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  • Open Access

    ARTICLE

    A Double Threshold Energy Detection-Based Neural Network for Cognitive Radio Networks

    Nada M. Elfatih1, Elmustafa Sayed Ali1,5, Maha Abdelhaq2, Raed Alsaqour3,*, Rashid A. Saeed4

    Computer Systems Science and Engineering, Vol.45, No.1, pp. 329-342, 2023, DOI:10.32604/csse.2023.028528

    Abstract

    In cognitive radio networks (CoR), the performance of cooperative spectrum sensing is improved by reducing the overall error rate or maximizing the detection probability. Several optimization methods are usually used to optimize the number of user-chosen for cooperation and the threshold selection. However, these methods do not take into account the effect of sample size and its effect on improving CoR performance. In general, a large sample size results in more reliable detection, but takes longer sensing time and increases complexity. Thus, the locally sensed sample size is an optimization problem. Therefore, optimizing the local sample size for each cognitive… More >

  • Open Access

    ARTICLE

    Topology Driven Cooperative Self Scheduling for Improved Lifetime Maximization in WSN

    G. Brindha1,*, P. Ezhilarasi2

    Computer Systems Science and Engineering, Vol.45, No.1, pp. 445-458, 2023, DOI:10.32604/csse.2023.027329

    Abstract In Wireless Sensor Network (WSN), scheduling is one of the important issues that impacts the lifetime of entire WSN. Various scheduling schemes have been proposed earlier to increase the lifetime of the network. Still, the results from such methods are compromised in terms of achieving high lifetime. With this objective to increase the lifetime of network, an Efficient Topology driven Cooperative Self-Scheduling (TDCSS) model is recommended in this study. Instead of scheduling the network nodes in a centralized manner, a combined approach is proposed. Based on the situation, the proposed TDCSS approach performs scheduling in both the ways. By sharing… More >

  • Open Access

    ARTICLE

    Optimized Cognitive Learning Model for Energy Efficient Fog-BAN-IoT Networks

    S. Kalpana1,*, C. Annadurai2

    Computer Systems Science and Engineering, Vol.43, No.3, pp. 1027-1040, 2022, DOI:10.32604/csse.2022.024685

    Abstract In Internet of Things (IoT), large amount of data are processed and communicated through different network technologies. Wireless Body Area Networks (WBAN) plays pivotal role in the health care domain with an integration of IoT and Artificial Intelligence (AI). The amalgamation of above mentioned tools has taken the new peak in terms of diagnosis and treatment process especially in the pandemic period. But the real challenges such as low latency, energy consumption high throughput still remains in the dark side of the research. This paper proposes a novel optimized cognitive learning based BAN model based on Fog-IoT technology as a… More >

  • Open Access

    ARTICLE

    Mean Opinion Score Estimation for Mobile Broadband Networks Using Bayesian Networks

    Ayman A. El-Saleh1, Abdulraqeb Alhammadi2,*, Ibraheem Shayea3, Azizul Azizan4, Wan Haslina Hassan2

    CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 4571-4587, 2022, DOI:10.32604/cmc.2022.024642

    Abstract Mobile broadband (MBB) networks are expanding rapidly to deliver higher data speeds. The fifth-generation cellular network promises enhanced-MBB with high-speed data rates, low power connectivity, and ultra-low latency video streaming. However, existing cellular networks are unable to perform well due to high latency and low bandwidth, which degrades the performance of various applications. As a result, monitoring and evaluation of the performance of these network-supported services is critical. Mobile network providers optimize and monitor their network performance to ensure the highest quality of service to their end-users. This paper proposes a Bayesian model to estimate the minimum opinion score (MOS)… More >

  • Open Access

    ARTICLE

    QoS Aware Multicast Routing Protocol for Video Transmission in Smart Cities

    Khaled Mohamad Almustafa1, Taiseer Abdalla Elfadil Eisa2, Amani Abdulrahman Albraikan3, Mesfer Al Duhayyim4,*, Manar Ahmed Hamza5, Abdelwahed Motwakel5, Ishfaq Yaseen5, Muhammad Imran Babar6

    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 2483-2499, 2022, DOI:10.32604/cmc.2022.024688

    Abstract In recent years, Software Defined Networking (SDN) has become an important candidate for communication infrastructure in smart cities. It produces a drastic increase in the need for delivery of video services that are of high resolution, multiview, and large-scale in nature. However, this entity gets easily influenced by heterogeneous behaviour of the user's wireless link features that might reduce the quality of video stream for few or all clients. The development of SDN allows the emergence of new possibilities for complicated controlling of video conferences. Besides, multicast routing protocol with multiple constraints in terms of Quality of Service (QoS) is… More >

  • Open Access

    ARTICLE

    QoS in FANET Business and Swarm Data

    Jesús Hamilton Ortiz1, Carlos Andrés Tavera Romero2,*, Bazil Taha Ahmed3, Osamah Ibrahim Khalaf4

    CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 1877-1899, 2022, DOI:10.32604/cmc.2022.023796

    Abstract This article shows the quality of services in a wireless swarm of drones that form an ad hoc network between them Fly Ad Hoc Networks (FANET). Each drone has the ability to send and receive information (like a router); and can behave as a hierarchical node whit the intregration of three protocols: Multiprotocol Label Switch (MPLS), Fast Hierarchical AD Hoc Mobile (FHAM) and Internet Protocol version 6 (IPv6), in conclusion MPLS + FHAM + IPv6. The metrics analyzed in the FANET are: delay, jitter, throughput, lost and sent packets/received. Testing process was carried out with swarms composed of 10, 20,… More >

  • Open Access

    ARTICLE

    Non-Cooperative Learning Based Routing for 6G-IoT Cognitive Radio Network

    Tauqeer Safdar Malik1,*, Kaleem Razzaq Malik1, Muhammad Sanaullah2, Mohd Hilmi Hasan3, Norshakirah Aziz3

    Intelligent Automation & Soft Computing, Vol.33, No.2, pp. 809-824, 2022, DOI:10.32604/iasc.2022.021128

    Abstract Cognitive Radio Network (CRN) has turn up to solve the issue of spectrum congestion occurred due to the wide spread usage of wireless applications for 6G based Internet of Things (IoT) network. The Secondary Users (SUs) are allowed to access dynamically the frequency channels owned by the Primary Users (PUs). In this paper, we focus the matter of contention of routing in multi hops setup by the SUs for a known destination in the presence of PUs. The traffic model for routing is generated on the basis of Poison Process of Markov Model. Every SU requires to reduce the end-to-end… More >

  • Open Access

    ARTICLE

    Intelligent Model for Predicting the Quality of Services Violation

    Muhammad Adnan Khan1,2, Asma Kanwal3, Sagheer Abbas3, Faheem Khan4, T. Whangbo4,*

    CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 3607-3619, 2022, DOI:10.32604/cmc.2022.023480

    Abstract Cloud computing is providing IT services to its customer based on Service level agreements (SLAs). It is important for cloud service providers to provide reliable Quality of service (QoS) and to maintain SLAs accountability. Cloud service providers need to predict possible service violations before the emergence of an issue to perform remedial actions for it. Cloud users’ major concerns; the factors for service reliability are based on response time, accessibility, availability, and speed. In this paper, we, therefore, experiment with the parallel mutant-Particle swarm optimization (PSO) for the detection and predictions of QoS violations in terms of response time, speed,… More >

  • Open Access

    ARTICLE

    Multi-Agent Deep Q-Networks for Efficient Edge Federated Learning Communications in Software-Defined IoT

    Prohim Tam1, Sa Math1, Ahyoung Lee2, Seokhoon Kim1,3,*

    CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 3319-3335, 2022, DOI:10.32604/cmc.2022.023215

    Abstract Federated learning (FL) activates distributed on-device computation techniques to model a better algorithm performance with the interaction of local model updates and global model distributions in aggregation averaging processes. However, in large-scale heterogeneous Internet of Things (IoT) cellular networks, massive multi-dimensional model update iterations and resource-constrained computation are challenging aspects to be tackled significantly. This paper introduces the system model of converging software-defined networking (SDN) and network functions virtualization (NFV) to enable device/resource abstractions and provide NFV-enabled edge FL (eFL) aggregation servers for advancing automation and controllability. Multi-agent deep Q-networks (MADQNs) target to enforce a self-learning softwarization, optimize resource allocation… More >

  • Open Access

    ARTICLE

    Adaptive Quality-of-Service Allocation Scheme for Improving Video Quality over a Wireless Network

    Raed Alsaqour1, Ammar Hadi2, Maha Abdelhaq3,*

    Intelligent Automation & Soft Computing, Vol.32, No.2, pp. 675-692, 2022, DOI:10.32604/iasc.2022.020482

    Abstract The need to ensure the quality of video streaming transmitted over wireless networks is growing every day. Video streaming is typically used for applications that are sensitive to poor quality of service (QoS) due to insufficient bandwidth, packet loss, or delay. These challenges hurt video streaming quality since they affect throughput and packet delivery of the transmitted video. To achieve better video streaming quality, throughput must be high, with minimal packet delay and loss ratios. A current study, however, found that the adoption of the adaptive multiple TCP connections (AM-TCP), as a transport layer protocol, improves the quality of video… More >

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