S. Soundararajan^1,*, B. R. Tapas Bapu², C. Kotteeswaran¹, S. Venkatasubramanian³, P. J. Sathish Kumar⁴, Ahmed Mudassar Ali²

Intelligent Automation & Soft Computing, Vol.36, No.2, pp. 1227-1240, 2023, DOI:10.32604/iasc.2023.025752

Abstract Recently, Wireless Sensor Network (WSN) becomes most potential technologies for providing improved services to several data gathering and tracking applications. Because of the wireless medium, multi-hop communication, absence of physical protectivity, and accumulated traffic, WSN is highly vulnerable to security concerns. Therefore, this study explores a specific type of DoS attack identified as a selective forwarding attack where the misbehaving node in the network drops packet on a selective basis. It is challenging to determine if packet loss is caused by a collision in the medium access path, poor channel quality, or a selective forwarding assault. Identifying misbehaving nodes at… More >

S. Sandhiyaa^*, C. Gomathy

CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 4747-4768, 2023, DOI:10.32604/cmc.2023.032298

Abstract The nodes in the sensor network have a wide range of uses, particularly on under-sea links that are skilled for detecting, handling as well as management. The underwater wireless sensor networks support collecting pollution data, mine survey, oceanographic information collection, aided navigation, strategic surveillance, and collection of ocean samples using detectors that are submerged in water. Localization, congestion routing, and prioritizing the traffic is the major issue in an underwater sensor network. Our scheme differentiates the different types of traffic and gives every type of traffic its requirements which is considered regarding network resource. Minimization of localization error using the… More >

P. Saranya^*, P. Asha

Intelligent Automation & Soft Computing, Vol.36, No.1, pp. 1137-1149, 2023, DOI:10.32604/iasc.2023.031470

Abstract In today’s growing modern world environment, as human food activities are changing, it is affecting human health, thus leading to diseases like cancer. Cancer is a complex disease with many subtypes that affect human health without premature treatment and cause death. So the analysis of early diagnosis and prognosis of cancer studies can improve clinical management by analyzing various features of observation, which has become necessary to classify the type in cancer research. The research needs importance to organize the risk of the cancer patients based on data analysis to predict the result of premature treatment. This paper introduces a… More >

Aqsa Aqdus¹, Rashid Amin^1,*, Sadia Ramzan¹, Sultan S. Alshamrani², Abdullah Alshehri³, El-Sayed M. El-kenawy⁴

CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 1413-1435, 2023, DOI:10.32604/cmc.2023.031719

Abstract The rapid advancement of wireless communication is forming a hyper-connected 5G network in which billions of linked devices generate massive amounts of data. The traffic control and data forwarding functions are decoupled in software-defined networking (SDN) and allow the network to be programmable. Each switch in SDN keeps track of forwarding information in a flow table. The SDN switches must search the flow table for the flow rules that match the packets to handle the incoming packets. Due to the obvious vast quantity of data in data centres, the capacity of the flow table restricts the data plane’s forwarding capabilities.… More >

Jiangyuan Yao¹, Zheng Jiang², Kaiwen Zou², Shuhua Weng¹, Yaxin Li³, Deshun Li¹, Yahui Li^4,*, Xingcan Cao⁵

CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 293-311, 2023, DOI:10.32604/cmc.2023.031282

Abstract With the expansion of network services, large-scale networks have progressively become common. The network status changes rapidly in response to customer needs and configuration changes, so network configuration changes are also very frequent. However, no matter what changes, the network must ensure the correct conditions, such as isolating tenants from each other or guaranteeing essential services. Once changes occur, it is necessary to verify the after-changed network. Whereas, for the verification of large-scale network configuration changes, many current verifiers show poor efficiency. In order to solve the problem of multiple global verifications caused by frequent updates of local configurations in… More >

Baoge Zhang¹, Shanyan Ping^1,*, Haoliang Shi², Yi Long¹, Boxiang Wu¹, Yuemin Jiao¹

Energy Engineering, Vol.119, No.6, pp. 2347-2367, 2022, DOI:10.32604/ee.2022.021693

Abstract Renewable energy is connected to the grid through the inverter, which in turn reduces the inertia and stability of the power grid itself. The traditional grid-connected inverter does not have the function of voltage regulation and frequency regulation and can therefore no longer adapt to the new development. The virtual synchronous generator (VSG) has the function of voltage regulation and frequency regulation, which has more prominent advantages than traditional inverters. Based on the principle of VSG, the relationship between the frequency characteristics and the energy storage capacity of the feedforward branch-based virtual synchronous machine (FVSG) is derived when the input… More >

C. Edwin Singh^1,*, S. Maria Celestin Vigila²

Intelligent Automation & Soft Computing, Vol.35, No.2, pp. 1737-1751, 2023, DOI:10.32604/iasc.2023.028022

Abstract Mobile ad-hoc networks (MANET) are garnering a lot of attention because of their potential to provide low-cost solutions to real-world communications. MANETs are more vulnerable to security threats. Changes in nodes, bandwidth limits, and centralized control and management are some of the characteristics. IDS (Intrusion Detection System) are the aid for detection, determination, and identification of illegal system activity such as use, copying, modification, and destruction of data. To address the identified issues, academics have begun to concentrate on building IDS-based machine learning algorithms. Deep learning is a type of machine learning that can produce exceptional outcomes. This study proposes… More >

D. Anitha^1,*, R. A. Karthika²

Intelligent Automation & Soft Computing, Vol.35, No.2, pp. 2463-2477, 2023, DOI:10.32604/iasc.2023.023361

Abstract Achieving sound communication systems in Under Water Acoustic (UWA) environment remains challenging for researchers. The communication scheme is complex since these acoustic channels exhibit uneven characteristics such as long propagation delay and irregular Doppler shifts. The development of machine and deep learning algorithms has reduced the burden of achieving reliable and good communication schemes in the underwater acoustic environment. This paper proposes a novel intelligent selection method between the different modulation schemes such as Code Division Multiple Access(CDMA), Time Division Multiple Access(TDMA), and Orthogonal Frequency Division Multiplexing(OFDM) techniques using the hybrid combination of the convolutional neural networks(CNN) and ensemble single… More >

Amel Boudelaa¹, Zohra Abdelhafidi¹, Nasreddine Lagraa¹, Chaker Abdelaziz Kerrache¹, Muhammad Bilal², Daehan Kwak^3,*, Mohamed Bachir Yagoubi¹

CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 2495-2512, 2022, DOI:10.32604/cmc.2022.028619

Abstract Vehicular Social Networks (VSNs) is the bridge of social networks and Vehicular Ad-Hoc Networks (VANETs). VSNs are promising as they allow the exchange of various types of contents in large-scale through Vehicle-to-Vehicle (V2V) and Vehicle-to-Infrastructure (V2I) communication protocols. Vehicular Named Data Networking (VNDN) is an auspicious communication paradigm for the challenging VSN environment since it can optimize content dissemination by decoupling contents from their physical locations. However, content dissemination and caching represent crucial challenges in VSNs due to short link lifetime and intermittent connectivity caused by vehicles’ high mobility. Our aim with this paper is to improve content delivery and… More >

Mofreh A. Hogo^*

CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 2947-2966, 2022, DOI:10.32604/cmc.2022.027300

Abstract Data size plays a significant role in the design and the performance of data mining models. A good feature selection algorithm reduces the problems of big data size and noise due to data redundancy. Features selection algorithms aim at selecting the best features and eliminating unnecessary ones, which in turn simplifies the structure of the data mining model as well as increases its performance. This paper introduces a robust features selection algorithm, named Features Ranking Voting Algorithm FRV. It merges the benefits of the different features selection algorithms to specify the features ranks in the dataset correctly and robustly; based… More >