Статьи журнала - International Journal of Wireless and Microwave Technologies
Все статьи: 532
A novel energy efficient cluster head selection method for wireless sensor networks
Статья научная
Wireless Sensor Networks are becoming a worldwide sensational topic with recent advances in wireless communications and digital electronics. It serves as the backbone for controlling real-life applications. It consists of group of sensor nodes that sense the information from an event area and passes it to the base station which reacts according to the environment. There are number of cluster based routing protocols, in which a region is divided into number of clusters and within each cluster, a cluster head is elected based on some parameter. So, a novel selection method for the cluster head having efficiency in energy is based on Flower Pollination Algorithm (FPA) is proposed in this paper. The performance of our proposed scheme is being analyzed and is compared with the already existing protocols like LEACH, C-LEACH and K-Means in terms of energy efficiency, number of alive nodes, packet drop ratio and energy dissipation etc
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A power-based method for improving the ODMRP protocol performance in mobile ad-hoc networks
Статья научная
Mobile AD hoc Networks as a special type of wireless networks have received special attention due to having special features such as no need for central management, no need for infrastructure and high mobility capability and can be used in cases where creating an effective communication infrastructure is not cost-effective or is practically impossible, such as conferences, such as battles and communications after natural disasters. Several routing protocols are proposed for these networks. ODMRP protocol is one of the most famous and used protocols in Mobile AD hoc networks. This study was carried out aimed to discuss this routing protocol and then provide a new routing method for this protocol for increasing its efficiency. In the ODMRP protocol, the optimal route is selected based on the shortest route. In wireless communications and getting the nodes away from each other, the received signal levels are weakened and may result in loss of data, and in practice, the shortest path that works based on the number of hops loses its effectiveness. In the proposed protocol, the route is selected based on the received signal strength level. According to the simulation results, the performance of the proposed protocol increases by decreasing control overhead and increasing the packet delivery rate compared to the original protocol.
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Статья научная
Blockchain’s vast applications in different industries have drawn several researchers to pursue extensive research in securing blockchain technologies. In recent times we could see several institutions coming together to create consortium based blockchain networks such as Hyperledger. Although for applications of blockchain such as Bitcoin, Litcoin, etc. the majority-attack might not be a great threat but for consortium based blockchain networks where we could see several institutions such as public, private, government, etc. are collaborating, the majority-attack might just prove to be a prevalent threat if collusion among these institutions takes place. This paper proposes a methodology where we can use intelligent software agents to monitor the activity of stakeholders in the blockchain networks to detect anomaly such as collusion, using supervised machine learning algorithm and algorithmic game theory and stop the majority attack from taking place.
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A stable routing protocol based on DSR protocol for mobile ad hoc networks
Статья научная
Mobile ad hoc network is a wireless non-centralized network. This network includes a set of distributed nodes with any base or central management, develop a temporary network. Such a way, routing is of the basic challenges of these kinds of networks. Till now, various protocols have been provided for routing in these kinds of networks. One of the optimum routing techniques in these networks is stable routing. In the stable routing, the target is to use paths for send and receive that probably have a higher life period. This causes the data to be sent from a more confident path and the need to new routing will be less, due to liquidation of the current path. In this paper, the target is to provide a stable routing protocol with high efficiency for these kinds of networks, by improving the DSR routing protocol. In the provided protocol, beside the path stability, the energy of the path nodes and path length will be considered too, in order to discover a path with higher quality and use it. The provided protocol will be called as ST-DSR. The result of stimulation in the NS-2 environment shows that the ST-DSR has a better operation toward the base protocol, meaning DSR.
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A study on Need of Adaptation Layer in 6LoWPAN Protocol Stack
Статья научная
Emergence of wireless embedded applications is resulting in the communication among sensor nodes connected in a wireless personal area network. Sensor nodes gather the real time information and transmit it to the desired application. This requires transmission of IPv6 packets over Low-power wireless personal area network and is called 6LoWPAN. IPv6 is resource intensive protocol whereas 6LoWPAN is resource constraint due to small packet size, limited device memory, short transmission range, and less data rate of sensor nodes. Also these nodes in 6LoWPAN are mainly battery operated hence minimum power consumption is also a major constraint. To make the efficient transmission of information in such a resource constraint network, an adaptation layer was suggested and implemented by Internet Engineering Task Force (IETF). The placing of this additional layer is in between network layer and data link layer of TCP/IP protocol stack. This paper contributes in the detailed analysis of need of adaptation layer in 6LoWPAN protocol stack. The necessity of this additional layer is justified by explaining the major functions like header compression, fragmentation and reassembly of packets and packet routing handled by it.
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Статья научная
The optimal capacity expansion of base station subsystems in Next Generation Wireless Network (NGWN) problem with respect to multi-demand type and system capacity constraints is known to be NP-complete. In this paper, we propose a novel ant colony optimization algorithm to solve a network topology has two levels in which mobile users are sources and both base stations and base station controllers are concentrators. There are two important aspects of upgrading to NGWN. The first importance of backward compatibility with pre-existing networks, and the second is the cost and operational benefit of gradually enhancing networks, by replacing, upgrading and installing new wireless network infrastructure elements that can accommodate both voice and data demand. Our objective function is the sources to concentrators connectivity costas well as the cost of the installation, connection, replacement, and capacity upgrade of infrastructure equipment. We evaluate the performance of our algorithm with a set of real world and data randomly generated. Numerical results show that our algorithms is a promising approach to solve this problem.
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Статья научная
This research presents a pioneering investigation into the tangible outcomes of implementing an Artificial Intelligence (AI) driven network security strategy, with a specific emphasis on dynamic threat landscape adaptation and the integration of time series analysis algorithms. The study focuses on the innovative fusion of adaptive mechanisms to address the ever-evolving threat landscape, coupled with the application of the Autoregressive Integrated Moving Average (ARIMA) time series analysis algorithm. Real-world case studies are employed to provide concrete evidence of the efficacy of these strategies in fortifying network defenses and responding dynamically to cyber threats. Novelty is introduced through the unified integration of dynamic threat landscape adaptation mechanisms that continuously learn and evolve. The paper details adaptive access controls, showcasing how the security system dynamically adjusts permissions in real time to respond to emerging threats. Additionally, the application of the ARIMA time series analysis algorithm represents a pioneering contribution to the field of cybersecurity. By unveiling temporal patterns in security incidents, ARIMA adds a predictive element to network defense strategies, offering valuable insights into potential future threats and enabling a proactive response. The findings underscore the practical impact of the applied strategies, with real-world case studies demonstrating substantial improvements in threat detection rates, the effectiveness of adaptive responses, and the predictive capabilities facilitated by ARIMA. This research contributes to the advancement of AI in network security by providing tangible evidence of the innovative and effective nature of the integrated approach. The outcomes bridge the gap between theoretical concepts and practical applications, offering valuable insights for organizations seeking adaptive and predictive strategies to enhance their cybersecurity resilience in dynamic threat environments.
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Статья научная
All new mobile radio communication systems undergo a cautious cellular network planning and re-planning process in order to resourcefully utilize the allotted frequency band and also ensure that the geographical area of focus is adequately fortified with integrated base stations transmitters. To this end, efficient radio propagation model prediction and tuning is of huge importance, as it assists radio network engineers to effectively assess and plan the cellular network signal coverage area. In this research work, an adaptive least absolute deviation approach is proposed and verified to fine-tune the parameters of Ericsson propagation model. The adaptive tuning technique have been verified experimentally with field propagation loss data acquired over three different suburban locations of a recently deployed LTE radio cellular network in Waterlines area of Port Harcourt City. In terms of the mean absolute percentage error and coefficient of efficiency, the outcomes of the proposed adaptive tuning approach show a higher degree of prediction performance accuracy on the measured loss data compared to the commonly applied least squares regression tuning technique.
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Adaptive Cross-layer Resource Allocation by HNN in OFDM-MISO System
Статья научная
This paper presents an adaptive cross-layer resource allocation problem with the fairness in multi-user OFDM-MISO communication systems, and provides two solutions with Hopfield Neural Network (HNN) and Genetic Algorithm (GA) for the problem. We utilized HNN’s characteristics such as parallel processing, fast convergence speed and easy convergence to the optimum, to solve this problem under the conditions of proportional fairness for satisfying system performances and users’ requirements. The method is simplified in the computation by dividing the bit-loading matrix into three matrixes. The simulation results show that HNN and GA can effectively solve optimization problems of resource allocation in such system, and results of selected HNN and GA methods are more effective than that of the traditional method.
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Adaptive HEC-VPS: The Real-time Reliable Wireless Multimedia Multicast Scheme
Статья научная
To satisfy the reliability of real-time wireless multimedia multicast services, the existing erasure error correction schemes usually assume that the packet size in transmissions is fixed. However, recent studies have shown that Variable Packet Size (VPS) can deeply influence the performance of unicast wireless services. Accordingly, using a delay-limited general architecture of EEC for real-time wireless multicast, this paper proposes an Adaptive Hybrid Error Correction (AHEC) scheme with VPS. Comparing with the AHEC schemes with fixed packet size, the analysis results show that the AHEC with VPS scheme can improve the throughput by about 10% in some cases.
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Adaptive Multi User Detection for FD-MC-CDMA in Presence of CFO
Статья научная
The main targets of multi-carrier direct sequence code division multiple access (MC-DS-CDMA) mobile communication systems are to overcome the multi-path fading influences as well as the near-far effect and to increase its capacity. Different types of optimal and suboptimal multi-user detection schemes have been proposed and analyzed in literature. Unfortunately, most of them share the drawback of requiring an efficient practical solution. Genetic algorithm provides a more robust and efficient approach for solving complex real world problem such as multi user detection, but genetic algorithms are not computationally efficient. Computational complexity and performance of the genetic algorithms depends on number of generations and/or the population size, schemes involving genetic algorithms would compromise in computational complexity or performance. In this paper we propose adaptive population sizing genetic algorithm based multi user detection algorithm and compare its performance with existing multi user detection algorithms in various channels. Simulation results confirmed that the proposed adaptive genetic algorithm assisted multi user detection algorithm performs better compared to the existing multi user detection algorithms.
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Adversarial Deep Learning in Anomaly based Intrusion Detection Systems for IoT Environments
Статья научная
Using deep learning networks, anomaly detection systems have seen better performance and precision. However, adversarial examples render deep learning-based anomaly detection systems insecure since attackers can fool them, increasing the attack success rate. Therefore, improving anomaly systems' robustness against adversarial attacks is imperative. This paper tests adversarial examples against three anomaly detection models based on Convolutional Neural Network (CNN), Long Short-term Memory (LSTM), and Deep Belief Network (DBN). It assesses the susceptibility of current datasets (in particular, UNSW-NB15 and Bot-IoT datasets) that represent the contemporary network environment. The result demonstrates the viability of the attacks for both datasets where adversarial samples diminished the overall performance of detection. The result of DL Algorithms gave different results against the adversarial samples in both our datasets. The DBN gave the best performance on the UNSW dataset.
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Adversarial Machine Learning Attacks and Defenses in Network Intrusion Detection Systems
Статья научная
Machine learning is now being used for applications ranging from healthcare to network security. However, machine learning models can be easily fooled into making mistakes using adversarial machine learning attacks. In this article, we focus on the evasion attacks against Network Intrusion Detection System (NIDS) and specifically on designing novel adversarial attacks and defenses using adversarial training. We propose white box attacks against intrusion detection systems. Under these attacks, the detection accuracy of model suffered significantly. Also, we propose a defense mechanism against adversarial attacks using adversarial sample augmented training. The biggest advantage of proposed defense is that it doesn’t require any modification to deep neural network architecture or any additional hyperparameter tuning. The gain in accuracy using very small adversarial samples for training deep neural network was however found to be significant.
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An Analysis of VoIP Application in Fixed and Mobile WiMAX Networks
Статья научная
WiMAX is a wireless broadband technology, which promises maximum coverage area and high data rates. WiMAX provides last mile connectivity. This network defines two working models such as fixed WiMAX and mobile WiMAX. The main aim of this paper is to compare and also analyze the performance of the VoIP application over fixed and mobile WiMAX, with respect to various codecs such as G.711, G.723.1ar5.3, G.726ar24, G.728ar16 and G.729. We have considered few QoS parameters such as average end-to-end delay, throughput, average jitter, average one-way delay and average MOS. From the obtained result, codec G.711 and G.726ar24 performs better when compared to other codecs in both fixed and mobile WiMAX network.
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An Analytical Study of Cloud Security Enhancements
Статья научная
Enhancements and extensions in pervasive computing have enabled penetration of cloud computing enabled services into almost all walks of human life. The expansion of computational capabilities into everyday objects and processes optimizes end users requirement to directly interact with computing systems. However, the amalgamation of technologies like Cloud Computing, Internet of Things (IoT), Deep Learning etc are further giving way to creation of smart ecosystem for smart human living. This transformation in the whole pattern of living as well as working in enterprises is generating high expectations as well as performance load on existing cloud implementation as well as cloud services. In this complete scenario, there are simultaneous efforts on optimizing as well as securing cloud services as well as the data available on the cloud. This manuscript is an attempt at introducing how cloud computing has become pivotal in the current enterprise setting due to its pay-as -you -use character. However, the allurement of using services without having to procure and retain involved hardware and software also has certain risks involved. The main risk involved in choosing cloud is compromising security concerns. Many potential customers avoid migrating towards cloud due to security concerns. Security concerns for the cloud implementations in the recent times have grown exponentially for all the varied stakeholders involved. The aim of this manuscript is to analyze the current security challenges in the existing cloud implementations. We provide a detailed analysis of existing cloud security taxonomies enabling the reader to make an informed decision on what combination of services and technologies could be used or hired to secure their data available on the cloud.
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An Approach Towards Dynamic Opportunistic Routing in Wireless Mesh Networks
Статья научная
Opportunistic routing (OR) for multi-hop wireless networks was first proposed by Biswas and Morris in 2004, but again as a modified version in 2005 as Extremely Opportunistic Routing (ExOR). A few other variants of the same were also proposed in the meanwhile time. In this paper we propose a Dynamic Opportunistic Routing (DOR) protocol which depends on network density and also provides spatial diversity. Our routing protocol is distributed in nature and provides partial 802.11 MAC layer abstraction. To verify the results of our protocol we took a network with light-density of nodes and bigger in size (as OR performs better in higher node density). A wireless mesh network in “QualNet network simulator” was created, where the average end-to-end delay and throughput at every node are compared with that of other standard routing protocol OLSR-INRIA.
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An Approach to Micro-blog Sentiment Intensity Computing Based on Public Opinion Corpus
Статья научная
Based on the analysis of the status of network public opinion, the features of short content and nearly real-time broadcasting velocity in this paper, it constructs a public opinion corpus on the content of micro-blog information, and proposes an approach to marking corpus on the basis of sentiment tendency from the semantic point of view; Furthermore, considering the characteristics of micro-blog, it calculates the sentiment intensity from three levels on words, sentences and documents respectively, which improves the efficiency of the public opinion characteristics analysis and supervision. So as to provide a better technical support for content auditing and public opinion monitoring for micro-blog platform.
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An Efficient and Cloud Based Architecture for Smart Grid Security
Статья научная
Due to explosive growth of users, increasing energy demand and also the need to improve efficiency and maintain the stability of the electricity grid, smart grid is the only option available to electrical industry engineers. In fact, the smart grid is a physical-cyber system that provides coherent and integrated communication, processing and control functions. The smart grid provides control and management of millions of devices in the electricity industry in a reliable, scalable, cost-effective, real time and two-sided manner. Given the increasing growth of cyber threats in the last decade, the need to protect the electricity industry and its critical systems seems essential. The slightest disruption to the power industry's systems results in disruption to other industries, reduced productivity, and discontent. Hence we proposed an efficient cloud based architecture to improve smart grid performance. Proposed architecture provides data security and privacy against different types of cyber threats such as replay attack, modification attack and so on.
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An Efficient and Comapct Design of Coupled-Line Unequal Wilkinson Power Divider
Статья научная
In this paper, 3:1 and 10:1 unequal Wilkinson power dividers are designed and investigated. Unequal power dividers are an integral part of the feeding network for antenna array where their performance affects a group of elements rather than an individual element. Thus, there is a need for an accurate design for such dividers. A coupled-line section with two grounding via has been used to attain the high characteristic impedance line. This is done in order to outplay the microstrip fabrication constraints of printing very thin/fine conductor lines. Further to reduce the size of the structure, meandering of the transmission line has been done which procreates three designs, namely: 00 Serpentine Flexure, 1800 Serpentine Flexure and Compact Meandered Flexure. Verification of the design methodology has been done by creating a 10:1 Unequal WPD. The structures are implemented on a high-resistive silicon substrate (HRS) for a centre frequency of 1.575 GHz. Further, their EM analysis is done in terms of S-parameters such as return loss and insertion loss using commercially available FEM solver. Satisfactory RF performance, with return loss better than -10 dB and required power split for all the structures, has been achieved.
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An Energy Efficient Routing Algorithm for Wireless Body Area Network
Статья научная
Wireless body area networks (WBANs) are emerging as one of the newest forms of Wireless Sensor Networks. In WBANs, sensor nodes accumulate human physiological data and transmit it to the sink node. However, transmission of physiological data to the sink node over a mobile route becomes a very daunting task for sensors due to their limited battery power. Moreover, replacement of critical sensor nodes is a major challenge in such scenarios. In order to increase network lifetime, some routing protocols have been proposed in the literature, but the majority of them are focused on coverage distance and residual energy of sensor nodes. In this work, we will propose an energy efficient routing algorithm for WBANs that will take into consideration two additional attributes (node criticality and communication count) along with the above stated attributes. These four parameters in the proposed algorithm will result in enhancement of working lifetime of the network via less energy consumption in comparison to existing routing protocols.
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