R. Shanthakumari¹, Yun-Cheol Nam², Yunyoung Nam^3,*, Mohamed Abouhawwash^4,5

Intelligent Automation & Soft Computing, Vol.36, No.2, pp. 1991-2005, 2023, DOI:10.32604/iasc.2023.033696 - 05 January 2023

Abstract Smart cities make use of a variety of smart technology to improve societies in better ways. Such intelligent technologies, on the other hand, pose significant concerns in terms of power usage and emission of carbons. The suggested study is focused on technological networks for big data-driven systems. With the support of software-defined technologies, a transportation-aided multicast routing system is suggested. By using public transportation as another communication platform in a smart city, network communication is enhanced. The primary objective is to use as little energy as possible while delivering as much data as possible. The… More >

P. Nalayini^1,*, R. Arun Prakash²

Computer Systems Science and Engineering, Vol.44, No.3, pp. 2033-2047, 2023, DOI:10.32604/csse.2023.028269 - 01 August 2022

Abstract Fog computing is a promising technology that has been emerged to handle the growth of smart devices as well as the popularity of latency-sensitive and location-awareness Internet of Things (IoT) services. After the emergence of IoT-based services, the industry of internet-based devices has grown. The number of these devices has raised from millions to billions, and it is expected to increase further in the near future. Thus, additional challenges will be added to the traditional centralized cloud-based architecture as it will not be able to handle that growth and to support all connected devices in… More >

B. Gomathi¹, S. T. Suganthi^2,*, T. N. Prabhu³, Andriy Kovalenko⁴

Intelligent Automation & Soft Computing, Vol.34, No.3, pp. 1851-1860, 2022, DOI:10.32604/iasc.2022.026779 - 25 May 2022

Abstract On the Internet of Vehicle (IoV) devices, offloading data is the major problem because massive amounts of data generate energy consumption, and the execution cost is high. At present, accidents traffic management is highly prominent due to increased vehicles among the population. IoV is the only technology to help the transport system effectively. This data outreach the memory also has high energy consumption, and the storage cost is high. To overcome these issues, a Mobility aware Offloading scheme with Multi-Objective Immune Optimization algorithm (MOS-MOIO) is used in the cloud storage. The data is generated from More >

A. Backia Abinaya^1,*, G. Karthikeyan²

Intelligent Automation & Soft Computing, Vol.34, No.1, pp. 325-338, 2022, DOI:10.32604/iasc.2022.020896 - 15 April 2022

Abstract The Internet of Vehicles (IoV) is utilized for collecting enormous real time information driven traffics and alert drivers depending on situations. In recent times, all smart vehicles are developed with IoT devices. These devices communicate with a radio access unit (RAU) at road side. Moreover, a 5G system is equipped with a base station and connection interfaces that use optic fiber for their effective communication. For a fast mode of communication, the IoV must offload its data to the nearest edge nodes. The main problem with the IoV is that it generates enormous data which… More >

Fadwa Alrowais¹, Ahmed S. Almasoud², Radwa Marzouk³, Fahd N. Al-Wesabi^4,5, Anwer Mustafa Hilal^6,*, Mohammed Rizwanullah⁶, Abdelwahed Motwakel⁶, Ishfaq Yaseen⁶

CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 2783-2795, 2022, DOI:10.32604/cmc.2022.025204 - 29 March 2022

Abstract Mobile edge computing (MEC) provides effective cloud services and functionality at the edge device, to improve the quality of service (QoS) of end users by offloading the high computation tasks. Currently, the introduction of deep learning (DL) and hardware technologies paves a method in detecting the current traffic status, data offloading, and cyberattacks in MEC. This study introduces an artificial intelligence with metaheuristic based data offloading technique for Secure MEC (AIMDO-SMEC) systems. The proposed AIMDO-SMEC technique incorporates an effective traffic prediction module using Siamese Neural Networks (SNN) to determine the traffic status in the MEC More >

V. R. Balaji^1,*, T. Kalavathi², J. Vellingiri³, N. Rajkumar⁴, Venkat Prasad Padhy⁵

Computer Systems Science and Engineering, Vol.42, No.1, pp. 289-301, 2022, DOI:10.32604/csse.2022.020971 - 02 December 2021

Abstract Data offloading at the network with less time and reduced energy consumption are highly important for every technology. Smart applications process the data very quickly with less power consumption. As technology grows towards 5G communication architecture, identifying a solution for QoS in 5G through energy-efficient computing is important. In this proposed model, we perform data offloading at 5G using the fuzzification concept. Mobile IoT devices create tasks in the network and are offloaded in the cloud or mobile edge nodes based on energy consumption. Two base stations, small (SB) and macro (MB) stations, are initialized More >

Ying Li¹, Jianbo Li^1,*, Jianwei Chen¹, Minchao Lu¹, Caoyuan Li^2,3

CMC-Computers, Materials & Continua, Vol.57, No.3, pp. 571-587, 2018, DOI:10.32604/cmc.2018.02851

Abstract The explosive growth of mobile data demand is becoming an increasing burden on current cellular network. To address this issue, we propose a solution of opportunistic data offloading for alleviating overloaded cellular traffic. The principle behind it is to select a few important users as seeds for data sharing. The three critical steps are detailed as follows. We first explore individual interests of users by the construction of user profiles, on which an interest graph is built by Gaussian graphical modeling. We then apply the extreme value theory to threshold the encounter duration of user More >