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  • 1
    Online Resource
    Online Resource
    Energy Efficient and Secure Information Dissemination in Heterogeneous Wireless Sensor Networks Using Machine Learning Techniques
    Hindawi Limited ; 2022
    In:  Wireless Communications and Mobile Computing Vol. 2022 ( 2022-6-7), p. 1-14
    Details
    In: Wireless Communications and Mobile Computing, Hindawi Limited, Vol. 2022 ( 2022-6-7), p. 1-14
    Abstract: The extensive use of sensor technology in every sphere of life, along with the continuous digitization of society, makes it realistic to anticipate that the planet will soon be patched with small-sized devices all over the place in the not-too-distant future. These devices give monitoring and surveillance capabilities, as well as access to a vast digital universe of information, among other things. Finding data and information, as well as processing enquiries, is made much easier thanks to the seamless transmission of information over wireless media, which is based on the “anywhere, anytime, everywhere” paradigm that allows information to be sent anywhere, at any time. Sensing networks came into existence as a consequence of the downsizing of wireless devices that are capable of receiving information from a source, transferring it, and processing it. Sensor networks, although they share many of the features, uses, and limits of ad hoc networks, have their own set of capabilities that are unique to them. While performing their responsibilities, sensor networks must contend with a variety of security issues, including unsecured wireless channels, physical compromise, and reprogramming. Because of the small size and ubiquitous availability of wireless sensor networks, compromise attacks are the most severe kind of attack in this environment (WSNs). With the proliferation of wireless sensor networks (WSNs), it is becoming more difficult to rely only on machine learning techniques. We sought to tackle the security challenge by developing a key management system as well as a secure routing mechanism. We are building scalable key management approaches that are resistant to node compromise and node replication attacks, which we will demonstrate in our proposed study, by using deployment-driven localization of security information and leveraging distributed key management. Using a security-aware selection of the next hop on the route to the destination, we were able to design safe routing algorithms that were effective.
    Type of Medium: Online Resource
    ISSN: 1530-8677 , 1530-8669
    URL: Article
    DOI: 10.1155/2022/2206530
    Language: English
    Publisher: Hindawi Limited
    Publication Date: 2022
    detail.hit.zdb_id: 2045240-8
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  • 2
    Online Resource
    Online Resource
    Local Binary Patterns Based on Neighbor-Center Difference Image for Color Texture Classification with Machine Learning Techniques
    Hindawi Limited ; 2022
    In:  Wireless Communications and Mobile Computing Vol. 2022 ( 2022-8-8), p. 1-11
    Details
    In: Wireless Communications and Mobile Computing, Hindawi Limited, Vol. 2022 ( 2022-8-8), p. 1-11
    Abstract: This is a topic that receives a lot of interest since many applications of computer vision focus on the detection of objects in visually appealing environments. Information about an object’s appearance and information regarding the object’s motion are both used as crucial signals in the process of identifying and recognising any given item. This information is used to characterise and recognise the item. The identification of objects based solely on their outward appearance has been the subject of a substantial amount of research. However, motion information in the recognition task has received only a marginal amount of attention, despite the fact that motion plays an essential role in the process of recognition. In order to analyze a moving picture in a way that is both fast and accurate, it is required to make use of motion information in conjunction with surface appearance in a strategy that has been designed. Dynamic texture is a kind of visual phenomenon that may be characterised as a type of visual phenomenon that shows spatially repeated features as well as some stationary properties during the course of time by using methodologies that are associated with machine learning. The design of modern VLSI systems takes into consideration a larger chip density, which results in a processor architecture with several cores that are capable of performing a wide range of functions (multicore processor architecture). It is becoming more challenging to run such complicated systems without the use of electric power. In order to increase the effectiveness of power optimization strategies while maintaining system performance for text data extraction, it has been developed and put into practice power optimization strategies that are based on scheduling algorithms. Over the last twenty years, texture analysis has been an increasingly busy and profitable field of study. Today, texture interpretation plays a vital role in various activities ranging from remote sensing to medical picture analysis. The absence of tools to newline analyze the many properties of texture pictures was the primary challenge faced by the texture analysis approach. Texture analysis may be roughly categorised as texture classification, texture segmentation, texture synthesis, and texture synthesis. Texture categorization is useful in numerous applications, such as the retrieval of picture databases, industrial agriculture applications, and biomedical applications. Texture categorization relies on three distinct methods, namely, statistical, spectral, and structural methods. Statistical methods are based on the statistical characteristics of the image’s grey level. Features are collected using second order statistical order, autocorrelation function, and grey level co-occurrence matrix function.
    Type of Medium: Online Resource
    ISSN: 1530-8677 , 1530-8669
    URL: Article
    DOI: 10.1155/2022/1191492
    Language: English
    Publisher: Hindawi Limited
    Publication Date: 2022
    detail.hit.zdb_id: 2045240-8
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  • 3
    Online Resource
    Online Resource
    Accurate Base Station Placement in 4G LTE Networks Using Multiobjective Genetic Algorithm Optimization
    Hindawi Limited ; 2023
    In:  Wireless Communications and Mobile Computing Vol. 2023 ( 2023-2-11), p. 1-9
    Details
    In: Wireless Communications and Mobile Computing, Hindawi Limited, Vol. 2023 ( 2023-2-11), p. 1-9
    Abstract: Cellular mobile communication network planning and optimization involve a complex engineering process that deals with network fundamentals, radio resource elements, and critical decision variables. The continuous evolution of radio access technologies provides new challenges that necessitate efficient radio planning and optimization. Therefore, the planning and optimization algorithms should be highly efficient, advanced, and robust. An important component of 4G LTE network planning is the proper placement of evolved node base stations (eNodeBs) and the configuration of their antenna elements. This contribution proposes a multiobjective genetic algorithm that integrates network coverage, capacity, and power consumption for optimal eNodeB placement in an operational 4G LTE network. The multi-objective-based genetic algorithm optimization has been achieved using the optimization toolbox in MATLAB. By leveraging the proposed method, the effect of different population sizes on the cost of placing the eNodeBs and the percentage coverage of the eNodeBs in a given cell is determined. As a result, the optimal selection technique that minimizes the total network cost without compromising the desired coverage and capacity benchmarks is achieved. The proposed automatic eNodeB antenna placement method can be explored to optimize 4G LTE cellular network planning in related wireless propagation environments.
    Type of Medium: Online Resource
    ISSN: 1530-8677 , 1530-8669
    URL: Article
    DOI: 10.1155/2023/7476736
    Language: English
    Publisher: Hindawi Limited
    Publication Date: 2023
    detail.hit.zdb_id: 2045240-8
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  • 4
    Online Resource
    Online Resource
    Realistic Prognostic Modeling of Specific Attenuation due to Rain at Microwave Frequency for Tropical Climate Region
    Hindawi Limited ; 2022
    In:  Wireless Communications and Mobile Computing Vol. 2022 ( 2022-4-14), p. 1-10
    Details
    In: Wireless Communications and Mobile Computing, Hindawi Limited, Vol. 2022 ( 2022-4-14), p. 1-10
    Abstract: Absorption and scattering of propagated microwave radio signals by atmospheric variables, particularly rainfall, remained a major cause of propagation attenuation losses and service quality degradation over terrestrial communication links. The International Telecommunications Union Radio (ITU-R) reports and other related works in the literature provided information on attenuation due to rain and microwave propagation data. Such propagation attenuation information in the tropical region of Nigeria is destitute, especially at lower radio waves transmission frequencies. Therefore, this study addresses this problem by employing 12-year rainfall datasets to conduct realistic prognostic modeling of rain rate intensity levels. A classification of the rainfall data into three subgroups based on the depth of rainfall in the region is presented. Additionally, an in-depth estimation of specific rain attenuation intensities based on the 12-year rainfall data at 3.5 GHz is demonstrated. On average, the three rainfall classes produced rain rates of about 29.27 mm/hr, 73.71 mm/hr, and 105.39 mm/hr. The respective attenuation values are 0.89 dB, 1.71 dB, and 2.13 dB for the vertical polarisation and 1.09 dB, 1.20 dB, and 2.78 dB for the horizontal polarisation at 0.01% time percentage computation. Generally, results indicate that higher rain attenuation of 12% is observed for the horizontal polarisation compared to the vertical polarisation. These results can provide valuable first-hand information for microwave radio frequency planning in making appropriate decisions on attenuation levels due to different rainfall depths, especially for lower frequency arrays.
    Type of Medium: Online Resource
    ISSN: 1530-8677 , 1530-8669
    URL: Article
    DOI: 10.1155/2022/8209256
    Language: English
    Publisher: Hindawi Limited
    Publication Date: 2022
    detail.hit.zdb_id: 2045240-8
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