Open Access

ARTICLE

Jin Wang¹, Wei Ou¹, Osama Alfarraj², Amr Tolba², Gwang-Jun Kim^3,*, Yongjun Ren⁴
Computer Systems Science and Engineering, Vol.45, No.2, pp. 1805-1819, 2023, DOI:10.32604/csse.2023.029622
Abstract Since transactions in blockchain are based on public ledger verification, this raises security concerns about privacy protection. And it will cause the accumulation of data on the chain and resulting in the low efficiency of block verification, when the whole transaction on the chain is verified. In order to improve the efficiency and privacy protection of block data verification, this paper proposes an efficient block verification mechanism with privacy protection based on zero-knowledge proof (ZKP), which not only protects the privacy of users but also improves the speed of data block verification. There is no need to put the whole… More >

View

1321

Download

1004

Open Access

ARTICLE

K. Madumathi^1,*, S. Chandrasekar²
Computer Systems Science and Engineering, Vol.45, No.2, pp. 1821-1836, 2023, DOI:10.32604/csse.2023.029561
Abstract Artificial intelligence, machine learning and deep learning algorithms have been widely used for Maximum Power Point Tracking (MPPT) in solar systems. In the traditional MPPT strategies, following of worldwide Global Maximum Power Point (GMPP) under incomplete concealing conditions stay overwhelming assignment and tracks different nearby greatest power focuses under halfway concealing conditions. The advent of artificial intelligence in MPPT has guaranteed of accurate following of GMPP while expanding the significant performance and efficiency of MPPT under Partial Shading Conditions (PSC). Still the selection of an efficient learning based MPPT is complex because each model has its advantages and drawbacks. Recently,… More >

View

729

Download

525

Open Access

ARTICLE

K. Kamaraj^1,*, B. Lanitha², S. Karthic³, P. N. Senthil Prakash⁴, R. Mahaveerakannan⁵
Computer Systems Science and Engineering, Vol.45, No.2, pp. 1837-1850, 2023, DOI:10.32604/csse.2023.029703
Abstract Software testing is the methodology of analyzing the nature of software to test if it works as anticipated so as to boost its reliability and quality. These two characteristics are very critical in the software applications of present times. When testers want to perform scenario evaluations, test oracles are generally employed in the third phase. Upon test case execution and test outcome generation, it is essential to validate the results so as to establish the software behavior’s correctness. By choosing a feasible technique for the test case optimization and prioritization as along with an appropriate assessment of the application, leads… More >

View

1010

Download

517

Open Access

ARTICLE

V. Harshini¹, T. Dhanwin¹, A. Shahina^1,*, N. Safiyyah², A. Nayeemulla Khan²
Computer Systems Science and Engineering, Vol.45, No.2, pp. 1851-1867, 2023, DOI:10.32604/csse.2023.028136
Abstract Biometrics, which has become integrated with our daily lives, could fall prey to falsification attacks, leading to security concerns. In our paper, we use Transient Evoked Otoacoustic Emissions (TEOAE) that are generated by the human cochlea in response to an external sound stimulus, as a biometric modality. TEOAE are robust to falsification attacks, as the uniqueness of an individual’s inner ear cannot be impersonated. In this study, we use both the raw 1D TEOAE signals, as well as the 2D time-frequency representation of the signal using Continuous Wavelet Transform (CWT). We use 1D and 2D Convolutional Neural Networks (CNN) for… More >

View

919

Download

384

Like

2

Open Access

ARTICLE

V. Divya^1,*, S. Sendil Kumar², V. Gokula Krishnan³, Manoj Kumar⁴
Computer Systems Science and Engineering, Vol.45, No.2, pp. 1869-1886, 2023, DOI:10.32604/csse.2023.029762
Abstract Signal processing based research was adopted with Electroencephalogram (EEG) for predicting the abnormality and cerebral activities. The proposed research work is intended to provide an automatic diagnostic system to determine the EEG signal in order to classify the brain function which shows whether a person is affected with schizophrenia or not. Early detection and intervention are vital for better prognosis. However, the diagnosis of schizophrenia still depends on clinical observation to date. Without reliable biomarkers, schizophrenia is difficult to detect in its early phase and hence we have proposed this idea. In this work, the EEG signal series are divided… More >

View

1061

Download

367

Open Access

ARTICLE

P. Gomathi^1,*, C. Muniraj², P. S. Periasamy³
Computer Systems Science and Engineering, Vol.45, No.2, pp. 1887-1899, 2023, DOI:10.32604/csse.2023.028808
Abstract The mortality rate decreases as the early detection of Breast Cancer (BC) methods are emerging very fast, and when the starting stage of BC is detected, it is curable. The early detection of the disease depends on the image processing techniques, and it is used to identify the disease easily and accurately, especially the micro calcifications are visible on mammography when they are 0.1 mm or bigger, and cancer cells are about 0.03 mm, which is crucial for identifying in the BC area. To achieve this micro calcification in the BC images, it is necessary to focus on the four… More >

View

715

Download

436

Open Access

ARTICLE

Abdllkader Esaid^1,*, Mary Agoyi²
Computer Systems Science and Engineering, Vol.45, No.2, pp. 1901-1915, 2023, DOI:10.32604/csse.2023.027819
Abstract Mobile Ad hoc Network (MANET) is decentralized wireless network and can communicate without existing infrastructure in many areas. MANET is vulnerable to various attacks that affect its performance such as blackhole attack. Blackhole attacker, inject fault routing information to persuade the source node to select the path with malicious node as the shortest path. To eliminate malicious nodes from launching any collaborative attack. A cooperative Trapping Approach (CTA) was proposed based on modifying Ad-hoc On-demand Distance Vector (AODV) routing protocol and trapping the malicious nodes by responding to the trap request message. The approach aims to eliminate and rule out… More >

View

634

Download

356

Open Access

ARTICLE

El-Sayed M. El-kenawy^1,2, Abdelaziz A. Abdelhamid^3,4, Abdelhameed Ibrahim⁵, Seyedali Mirjalili^6,7, Nima Khodadad⁸, Mona A. Al duailij⁹, Amel Ali Alhussan^9,*, Doaa Sami Khafaga⁹
Computer Systems Science and Engineering, Vol.45, No.2, pp. 1917-1934, 2023, DOI:10.32604/csse.2023.032497
Abstract Metaheuristic optimization algorithms present an effective method for solving several optimization problems from various types of applications and fields. Several metaheuristics and evolutionary optimization algorithms have been emerged recently in the literature and gained widespread attention, such as particle swarm optimization (PSO), whale optimization algorithm (WOA), grey wolf optimization algorithm (GWO), genetic algorithm (GA), and gravitational search algorithm (GSA). According to the literature, no one metaheuristic optimization algorithm can handle all present optimization problems. Hence novel optimization methodologies are still needed. The Al-Biruni earth radius (BER) search optimization algorithm is proposed in this paper. The proposed algorithm was motivated by… More >

View

1321

Download

866

Like

2

Open Access

ARTICLE

Pankaj Kumar Sharma^1,*, Uma Shankar Modani²
Computer Systems Science and Engineering, Vol.45, No.2, pp. 1935-1951, 2023, DOI:10.32604/csse.2023.031509
Abstract The mobile transient and sensor network’s routing algorithm detects available multi-hop paths between source and destination nodes. However, some methods are not as reliable or trustworthy as expected. Therefore, finding a reliable method is an important factor in improving communication security. For further enhancement of protected communication, we suggest a trust cluster based secure routing (TCSR) framework for wireless sensor network (WSN) using optimization algorithms. First, we introduce an efficient cluster formation using a modified tug of war optimization (MTWO) algorithm, which provides load-balanced clusters for energy-efficient data transmission. Second, we illustrate the optimal head selection using multiple design constraints… More >

View

625

Download

401

Open Access

ARTICLE

M. Jamuna Rani^1,*, C. Vasanthanayaki²
Computer Systems Science and Engineering, Vol.45, No.2, pp. 1953-1970, 2023, DOI:10.32604/csse.2023.028713
Abstract Underwater imagery and transmission possess numerous challenges like lower signal bandwidth, slower data transmission bit rates, Noise, underwater blue/green light haze etc. These factors distort the estimation of Region of Interest and are prime hurdles in deploying efficient compression techniques. Due to the presence of blue/green light in underwater imagery, shape adaptive or block-wise compression techniques faces failures as it becomes very difficult to estimate the compression levels/coefficients for a particular region. This method is proposed to efficiently deploy an Extreme Learning Machine (ELM) model-based shape adaptive Discrete Cosine Transformation (DCT) for underwater images. Underwater color image restoration techniques based… More >

View

550

Download

458

Open Access

ARTICLE

Sowjanya Ramisetty^1,2, Divya Anand², Kavita^3,*, Sahil Verma³, NZ Jhanjhi⁴, Mehedi Masud⁵, Mohammed Baz⁶
Computer Systems Science and Engineering, Vol.45, No.2, pp. 1971-1983, 2023, DOI:10.32604/csse.2022.021924
Abstract For achieving Energy-Efficiency in wireless sensor networks (WSNs), different schemes have been proposed which focuses only on reducing the energy consumption. A shortest path determines for the Base Station (BS), but fault tolerance and energy balancing gives equal importance for improving the network lifetime. For saving energy in WSNs, clustering is considered as one of the effective methods for Wireless Sensor Networks. Because of the excessive overload, more energy consumed by cluster heads (CHs) in a cluster based WSN to receive and aggregate the information from member sensor nodes and it leads to failure. For increasing the WSNs’ lifetime, the… More >

View

827

Download

470

Like

1

Open Access

ARTICLE

S. Sudha^*, A. Srinivasan, T. Gayathri Devi
Computer Systems Science and Engineering, Vol.45, No.2, pp. 1985-2000, 2023, DOI:10.32604/csse.2023.030960
Abstract The substantial vision loss due to Diabetic Retinopathy (DR) mainly damages the blood vessels of the retina. These feature changes in the blood vessels fail to exist any manifestation in the eye at its initial stage, if this problem doesn’t exhibit initially, that leads to permanent blindness. So, this type of disorder can be only screened and identified through the processing of fundus images. The different stages in DR are Micro aneurysms (Ma), Hemorrhages (HE), and Exudates, and the stages in lesion show the chance of DR. For the advancement of early detection of DR in the eye we have… More >

View

684

Download

357

Like

1

Open Access

ARTICLE

Sharmilee Kannan^1,*, R. U. Anitha², M. Divayapushpalakshmi³, K. S. Kalaivani⁴
Computer Systems Science and Engineering, Vol.45, No.2, pp. 2001-2016, 2023, DOI:10.32604/csse.2023.031965
Abstract The rising use of mobile technology and smart gadgets in the field of health has had a significant impact on the global community. Health professionals are increasingly making use of the benefits of these technologies, resulting in a major improvement in health care both in and out of clinical settings. The Internet of Things (IoT) is a new internet revolution that is a rising research area, particularly in health care. Healthcare Monitoring Systems (HMS) have progressed rapidly as the usage of Wearable Sensors (WS) and smartphones have increased. The existing framework of conventional telemedicine’s store-and-forward method has some issues, including… More >

View

1028

Download

403

Open Access

ARTICLE

K. Jagadeesh^1,*, A. Rajendran²
Computer Systems Science and Engineering, Vol.45, No.2, pp. 2017-2032, 2023, DOI:10.32604/csse.2023.029169
Abstract Lung Cancer is one of the hazardous diseases that have to be detected in earlier stages for providing better treatment and clinical support to patients. For lung cancer diagnosis, the computed tomography (CT) scan images are to be processed with image processing techniques and effective classification process is required for appropriate cancer diagnosis. In present scenario of medical data processing, the cancer detection process is very time consuming and exactitude. For that, this paper develops an improved model for lung cancer segmentation and classification using genetic algorithm. In the model, the input CT images are pre-processed with the filters called… More >

View

1093

Download

387

Like

1

Open Access

ARTICLE

Anwer Mustafa Hilal^1,2,*, Aisha Hassan Abdalla Hashim¹, Heba G. Mohamed³, Lubna A. Alharbi⁴, Mohamed K. Nour⁵, Abdullah Mohamed⁶, Ahmed S. Almasoud⁷, Abdelwahed Motwakel²
Computer Systems Science and Engineering, Vol.45, No.2, pp. 2033-2047, 2023, DOI:10.32604/csse.2023.031181
Abstract Recent developments on Internet and social networking have led to the growth of aggressive language and hate speech. Online provocation, abuses, and attacks are widely termed cyberbullying (CB). The massive quantity of user generated content makes it difficult to recognize CB. Current advancements in machine learning (ML), deep learning (DL), and natural language processing (NLP) tools enable to detect and classify CB in social networks. In this view, this study introduces a spotted hyena optimizer with deep learning driven cybersecurity (SHODLCS) model for OSN. The presented SHODLCS model intends to accomplish cybersecurity from the identification of CB in the OSN.… More >

View

950

Download

399

Open Access

ARTICLE

Aravindan Madhavan^1,*, Yamuna Govindarajan¹, Neelakandan Rajamohan²
Computer Systems Science and Engineering, Vol.45, No.2, pp. 2049-2058, 2023, DOI:10.32604/csse.2023.031566
Abstract In an underdetermined system, compressive sensing can be used to recover the support vector. Greedy algorithms will recover the support vector indices in an iterative manner. Generalized Orthogonal Matching Pursuit (GOMP) is the generalized form of the Orthogonal Matching Pursuit (OMP) algorithm where a number of indices selected per iteration will be greater than or equal to 1. To recover the support vector of unknown signal ‘x’ from the compressed measurements, the restricted isometric property should be satisfied as a sufficient condition. Finding the restricted isometric constant is a non-deterministic polynomial-time hardness problem due to that the coherence of the… More >

View

631

Download

448

Open Access

ARTICLE

Raed Alhamad^1,*, Hatem Boujemaa²
Computer Systems Science and Engineering, Vol.45, No.2, pp. 2059-2070, 2023, DOI:10.32604/csse.2023.032610
Abstract In this article, we use Intelligent Reflecting Surfaces (IRS) to improve the throughput of Non Orthogonal Multiple Access (NOMA) with Adaptive Transmit Power (ATP). The results are valid for Cognitive Radio Networks (CRN) where secondary source adapts its power to generate low interference at primary receiver. In all previous studies, IRS were implemented with fixed transmit power and previous results are not valid when the power of the secondary source is adaptive. In CRN, secondary nodes are allowed to transmit over the same band as primary users since they adapt their power to minimize the generated interference. Each NOMA user… More >

View

535

Download

382

Open Access

ARTICLE

Waleed Halboob^1,*, Jalal Almuhtadi^1,2
Computer Systems Science and Engineering, Vol.45, No.2, pp. 2071-2092, 2023, DOI:10.32604/csse.2023.024110
Abstract Privacy preservation (PP) in Digital forensics (DF) is a conflicted and non-trivial issue. Existing solutions use the searchable encryption concept and, as a result, are not efficient and support only a keyword search. Moreover, the collected forensic data cannot be analyzed using existing well-known digital tools. This research paper first investigates the lawful requirements for PP in DF based on the organization for economic co-operation and development OECB) privacy guidelines. To have an efficient investigation process and meet the increased volume of data, the presented framework is designed based on the selective imaging concept and advanced encryption standard (AES). The… More >

View

646

Download

371

Open Access

ARTICLE

Sureshkumar Rajagopal¹, Tamilvizhi Thanarajan^2,*, Youseef Alotaibi³, Saleh Alghamdi⁴
Computer Systems Science and Engineering, Vol.45, No.2, pp. 2093-2109, 2023, DOI:10.32604/csse.2023.032488
Abstract Automated segmentation of brain tumors using Magnetic Resonance Imaging (MRI) data is critical in the analysis and monitoring of disease development. As a result, gliomas are aggressive and diverse tumors that may be split into intra-tumoral groups by using effective and accurate segmentation methods. It is intended to extract characteristics from an image using the Gray Level Co-occurrence (GLC) matrix feature extraction method described in the proposed work. Using Convolutional Neural Networks (CNNs), which are commonly used in biomedical image segmentation, CNNs have significantly improved the precision of the state-of-the-art segmentation of a brain tumor. Using two segmentation networks, a… More >

View

888

Download

684

Open Access

ARTICLE

Chuqing Zhang¹, Jiangyuan Yao^2,*, Guangwu Hu³, Xingcan Cao⁴
Computer Systems Science and Engineering, Vol.45, No.2, pp. 2111-2124, 2023, DOI:10.32604/csse.2023.030516
Abstract Traditional linear statistical methods cannot provide effective prediction results due to the complexity of human mind. In this paper, we apply machine learning to the field of funding allocation decision making, and try to explore whether personal characteristics of evaluators help predict the outcome of the evaluation decision? and how to improve the accuracy rate of machine learning methods on the imbalanced dataset of grant funding? Since funding data is characterized by imbalanced data distribution, we propose a slacked weighted entropy decision tree (SWE-DT). We assign weight to each class with the help of slacked factor. The experimental results show… More >

View

646

Download

363

Open Access

ARTICLE

Usman Ahmad¹, Muhammad Junaid Ali², Faizan Ahmed Khan³, Arfat Ahmad Khan⁴, Arif Ur Rehman¹, Malik Muhammad Ali Shahid⁵, Mohd Anul Haq^6,*, Ilyas Khan⁷, Zamil S. Alzamil⁶, Ahmed Alhussen⁸
Computer Systems Science and Engineering, Vol.45, No.2, pp. 2125-2140, 2023, DOI:10.32604/csse.2023.031008
Abstract Building an automatic fish recognition and detection system for large-scale fish classes is helpful for marine researchers and marine scientists because there are large numbers of fish species. However, it is quite difficult to build such systems owing to the lack of data imbalance problems and large number of classes. To solve these issues, we propose a transfer learning-based technique in which we use Efficient-Net, which is pre-trained on ImageNet dataset and fine-tuned on QuT Fish Database, which is a large scale dataset. Furthermore, prior to the activation layer, we use Global Average Pooling (GAP) instead of dense layer with… More >

View

1216

Download

675

Like

3

Open Access

ARTICLE

Prohim Tam¹, Sa Math¹, Seokhoon Kim^1,2,*
Computer Systems Science and Engineering, Vol.45, No.2, pp. 2141-2154, 2023, DOI:10.32604/csse.2023.030984
Abstract Edge intelligence brings the deployment of applied deep learning (DL) models in edge computing systems to alleviate the core backbone network congestions. The setup of programmable software-defined networking (SDN) control and elastic virtual computing resources within network functions virtualization (NFV) are cooperative for enhancing the applicability of intelligent edge softwarization. To offer advancement for multi-dimensional model task offloading in edge networks with SDN/NFV-based control softwarization, this study proposes a DL mechanism to recommend the optimal edge node selection with primary features of congestion windows, link delays, and allocatable bandwidth capacities. Adaptive partial task offloading policy considered the DL-based recommendation to… More >

View

675

Download

405

Open Access

ARTICLE

LiangJun Deng¹, Hang Lei¹, Zheng Yang¹, WeiZhong Qian^1,*, XiaoYu Li¹, Hao Wu², Sihao Deng³, RuChao Sha¹, WeiDong Deng⁴
Computer Systems Science and Engineering, Vol.45, No.2, pp. 2155-2170, 2023, DOI:10.32604/csse.2023.027680
Abstract In order to realize a general-purpose automatic formal verification platform based on WebAssembly technology as a web service (FVPS), which aims to provide an automated report of vulnerability detections, this work builds a Hyperledger Fabric blockchain runtime model. It proposes an optimized methodology of the functional equivalent translation from source program languages to formal languages. This methodology utilizes an external application programming interface (API) table to replace the source codes in compilation, thereby pruning the part of housekeeping codes to ease code inflation. Code inflation is a significant metric in formal language translation. Namely, minor code inflation enhances verification scale… More >

View

782

Download

415

Like

1

Open Access

ARTICLE

Anis Ammous^*, Ammar Alsaedi, Ahmed N. M. Alahmadi, Fahad Alharbi, Kaiçar Ammous
Computer Systems Science and Engineering, Vol.45, No.2, pp. 2171-2186, 2023, DOI:10.32604/csse.2023.029389
Abstract The Low Voltage Direct Current (LVDC) architecture gives higher benefits over the classic low-voltage alternating current (LVAC) supply concept. LVDC has fewer energy conversion stages, is compatible with renewable energy sources, and is easier to integrate with accumulators. In this paper, an LVDC supply concept is proposed and compared with currently used conventional photovoltaic (PV) systems in terms of efficiency. The new LVDC photovoltaic system behavior is validated using LTspice modeling tool. The findings of this work prove that the concept of LVDC supply is highly attractive when the electricity produced by the photovoltaic is used onsite in the daytime.… More >

View

656

Download

405

Open Access

ARTICLE

M. Priyadharsini^1,*, K. Karuppasamy²
Computer Systems Science and Engineering, Vol.45, No.2, pp. 2187-2205, 2023, DOI:10.32604/csse.2023.031115
Abstract Big Data applications face different types of complexities in classifications. Cleaning and purifying data by eliminating irrelevant or redundant data for big data applications becomes a complex operation while attempting to maintain discriminative features in processed data. The existing scheme has many disadvantages including continuity in training, more samples and training time in feature selections and increased classification execution times. Recently ensemble methods have made a mark in classification tasks as combine multiple results into a single representation. When comparing to a single model, this technique offers for improved prediction. Ensemble based feature selections parallel multiple expert’s judgments on a… More >

View

1056

Download

468

Open Access

ARTICLE

Yonghui Duan¹, Keqing Zhao^1,*, Yibin Guo², Xiang Wang²
Computer Systems Science and Engineering, Vol.45, No.2, pp. 2207-2222, 2023, DOI:10.32604/csse.2023.032297
Abstract A number of risks exist in commercial housing, and it is critical for the government, the real estate industry, and consumers to establish an objective early warning indicator system for commercial housing risks and to conduct research regarding its measurement and early warning. In this paper, we examine the commodity housing market and construct a risk index for the commodity housing market at three levels: market level, the real estate industry and the national economy. Using the Bootstrap aggregating-grey wolf optimizer-support vector machine (Bagging-GWO-SVM) model after synthesizing the risk index by applying the CRITIC objective weighting method, the commercial housing… More >

View

772

Download

399

Like

1

Open Access

ARTICLE

Alla Abbas Khadir¹, Seyed Amin Hosseini Seno^1,2,*, Baydaa Fadhil Dhahir^2,3, Rahmat Budiarto⁴
Computer Systems Science and Engineering, Vol.45, No.2, pp. 2223-2234, 2023, DOI:10.32604/csse.2023.032316
Abstract Fog computing became a traditional OffLad Destination (OLD) to compute the offloaded tasks of the Internet of Vehicles (IoV). Nevertheless, the limited computing resources of the fog node leads to re-offload these tasks to the neighboring fog nodes or the cloud. Thus, the IoV will incur additional offloading costs. In this paper, we propose a new offloading scheme by utilizing RoadSide Parked Vehicles (RSPV) as an alternative OLD for IoV. The idle computing resources of the RSPVs can compute large tasks with low offloading costs compared with fog nodes and the cloud. Finally, a performance evaluation of the proposed scheme… More >

View

673

Download

470

Like

2

Open Access

ARTICLE

Mostafa Nassar¹, Anas M. Ali^1,2, Walid El-Shafai^1,3, Adel Saleeb¹, Fathi E. Abd El-Samie¹, Naglaa F. Soliman⁴, Hussah Nasser AlEisa^5,*, Hossam Eldin H. Ahmed¹
Computer Systems Science and Engineering, Vol.45, No.2, pp. 2235-2247, 2023, DOI:10.32604/csse.2023.032156
Abstract Traditional security systems are exposed to many various attacks, which represents a major challenge for the spread of the Internet in the future. Innovative techniques have been suggested for detecting attacks using machine learning and deep learning. The significant advantage of deep learning is that it is highly efficient, but it needs a large training time with a lot of data. Therefore, in this paper, we present a new feature reduction strategy based on Distributed Cumulative Histograms (DCH) to distinguish between dataset features to locate the most effective features. Cumulative histograms assess the dataset instance patterns of the applied features… More >

View

687

Download

432

Open Access

ARTICLE

R. S. Sandhya Devi^1,*, V. R. Vijay Kumar², P. Sivakumar³
Computer Systems Science and Engineering, Vol.45, No.2, pp. 2249-2263, 2023, DOI:10.32604/csse.2023.032231
Abstract Plant disease classification and prevention of spreading of the disease at earlier stages based on visual leaves symptoms and Pest recognition through deep learning-based image classification is in the forefront of research. To perform the investigation on Plant and pest classification, Transfer Learning (TL) approach is used on EfficientNet-V2. TL requires limited labelled data and shorter training time. However, the limitation of TL is the pre-trained model network’s topology is static and the knowledge acquired is detrimentally overwriting the old parameters. EfficientNet-V2 is a Convolutional Neural Network (CNN) model with significant high speed learning rates across variable sized datasets. The… More >

View

1410

Download

798

Like

1

Open Access

ARTICLE

P. M. Arunkumar¹, Mehedi Masud², Sultan Aljahdali², Mohamed Abouhawwash^3,4,*
Computer Systems Science and Engineering, Vol.45, No.2, pp. 2265-2280, 2023, DOI:10.32604/csse.2023.032571
Abstract Nowadays, the cloud environment faces numerous issues like synchronizing information before the switch over the data migration. The requirement for a centralized internet of things (IoT)-based system has been restricted to some extent. Due to low scalability on security considerations, the cloud seems uninteresting. Since healthcare networks demand computer operations on large amounts of data, the sensitivity of device latency evolved among health networks is a challenging issue. In comparison to cloud domains, the new paradigms of fog computing give fresh alternatives by bringing resources closer to users by providing low latency and energy-efficient data processing solutions. Previous fog computing… More >

View

965

Download

423