network diameter, bisection width, minimum node-degree and network cost compared to its counterpart architecture of OTIS family named ‘OTIS Hyper Hexa-Cell’ and traditional grid-based architecture of Biswapped family named ‘Biswapped-Mesh’. In this paper, we present a novel and efficient parallel algorithm for counting sort for sorting distinct numeric values on dh-dimensional Biswapped-Hyper Hexa-Cell optoelectronic network. The parallel algorithm demands 10d_h+12+ log_2〖S_A 〗 electronic and 10 optical moves, where SA is the size of count array: Acip[SA], and SA equals to maximal minus minimal numeric value plus one. On the basis of analysis, it is concluded that proposed algorithm delivers better performance since speedup and efficiency improved for worst case scenario (difference between maximal and minimal data values becomes larger) with the increase of only few communication moves required for sorting.
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Optimized and Executive Survey of Physical Node Capture Attack in Wireless Sensor Network
Статья научная
Wireless sensor networks (WSNs) are novel large-scale wireless networks that consist of distributed, self organizing, low-power, low-cost, tiny sensor devices to cooperatively collect information through infrastructure less wireless networks. These networks are envisioned to play a crucial role in variety of applications like critical military surveillance applications, forest fire monitoring, commercial applications such as building security monitoring, traffic surveillance, habitat monitoring and smart homes and many more scenarios. Node capture attack is one of the most dreadful security attack exist in wireless sensor networks. An adversary steals cryptographic key or other confidential information like node’s id etc from a captured node to compromise entire network. So, Security of wireless sensor network is an important issue for maintaining confidentiality and integrity of wireless links. Now-a-days, researchers are paying attention towards developing security schemes against Node capture attack. Our survey provides deep insights of existing techniques that enhance the attacking efficiency of the node capture attack in wireless sensor network. It also analyzes various detection and key pre-distribution schemes for inventing a new scheme to improve resilience against node capture attack.
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Optimizing Concentric Circular Antenna Arrays for High-Altitude Platforms Wireless Sensor Networks
Статья научная
Wireless Sensor Networks (WSN) has gained interest in many applications and it becomes important to improve its performance. Antennas and communication performance are most important issues of WSN. In this paper, an adaptive concentric circular array (CCA) is proposed to improve the link between the sink and sensor nodes. This technique is applied to the new High – Altitude Platform (HAP) Wireless Sensor Network (WSN). The proposed array technique is applied for two coverage scenarios; a wider coverage cell of 30 km radius and a smaller cell of 8 km radius. The feasibility of the link is discussed where it shows the possibility of communications between the HAP sink station and sensor nodes located on the ground. The proposed CCA array is optimized using a modified Dolph-Chebyshev feeding function. A comparison with conventional antenna models in literature shows that the link performance in terms of bit energy to noise power spectral density ratio can be improved by up to 11.37 dB for cells of 8 km radius and 16.8 dB in the case of 30 km radius cells that make the link at 2.4 GHz feasible and realizable compared to using conventional antenna techniques.
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Optimizing the CMTS to Improve Quality of Service in Next Generation Networks based on ACO Algorithm
Статья научная
In this paper, we focus on the network topological design for providing Quality of Service (QoS) in Next Generation Network (NGN) and propose an effective Ant Colony Optimization (ACO) algorithm to solve the capacitated minimum spanning tree (cMTS) problem in dynamic environment. To improve QoS of communication network with considering the network provisioning capability and dynamic environment, we formulate this problem with minimizing the communication cost (as a kind of performance measures for network's QoS). Our objective functions are determined by pheromone matrix of ants satisfies capacity constraints to find good approximate solutions of cMST problems. Numerical experiments show that our algorithm have achieved much better than recent researches.
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Статья научная
In wireless sensor networks (WSN), sensor nodes are expected to operate autonomously in a human inaccessible and the hostile environment for which the sensor nodes and communication links are therefore, prone to faults and potential malicious attacks. Sensor readings that differ significantly from the usual pattern of sensed data due to faults in sensor nodes, unreliable communication links, and physical and logical malicious attacks are considered as outliers. This paper presents an outlier detection technique based on deep learning namely, generative adversarial networks (GANs) with autoencoder neural network. The two-level architecture proposed for WSN makes the proposed technique robust. The simulation result indicates improvement in detection accuracy compared to existing state-of-the-art techniques applied for WSNs and increase of the network lifetime. Robustness of outlier detection algorithm with respect to channel fault and robustness concerning different types of distribution of faulty communication channel is analyzed.
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Overview and Comparison of Candidate 5G Waveforms: FBMC, UFMC and F-OFDM
Статья научная
The fifth generation (5G) technology standard, utilizing the Internet of Things, promises enhanced communication systems. However, the efficiency expected from such systems entails significant requirements, such as higher data rates and flexibility of the lowest 5G layer. Meeting these requirements in subsequent wireless communication systems is highly dependent on the use of waveforms capable of efficiently enabling multiple access. In other words, proper waveforms determine the effective handling of diverse traffic within a given band. In this study, four candidate multicarrier waveforms, namely filtered orthogonal frequency division multiplexing, filter bank multicarrier, universal filtered multicarrier, and orthogonal frequency division multiplexing, which is currently used in 4G systems, are compared based on multiple parameters. MATLAB simulation results indicate that the waveforms significantly improved spectrum localization and provided appropriate spectrum fragmentation. As these waveforms can mix diverse traffic specifications, they handle the problem of time-frequency synchronization effectively. Therefore, these new waveforms exhibit significant potential in terms of orthogonality and synchronicity and can support numerous users without dropping signals. In addition, they support all applications and scenarios related to multiple-input and multiple-output. The obtained simulation results confirm the suitability of such waveforms for 5G applications and systems.
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PAPR reduction in OFDM system using clipping and filtering methods based on CCDF
Статья научная
Wireless communication systems are becoming so promising day-by-day due to the mobility and the dynamicity of communication pattern. But, to fulfill the wide range of user’s demand it has become much important to use some techniques which would be most efficient in terms of bandwidth and speed. The multicarrier strategy, called as orthogonal frequency division multiplexing (OFDM) has outstanding features to fulfill these demands. Multipath fading, delay spread, frequency selective fading and inter channel interference all of these limitations of wireless communication compound it with the scarcity of bandwidth gave rise to OFDM. However, the high peak-to-average power ratio is a great problem or a barrier in OFDM which causes the signal being distorted with the insufficient power at the receiver. There are some specified techniques to minimize it. In this paper, we have used clipping and filtering methods to minimize the effect of peak-to-average power ratio.
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PEECA: PSO-Based Energy Efficient Clustering Algorithm for Wireless Sensor Networks
Статья научная
In previous years, wireless sensor networks (WSNs) have fascinated lot of consideration from the scientific and technical society. The distributed characteristics and dynamic topology of sensor networks initiates very peculiar necessities in routing schemes that supposed to be met. The key feature of efficient routing protocol is energy expenditure and extension in lifetime of network. In past few years, various routing algorithms have been presented for WSNs. In this work, we focus on cluster based routing algorithms and propose a new algorithm for routing in WSNs. We perform the analysis of our new cluster based algorithms with existing algorithm on the basis of performance metrics. Simulation results shows that proposed algorithm outperform the other existing algorithms of his category.
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PNFEA: A Proposal Approach for Proactive Network Forensics Evidence Analysis to Resolve Cyber Crimes
Статья научная
Nowadays, cyber crimes are increasing and have affected large organizations with highly sensitive information. Consequently, the affected organizations spent more resources analyzing the cyber crimes rather than detecting and preventing these crimes. Network forensics plays an important role in investigating cyber crimes; it helps organizations resolve cyber crimes as soon as possible without incurring a significant loss. This paper proposes a new approach to analyze cyber crime evidence. The proposed approach aims to use cyber crime evidence to reconstruct useful attack evidence. Moreover, it helps investigators to resolve cyber crime efficiently. The results of the comparison of the proposed approach prove that it is more efficient in terms of time and cost compared with the generic and the modern process approach for network forensics.
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PSO and TLBO based reliable placement of controllers in SDN
Статья научная
SDN (software defined networks) is a programmable network architecture that divides the forwarding plane and control plane. It can centrally manage the network through a software program, i.e., controller. Multiple controllers are required to manage the current software defined WAN. Placing multiple controllers in a network is known as controller placement problem (CPP). Only one controller is not capable to handle the scalability and reliability issues. To tackle these issues, multiple controllers are required. Efficient deployment of controllers in SDN is used to improve the performance and reliability of the network. To the best of our knowledge, this is the first attempt to minimize the total average latency of reliable SDN along with the implementation of TLBO and PSO algorithms to solve CPP. Our experimental results show that TLBO outperforms PSO for publicly available topologies.
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Parallel prefix sum algorithm on optoelectronic biswapped network hyper hexa-cell
Статья научная
The biswapped network hyper hexa-cell is recently reported optoelectronic network architecture for delivering excellent performance especially for mapping numerical problems which demands frequent routing and broadcasting. This network contains some important benefits such as smaller diameter, higher bisection width, and lower network’s total and optical cost as compared to counter-part OTIS hyper hexa-cell network. It is also advantageous as compared to the traditional biswapped network mesh containing smaller diameter and higher minimum node degree. In this paper, we present a parallel algorithm for mapping prefix sum of 2×(6×2^(d_h-1) )^2 data elements on a dh-dimensional biswapped network hyper hexa-cell of2〖×(6×2^(d_h-1) )〗^2 processors (assuming each processor contain single data element). It demands total ((d_h- 1)×(d_h+ 1))- ((d_h- 1)×(d_h- 2))/2+ 5d_h + 10 intra-cluster (electronic) and 3 inter-cluster (optical) moves.
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Статья научная
Model-based parameter estimation, identification, and optimisation play a dominant role in many aspects of physical and operational processes in applied sciences, engineering, and other related disciplines. The intricate task involves engaging and fitting the most appropriate parametric model with nonlinear or linear features to experimental field datasets priori to selecting the best optimisation algorithm with the best configuration. Thus, the task is usually geared towards solving a clear optimsation problem. In this paper, a systematic-stepwise approach has been employed to review and benchmark six numerical-based optimization algorithms in MATLAB computational Environment. The algorithms include the Gradient Descent (GRA), Levenberg-Marguardt (LEM), Quasi-Newton (QAN), Gauss-Newton (GUN), Nelda-Meald (NEM), and Trust-Region-Dogleg (TRD). This has been accomplished by engaging them to solve an intricate radio frequency propagation modelling and parametric estimation in connection with practical spatial signal data. The spatial signal data were obtained via real-time field drive test conducted around six eNodeBs transmitters, with case studies taken from different terrains where 4G LTE transmitters are operational. Accordingly, three criteria in connection with rate of convergence Results show that the approximate hessian-based QAN algorithm, followed by the LEM algorithm yielded the best results in optimizing and estimating the RF propagation models parameters. The resultant approach and output of this paper will be of countless assets in assisting the end-users to select the most preferable optimization algorithm to handle their respective intricate problems.
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Parameter training in MANET using artificial neural network
Статья научная
The study of convenient methods of information dissemination has been a vital research area for years. Mobile ad hoc networks (MANET) have revolutionized our society due to their self-configuring, infrastructure-less decentralized modes of communication and thus researchers have focused on finding better and better ways to fully utilize the potential of MANETs. The recent advent of modern machine learning techniques has made it possible to apply artificial intelligence to develop better protocols for this purpose. In this paper, we expand our previous work which developed a clustering algorithm that used weight-based parameters to select cluster heads and use Artificial Neural Network to train a model to accurately predict the scale of the weights required for different network topologies.
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