M. Iyapparaja¹, Naif Khalaf Alshammari^2,*, M. Sathish Kumar¹, S. Siva Rama Krishnan¹, Chiranji Lal Chowdhary¹

CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 2225-2239, 2022, DOI:10.32604/cmc.2022.015707 - 27 September 2021

Abstract Infrastructure of fog is a complex system due to the large number of heterogeneous resources that need to be shared. The embedded devices deployed with the Internet of Things (IoT) technology have increased since the past few years, and these devices generate huge amount of data. The devices in IoT can be remotely connected and might be placed in different locations which add to the network delay. Real time applications require high bandwidth with reduced latency to ensure Quality of Service (QoS). To achieve this, fog computing plays a vital role in processing the request More >

Hind A. Alshambri^1,* Fawaz Alassery²

Journal of Cyber Security, Vol.3, No.3, pp. 149-166, 2021, DOI:10.32604/jcs.2021.022112 - 17 November 2021

Abstract Currently, the majority of institutions have made use of information technologies to improve and develop their diverse educational methods to attract more learners. Through information technologies, e-learning and learning-on-the go have been adopted by the institutions to provide affordability and flexibility of educational services. Most of the educational institutes are offering online teaching classes using the technologies like cloud computing, networking, etc. Educational institutes have developed their e-learning platforms for the online learning process, through this way they have paved the way for distance learning. But e-learning platform has to face a lot of… More >

M. Iyapparaja¹, M. Sathish Kumar¹, S. Siva Rama Krishnan¹, Chiranji Lal Chowdhary¹, Byungun Yoon², Saurabh Singh², Gi Hwan Cho^3,*

CMC-Computers, Materials & Continua, Vol.69, No.3, pp. 3163-3178, 2021, DOI:10.32604/cmc.2021.017302 - 24 August 2021

Abstract Industry 4.0 refers to the fourth evolution of technology development, which strives to connect people to various industries in terms of achieving their expected outcomes efficiently. However, resource management in an Industry 4.0 network is very complex and challenging. To manage and provide suitable resources to each service, we propose a FogQSYM (Fog–-Queuing system) model; it is an analytical model for Fog Applications that helps divide the application into several layers, then enables the sharing of the resources in an effective way according to the availability of memory, bandwidth, and network services. It follows the… More >

Jaber Almutairi¹, Mohammad Aldossary^2,*

Intelligent Automation & Soft Computing, Vol.30, No.1, pp. 129-145, 2021, DOI:10.32604/iasc.2021.018480 - 26 July 2021

Abstract With the increasing number of Internet of Things (IoT) devices connected to the internet, a platform is required to support the enormous amount of data they generate. Since cloud computing is far away from the connected IoT devices, applications that require low-latency, real-time interaction and high quality of service (QoS) may suffer network delay in using the Cloud. Consequently, the concept of edge computing has appeared to complement cloud services, working as an intermediate layer with computation capabilities between the Cloud and IoT devices, to overcome these limitations. Although edge computing is a promising enabler… More >

K. Kalaivani^*, M. Chinnadurai

Intelligent Automation & Soft Computing, Vol.30, No.1, pp. 1-15, 2021, DOI:10.32604/iasc.2021.017515 - 26 July 2021

Abstract Fog computing extends the concept of cloud computing by providing the services of computing, storage, and networking connectivity at the edge between data centers in cloud computing environments and end devices. Having the intelligence at the edge enables faster real-time decision-making and reduces the amount of data forwarded to the cloud. When enhanced by fog computing, the Internet of Things (IoT) brings low latency and improves real time and quality of service (QoS) in IoT applications of augmented reality, smart grids, smart vehicles, and healthcare. However, both cloud and fog computing environments are vulnerable to… More >

Farouq Aliyu^1,*, Tarek Sheltami¹, Ashraf Mahmoud¹, Louai Al-Awami¹, Ansar Yasar²

CMC-Computers, Materials & Continua, Vol.69, No.1, pp. 1159-1181, 2021, DOI:10.32604/cmc.2021.016938 - 04 June 2021

Abstract Fog computing (FC) is a networking paradigm where wireless devices known as fog nodes are placed at the edge of the network (close to the Internet of Things (IoT) devices). Fog nodes provide services in lieu of the cloud. Thus, improving the performance of the network and making it attractive to social media-based systems. Security issues are one of the most challenges encountered in FC. In this paper, we propose an anomaly-based Intrusion Detection and Prevention System (IDPS) against Man-in-the-Middle (MITM) attack in the fog layer. The system uses special nodes known as Intrusion Detection… More >

Jialin Wan¹, Muhammad Waqas^1,2, Shanshan Tu^1,*, Syed Mudassir Hussain³, Ahsan Shah², Sadaqat Ur Rehman⁴, Muhammad Hanif²

CMC-Computers, Materials & Continua, Vol.68, No.1, pp. 267-281, 2021, DOI:10.32604/cmc.2021.016260 - 22 March 2021

Abstract Fog computing paradigm extends computing, communication, storage, and network resources to the network’s edge. As the fog layer is located between cloud and end-users, it can provide more convenience and timely services to end-users. However, in fog computing (FC), attackers can behave as real fog nodes or end-users to provide malicious services in the network. The attacker acts as an impersonator to impersonate other legitimate users. Therefore, in this work, we present a detection technique to secure the FC environment. First, we model a physical layer key generation based on wireless channel characteristics. To generate More >

Abdullah Alamri^1,*, Sultan Alamri²

Intelligent Automation & Soft Computing, Vol.27, No.2, pp. 441-452, 2021, DOI:10.32604/iasc.2021.015198 - 18 January 2021

Abstract The COVID-19 pandemic has presented an unprecedented challenge to the entire world. It is a humanitarian crisis on a global scale. The virus continues to spread throughout nations, putting health systems under enormous pressure in the battle to save lives. With this growing crisis, companies and researchers worldwide are searching for ways to overcome the challenges associated with this virus. Also, the transport sector will play a critical role in revitalizing economies while simultaneously containing the spread of COVID-19. As the virus is still circulating, the only solution is to redesign public transportation to make More >

Lewis Nkenyereye^1,*, S. M. Riazul Islam², Mahmud Hossain³, M. Abdullah-Al-Wadud⁴, Atif Alamri⁴

CMC-Computers, Materials & Continua, Vol.66, No.2, pp. 1937-1948, 2021, DOI:10.32604/cmc.2020.013025 - 26 November 2020

Abstract The rapid development of personal health records (PHR) systems enables an individual to collect, create, store and share his PHR to authorized entities. Health care systems within the smart city environment require a patient to share his PRH data with a multitude of institutions’ repositories located in the cloud. The cloud computing paradigm cannot meet such a massive transformative healthcare systems due to drawbacks including network latency, scalability and bandwidth. Fog computing relieves the load of conventional cloud computing by availing intermediate fog nodes between the end users and the remote servers. Assuming a massive More >

Le Sun^1,*, Qiandi Yu¹, Dandan Peng¹, Sudha Subramani², Xuyang Wang¹

CMC-Computers, Materials & Continua, Vol.66, No.1, pp. 603-619, 2021, DOI:10.32604/cmc.2020.012515 - 30 October 2020

Abstract Recently, an increasing number of works start investigating the combination of fog computing and electronic health (ehealth) applications. However, there are still numerous unresolved issues worth to be explored. For instance, there is a lack of investigation on the disease prediction in fog environment and only limited studies show, how the Quality of Service (QoS) levels of fog services and the data stream mining techniques influence each other to improve the disease prediction performance (e.g., accuracy and time efficiency). To address these issues, we propose a fog-based framework for disease prediction based on Medical sensor More >