International Journal of Wireless and Microwave Technologies @ijwmt
Journal articles - International Journal of Wireless and Microwave Technologies
All articles: 648
Scientific article
This paper presents a Causal Observability Framework designed to enhance the reliability and performance of cloud-native distributed systems through structured integration with the DevOps pipeline. The framework unifies three interdependent components: real-time telemetry collection, dual-domain causal tracing, and probabilistic causal inference. The causal tracing layer combines a time-domain vector autoregressive Granger causality model with a discrete Fourier transform frequency-domain extension. The causal inference layer employs Bayesian network propagation, updated online via the Expectation-Maximisation algorithm, to compute posterior downstream failure probabilities from upstream anomaly observations. Validation was conducted through a controlled, three-replicate experimental study on a seven-service AI-powered recommendation application deployed across a dual-provider six-node Kubernetes cluster (AWS EKS and GCP GKE) under three traffic profiles ranging from 50 to 500 requests per second. Against a conventional threshold-based monitoring baseline, the proposed framework achieved: a 35% reduction in incident response time (70 minutes to 45 minutes), a 40% reduction in mean time to recovery (50 minutes to 30 minutes), a 1.5 percentage-point improvement in system availability (98.0% to 99.5%), a 61% reduction in false-positive alert rate (18% to 7%), and a 63% improvement in root-cause localisation accuracy (54% to 88%). All five improvements were statistically significant at p < 0.05 via paired t-test. A quantified nine-minute early-warning lead time over conventional detection was demonstrated in the fault-injection scenario. Seven formal equations underpin the methodology, spanning Granger vector autoregression, F-test inference, AIC-based lag selection, normalised causality scoring, frequency-domain spectral causality, Bayesian posterior propagation, and expected detection lead time.
Free
Implementing Video OCR along with SWT Technique for Video indexing and Analysis
Scientific article
The main purpose of this paper is to expand the usage of OCR (Optical character recognition) as this is only implemented over images and to extend this Video OCR is introduced in a way to help to retrieve the information from the video without playing the video. Video OCR is executed with the assistance of OpenCv2 module and PyTesseract [7] at the side of SWT approach which all pretty collectively make an ideal aggregate to offer an appropriate content from the video (i.e., Lecture video or any kind of video which has slides or text on the background of the video) [2,4].This technique is performed in a well-designed along with easy steps to provide us an correct end result of the facts from the video into textual files. In addition to this we also added Speech Recognition module within the project to support the video along with the text file. This speech delivered by the faculty (i.e., instructor/educator/teacher), or an educator will be also resulted in a text file.
Free
Improved Hybrid Architecture to Mitigate Free Riding in P2p Network
Scientific article
Peer-to-peer (P2P) networks rely heavily on resources shared by peers in the network as a result of this mitigating free riding in the network is very crucial in a P2P system. In this work, we introduced a dynamic grace period allocation and a content scanning mechanism to a hybrid P2P architecture to mitigate free riding and prevent peers from uploading repeated and fake files within the network. The method introduced was simulated using Python programming language with peers selected at random to upload and download files representing a typical scenario of a P2P network. From the range of 0-500 and 600-2000, twenty different peers were selected at random the first scenario represents few peers and the second scenario represents many peers for analysis and experimentation purposes and also for the different percentages of free riders used for the experiment, this was chosen at random. Finally, we compared our method with a credit-based approach (CBA) that uses a common grace period assigned to peers in the network. Then, for the performance evaluation metric, we used the total uploads and downloads, contributing peers uploads and downloads, free rider peers uploads and downloads, and repeated and fake files detected gotten from the simulation result to evaluate the model and analyze the outcome of the experiments. Results from the simulation revealed that the Dynamic grace period approach (DGA) is 25-70% more effective than CBA in maintaining contributing peer activity and preventing the spread of repeated and fake files,while also achieving lower latency, higher throughput, and better quality of service (QoS) across diverse network conditions, particularly in high free-rider environments.
Free
Improved Route Discovery Scheme under Blackhole Attack in MANET
Scientific article
A Mobile Ad Hoc Network (MANET) consists of numerous wireless mobile devices. It is a self-organizing network and does not require any pre-established infrastructure. Communication between devices sets up without any dedicated centralized server. A malicious node takes advantage of this vulnerability and attempts to integrate into the network in order to lower its overall performance. In MANET, one of the most dangerous types of attacks is the blackhole node assault. In order to join the route, a node with blackhole assault wrongly sends route information to the source node during the route discovery process and degrades the network performance. In order to address this problem, a novel Blackhole Detection Algorithm (BHDA) has been proposed in this work. To determine the existence of blackhole nodes, the protocol takes into account various factors including number of route request packets (RREQ) received, number of RREQ packets forwarded, and number of route reply packets (RREP) transmitted by nodes throughout the route discovery process. Apart from this, each node maintains a local neighbourhood information and for that all neighbourhood node has to pass the check before becoming a neighbour. The simulation results prove that the proposed technique BHDA shows drastic improvement in network performance under blackhole attack.
Free
Scientific article
The design of a double layer stacked microstrip loop shaped patch antenna for multiband operation has been proposed. The design has been evolved following the iterations of a rectangular patch and a single layer loop patch structure. The material considered for the substrate of both the layers is 1.6 mm thick FR4 epoxy and the feeding technique used for the bottom patch is coaxial/ probe feed. The radiations from the bottom layer patch have been electromagnetically coupled to the upper layer patch. The main results including the reflection coefficient, bandwidth, radiation pattern, gain, directivity and VSWR for single frequency operation in each case have been discussed separately and finally compared. The comparison shows that the proposed stacked structure is clearly advantageous over the conventional rectangular patch and the single layer designed prototype in terms of the standard parameters that have been obtained. The three stage designs are useful to serve the X-band aviation applications including radio location and fixed mobile radio location.
Free
Improvement of ZigBee Using by Thread and Backpressure Algorithm
Scientific article
In wireless sensor networks, two approaches of tree and mesh routing are introduced to determine the path of packets during the transition process. Tree routing is a simple routing protocol with low overhead that in this protocol father-child bonds for packet transmission from the source to the destination is used. The biggest problem of routing is the increase of the number of mutations in comparison with other routing protocols. In order to improve this problem, protocols have been introduced in recent years to determine a shortcut path on the basis of the tree routing. This study is an attempt to analyse and evaluate the existing routing algorithms, identify and overcome their disadvantages, also in some other protocols, only reducing the number of mutations has been discussed. However, to achieve this goal leads to increased energy consumption and thus reducing the lifetime of the network; reducing the number of mutations is an important parameter and can reduce delays in the network, however, it should be noted the energy consumption in ZigBee networks is a very important debate. Besides that, this study will try—in addition to reducing the average number of mutations—to reduce the traffic load near the root node in the proposed algorithms. As a result, on the one hand, the application of this algorithm in ZigBee networks reduces delays and on the other hand, will also lead to balancing of load and energy in the network. Using this algorithm, the scope and lifetime of the proposed protocol-based networks can be increased.
Free
Scientific article
Wireless sensor network has many applications and very active research area. The coverage span of this network is very important parameter where wide coverage area is a challenge. This paper proposes an architecture for large-scale wireless sensor network (LSWSN) based on satellites and the High-Altitude Platforms (HAP) where the sensor nodes are located on the ground and a wide coverage sink station may be in the form of a satellite or a network of HAPs. A scenario is described for multilayer LSWSN and a study for the system requirements has been established showing the number of Satellites, HAPs and coverage per each sink according to the elevation angle requirements. The Satellite-HAP-Sensor multilayer LSWSN architecture has the feasibility for effective energy and earth coverage and is optimum for covering largely sparse regions.
Free
Integrated Guard Channel Synthesis in AESA based Airborne Surveillance Radar
Scientific article
The guard channel is very effective in eliminating side-lobe returns, both targets and discrete clutter, in airborne radar's. The ideal design criterion for the guard channel is that all the side lobes of the main antenna are covered by the guard pattern. In this paper a novel design approach of generating the guard using the elements of the main Active Electronically Scanned Array (AESA) antenna, thereby eliminating the need for a separate antenna, is presented. The ground clutter has an angle dependent Doppler and clutter discrete that leak in through the side lobes, especially the inter-cardinal elevation side lobes looking at the near range, needs to be eliminated. Towards this the design of the weighting coefficients for the guard to cover all the side lobes of the main array is discussed. Furthermore a digital threshold scheme is proposed to improve the effectiveness of guard channel in eliminating side-lobe returns. The detection loss and blanking probability are characterized for the design. The measurement results confirm that the design objectives are met.
Free
Scientific article
IoT networks face persistent security challenges due to limited compute, heterogeneous hardware, and weak threat-detection coverage. Classical machine-learning methods struggle with high-dimensional traffic and novel attack patterns. This paper proposes a hybrid framework combining Fractional Generalized Laguerre (FrGL) moment-based feature extraction with a Residual Network augmented by Squeeze-and-Excitation attention (ResNet-SE). FrGL moments yield compact, noise-resistant descriptors via simple recurrence relations, while ResNet-SE mitigates degradation in deep networks through identity shortcuts and adaptively recalibrates channels to highlight attack-relevant features. On the Bot-IoT and Leopard Mobile IoT benchmarks the method reaches 99.78 % accuracy and 99.37 % F1, exceeding KNN (84.7 %), MLR (87.5 %) and a baseline CNN (99.3 %); cross-dataset tests on UNSW-NB15 and IoT-Bot give 96.34 % and 97.12 % accuracy. The framework additionally delivers per-sample inference latency on server- and edge-class hardware (3.9 ms on an NVIDIA V100 and 27.4 ms on a Raspberry Pi 4B with a Coral USB accelerator), an energy cost of 0.42 J per inference on the edge platform, a sensitivity analysis over learning rate, batch size, fractional order λ and reduction ratio r, and an adversarial-robustness evaluation under FGSM and PGD attacks, supporting real-time deployment on resource-constrained IoT gateways.
Free
Scientific article
With the accelerated proliferation of cloud services and web-based applications, exposure to sophisticated cy-ber threats like zero-day vulnerabilities, advanced persistent threats, and application-layer attacks, has sharply increased. Conventional intrusion detection systems, along with cryptographic security mechanisms, often do not fulfill the require-ments of adaptive detection, privacy preservation, and variety of scalability within distributed systems. To alleviate these problems, this paper suggests a cross-layer adaptive security model, which includes, in the secure cloud and web applica-tions, machine learning-based anomaly detection complemented with advanced cryptographic security. The model com-bines, in this context, lightweight local anomaly detection, federated learning, selective privacy, and a deep reinforcement learning-based threat detection and security orchestration. Through federated learning, active participation in the learning process is assured, while the selective privacy mechanism preserves the model parameters. The deep reinforcement learn-ing agent adjusts the interaction, aggregation, and privacy settings according to demands of the adaptive system and the environment. The assessment of the model is realized through the CSE-CIC-IDS2018, CIC-IDS2017, and the CSIC 2010 HTTP benchmark datasets to verify the model in detection, generalization, and operational effectiveness. The results of the performed tests reflect an accuracy of 97.9%, a F1 score of 97.5%, a false positive rate of 1.8%, and a detection latency of 36 ms, surpassing performance of conventional federated and centralized state-of-the-art models. Cross-dataset testing validates the model effectiveness in the presence of highly variable traffic. The results suggest that adaptive orchestration, federated learning, and selective privacy preservation, when combined, substantially boost intrusion detection, decrease communication overhead, and ensure privacy preservation. Therefore, this framework is a scalable and robust approach to intrusion detection within contemporary cloud and web settings.
Free
Integrating Quantum Computing with Cloud Systems: Opportunities, Challenges, and Future Prospects
Scientific article
Cloud computing can be revolutionized by quantum computing which will offer the world more computational power than has ever been seen to solve complex issues. Quantum computing coupled with cloud computing enables the remote access to quantum resources, thus greatly minimizing the cost, technical, and operational difficulties of having quantum hardware owned and maintained in the field. The integration makes large-scale data processing, cryptography, and optimization tasks as well as new applications in artificial intelligence efficient in terms of their computation. This work is a review of the existing approaches, system, and systems to quantum cloud computing, the main algorithms, software applications, implementation plans, and real-life examples. We find that quantum cloud computing provides significant enhancements in computational speed and parallelism, scalability, as well as provides the capability to process data securely and to execute quantum circuits remotely. However, there are still a few obstacles such as stability of qubits, error correction, noise reduction, and effective resource utilization, which restrict the practical use of quantum cloud services. The findings indicate that, irrespective of these challenges, quantum computing with the use of cloud computing platforms offers meaningful potentials to scientific discovery, business, and an AI-based innovation. The paper wraps up by noting that further research should be done to enhance the reliability of quantum hardware, optimize quantum algorithms, and design quantum cloud computing security systems, enabling quantum cloud computing to be adopted more broadly as a more transformative model of computation and ensuring that quantum cloud computing can grow sustainably.
Free
Scientific article
The new and emerging challenges posed by the convergence of cyber threats and socio-political tensions have risen as one of the core formidable threats to the present global security landscape. This paper proposes a hybrid predictive model intended to act against these real-world multidimensional attack vectors. The model integrates cyber threat hunting techniques with socio-political risk assessment methodologies to comprehensively forecast consequent cybersecurity threats to social unrest scenarios. Cyber threat data is collected from sources such as the Offensive Defensive-Intrusion Detection System (OD-IDS2022) and the Aegean Wi-Fi Intrusion Dataset (AWID3), and social terror attack information is gathered from the Global Database of Events, Language, and Tone (GDLET) Project and Armed Conflict Location & Event Data (ACLED) to comprise the bidirectional dataset for the model that contains views from both cyber and socio-political risk landscapes. The model adopts a holistic, robust predictive capability through k-fold cross-validation and feature importance evaluation implementation techniques. This multidisciplinary approach offers a synoptic understanding of emerging and future security threats and enables the execution of proactive measures to secure national and transnational borders.
Free
Intelligent Load Balancing Framework for Distributed Big Data Processing System
Scientific article
This paper proposes an intelligent load balancing framework for distributed big data processing systems that integrates machine learning techniques with adaptive weight-based decision mechanisms. The study addresses limitations of traditional static load balancing methods, which do not account for dynamic workload variations and heterogeneous request characteristics, leading to inefficient resource utilization and bottlenecks in multi-node environments. The proposed approach combines an online learning model for real-time estimation of request complexity with multi-parameter evaluation of node states, including CPU utilization, memory consumption, queue length, response latency, and cache efficiency. A dynamic weighting strategy is used to construct an integrated load indicator for adaptive request distribution across nodes. The framework is deployed within a multi-layer distributed architecture consisting of clustered application servers, distributed databases, caching subsystems, and monitoring components, ensuring scalable and fault-tolerant processing. For evaluation, a three-node simulation environment was used with 10,000 heterogeneous requests, followed by extended testing on semi-realistic workload traces derived from web traffic patterns and database query logs. The dataset included over 1.2 million requests, capturing bursty arrivals, skewed distributions, and heterogeneous complexity. Experimental results show that the proposed method improves load distribution uniformity to 6%, reduces average response time to 210 ms, and increases throughput up to 13,800 requests per second. Statistical validation using confidence intervals and hypothesis testing confirms a 47% (±3.2% at 95% confidence level) reduction in mean response time and throughput improvement up to 14,200 requests per second under realistic workloads.
Free
Intelligent and Distributed Localization of Nodes in Wireless Sensor Networks
Scientific article
In wireless sensor networks, the issue of nodes localization has taken a wide area of research. Most applications need to know the position of sensor nodes for reasons of optimal and fast data routing. In this paper, a new distributed localization algorithm based on Self Organizing Maps (SOMs) is proposed to determine the location of a node in a wireless sensor network. The proposed algorithm is classified as a range-free algorithm which uses only the connectivity information between nodes without the need to measure the time of arrival or signal strength as range-based algorithms require. It utilizes the neighborhood information and the well-known anchors' positions to calculate the estimated locations of nodes. Our algorithm is made up of two main stages. The initial estimated locations of nodes are calculated in the initialization stage, and fed to the learning stage in which a SOM is used to calculate the final estimated locations of nodes. By using the neighborhood information at the first stage, the algorithm has significantly reduced the SOM learning time and the number of iterations to converge. On the other hand, starting with real data rather than random data maximized the accuracy of the resulted locations. Furthermore, the distributed implementation of the algorithm highly alleviated the pressure on the wireless nodes which are characterized with low power and limited capabilities. The proposed algorithm has been implemented using MATLAB software and experimented by deploying different number of nodes in a specific area with different communication radio ranges. Extensive simulations evidently verified the performance of the algorithm and achieved a very good accuracy. Moreover, the algorithm proved its effectiveness with a lower average error and lower number of iterations compared to other related algorithms.
Free
Scientific article
In this paper, we present atmospheric effect on 5th Generation (5G) millimeter wave (MMWave) communication system. Atmospheric effects for Delhi (India) based 5G communication system is calculated as per Delhi atmospheric conditions. Atmospheric impairments are major cause of degrading mmWave signal power while mmWave propagation in wireless channel. Due to Atmospheric impairments attenuation takes place and major impairments are like water vapour, oxygen, rain and fog for Delhi (India). 5G mmWave attenuation calculations are performed for the mmWave band frequencies 28 GHz, 37 GHz and 39 GHz. In this paper intelligent adaptive transmitter based on trend of the atmospheric conditions tunes to machine learning (ML) based derivation of channel capacity. The ML based transmitter is a supervised ML device and it has provision of self teaching learning machine based on data. Results are graphed for the mentioned frequencies and also intelligently software defined (SD) Shannon channel capacity calculated for Delhi (India) based 5G mmWave communication system under different atmospheric conditions.
Free
Interference Mitigation Techniques for Spectral Capacity Enhancement in GSM Networks
Scientific article
Random Frequency Hopping (FH) is a key feature of GSM networks that allows for capacity enhancement. The increased co-channel interference experienced in networks with tight frequency reuse schemes can be mitigated by adopting frequency hopping. Frequency hopping diversifies the interference signals over sparse transmitted bursts. This effect is called Interference Diversity. Interference Diversity allows the Forward Error Correcting codes (FEC) to easily correct the corrupted bits. Thus, frequency hopping allows the network operator to use a tighter frequency reuse scheme without exhibiting higher levels of co-channel interference. Discontinuous Transmission (DTX) is another interference mitigation method that utilizes the user’s silence frames to reduce the transmitted power, while Power Control (PC) links the transmitted handset power with its relative distance from the Base Station (BTS). In this work, we study the impact of random FH, DTX and PC on the Spectral Capacity of GSM cellular networks by means of combined link level and system level simulation. It is shown that a spectral capacity gain is obtained in a 3/9 reuse scheme that deploys PC, DTX and FH compared to a conventional 4/12 reuse scheme.
Free
Interference Mitigation in Wireless Communication – A Tutorial on Spread Spectrum Technology
Scientific article
This paper focuses on Spread Spectrum technique and its interference mitigation feature as applied in wireless communication. With spread spectrum technology it is possible to implement the transmission of multiple signals over wider ranges of spectrum without resulting to interference from other signals transmitted over the same frequencies. It does this by rejecting any received signal that does not carry the proper code. Interference rejection, one of the several features of spread spectrum technology is a difficult concept to understand. It is therefore proper to x-ray this topic in a less complex manner so that it can be well understood by those who are not mathematically grounded. In view of this a further simplified approach in presenting this subject is necessary. A tutorial approach is used to simplify this subject for better understanding and how this feature is used in Code Division Multiple Access (CDMA) systems. To show how multipath interference rejection is achieved in CDMA systems simple equations and schematics were used. The discussions cover the method of code recognition at the receiver which serves as a technique for interference mitigation. The paper helps to understand the theory of code recognition in Spread Spectrum, and thus provides answer to the question on how does interference mitigation or rejection in spread spectrum works?
Free
Interference mitigation and mobility management for D2D communication in LTE-A networks
Scientific article
Interference and Mobility management are the main parameters which affect the signal capacity and reduce the transmission efficiency for D2D communication in LTE-A networks. When the users are in the same spectrum, due to the coexistence of D2D pairs and cellular users interference management becomes a critical issue. In this paper, we introduce an interference management algorithm that maximizes the performance of D2D communication in LTE-A networks for both uplink and downlink transmissions. Optimal routing selection techniques reduce the total path distance which helps to minimize the interference and improve the overall network capacity. Mobility management is also a challenging issue in IP-mobile networks. When two DUEs change their locations from one BS to the other, handover delay calculation becomes very important to maintain the communication without interruption. In this paper we show power control techniques which helps to reduce the effect of interference and also we addressed a method for the lower delay under complex mobility issues with uninterrupted D2D communication.
Free
Internet Rescue Robots for Disaster Management
Scientific article
The prototype development of Rescue Robot can help search and rescue teams with their difficult and life-saving tasks. Unmanned Aerial vehicles (UAVs) and Unmanned Ground vehicles (UGVs) are viewed as two separate entities. However, upon closer examination, we can classify them into a closely-coupled system where both are just seen as separable parts of the body of one robotic entity, whose body parts can separate temporarily and acquire together again later. In this prototype, a mobile robot UGV can be used as transport and landing station for a light-weight quadcopter UAV. UAV has separable long-range vision system which provides the top view of environment for the UGV, separable images are stitched and transformed into maps and utilized for rescue operations. This rescue robot contains a combination of UGV and UAV. It is equipped with a strong manipulator arm, used for debris removal, shoring operations, and delivering medicines/ food on very rough terrain. It has light detection and ranging (lidar) sensors, cameras, enabling it to look for victims and for mapping semi-destroyed buildings. The UGV can send visual feedback to the operator at a remote location. The UAV drone has a camera for an aerial view and mapping of the place. Working in conjunction with one another and thus the human search and rescue workers, these robotic assets form a strong team, increasing the effectiveness of search and rescue operations. This project aims at the realization of a new generation of search and rescue robot which can work in semi-autonomous and wireless modes and can be used in harsh physical environments of disaster regions to hold out the given tasks more effectively by the utilization of advanced and economic sensors. the problem domain of earthquake disasters and search and rescue processes is clarified with introducing an overview of this project. Disasters unsettle the economic and social stability of society. Shortage of skilled rescue work forces, also because the risks involved in search and rescue operations, are getting foremost problems during an emergency situation. In this paper rescue robot were designed, implemented in a real time environment and analyzed the result.
Free
Interoperability in connected vehicles – a review
Scientific article
The introduction of automated transportation system and implementation of connected vehicle system has made interoperability even more critical than before in order to ensure effective connectivity , consistency , accuracy and reliable performance.Connected vehicles are employed with in vehicle sensor networks to collect , store , process and communicate with neighbouring vehicles to help drivers making life saving decisions. Connected vehicle systems enable the exchange of communication between a vehicle and world. Some vehicles may only receive communication, other vehicles may only send data and some may receive and send data. Hence it is essential that all systems , devices need to work together in a safe, trusted , efficient manner. Devices/Sensors embedded in vehicles follow different communication protocols as the sensors or devices are manufactured by different vendors. Hence management of coordination between devices is of much importance in Dynamic, Mobile, Heterogeneous environments such as connected vehicles. Hence, there is a need to create seamless interoperability to enable connected vehicles. It is required to enable intelligent transportation system (ITS) system/devices in Vehicles to effectively connect and communicate with other systems/devices. The adaptability of Interoperability when the devices are adhere to dynamics and mobile in nature becomes tedious and cumbersome. Solutions to interoperability is not much explored in literature. Existing interoperability solutions does not guarantee to articulate for high mobile environments such as connected vehicles where vehicles are highly mobile in nature and moving at varying speeds. The paper summarizes connected vehicles issues and challenges, current interoperability solutions, the impact of interoperability in connected vehicle scenario and demonstrates the effect of conversion time delay when exchanging data between source and destination pairs.
Free
