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  • Open Access

    ARTICLE

    Task Offloading and Resource Allocation in IoT Based Mobile Edge Computing Using Deep Learning

    Ilyоs Abdullaev1, Natalia Prodanova2, K. Aruna Bhaskar3, E. Laxmi Lydia4, Seifedine Kadry5,6,7, Jungeun Kim8,*

    CMC-Computers, Materials & Continua, Vol.76, No.2, pp. 1463-1477, 2023, DOI:10.32604/cmc.2023.038417 - 30 August 2023

    Abstract Recently, computation offloading has become an effective method for overcoming the constraint of a mobile device (MD) using computation-intensive mobile and offloading delay-sensitive application tasks to the remote cloud-based data center. Smart city benefitted from offloading to edge point. Consider a mobile edge computing (MEC) network in multiple regions. They comprise N MDs and many access points, in which every MD has M independent real-time tasks. This study designs a new Task Offloading and Resource Allocation in IoT-based MEC using Deep Learning with Seagull Optimization (TORA-DLSGO) algorithm. The proposed TORA-DLSGO technique addresses the resource management issue More >

  • Open Access

    ARTICLE

    Improvised Seagull Optimization Algorithm for Scheduling Tasks in Heterogeneous Cloud Environment

    Pradeep Krishnadoss*, Vijayakumar Kedalu Poornachary, Parkavi Krishnamoorthy, Leninisha Shanmugam

    CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 2461-2478, 2023, DOI:10.32604/cmc.2023.031614 - 31 October 2022

    Abstract Well organized datacentres with interconnected servers constitute the cloud computing infrastructure. User requests are submitted through an interface to these servers that provide service to them in an on-demand basis. The scientific applications that get executed at cloud by making use of the heterogeneous resources being allocated to them in a dynamic manner are grouped under NP hard problem category. Task scheduling in cloud poses numerous challenges impacting the cloud performance. If not handled properly, user satisfaction becomes questionable. More recently researchers had come up with meta-heuristic type of solutions for enriching the task scheduling… More >

  • Open Access

    ARTICLE

    Sailfish Optimization with Deep Learning Based Oral Cancer Classification Model

    Mesfer Al Duhayyim1,*, Areej A. Malibari2, Sami Dhahbi3, Mohamed K. Nour4, Isra Al-Turaiki5, Marwa Obayya6, Abdullah Mohamed7

    Computer Systems Science and Engineering, Vol.45, No.1, pp. 753-767, 2023, DOI:10.32604/csse.2023.030556 - 16 August 2022

    Abstract Recently, computer aided diagnosis (CAD) model becomes an effective tool for decision making in healthcare sector. The advances in computer vision and artificial intelligence (AI) techniques have resulted in the effective design of CAD models, which enables to detection of the existence of diseases using various imaging modalities. Oral cancer (OC) has commonly occurred in head and neck globally. Earlier identification of OC enables to improve survival rate and reduce mortality rate. Therefore, the design of CAD model for OC detection and classification becomes essential. Therefore, this study introduces a novel Computer Aided Diagnosis for… More >

  • Open Access

    ARTICLE

    Energy Efficient Clustering and Optimized LOADng Protocol for IoT

    Divya Sharma1,*, Sanjay Jain2, Vivek Maik3

    Intelligent Automation & Soft Computing, Vol.34, No.1, pp. 357-370, 2022, DOI:10.32604/iasc.2022.025637 - 15 April 2022

    Abstract In recent years, the use of Internet of Things (IoT) devices has increased exponentially due to the advancement of information and communication technologies. Wireless sensor networks (WSNs) are vital in the development of IoT and include low-cost smart devices for data collection. However, such smart devices hold some restrictions in terms of calculation, processing, storage, and energy resources. With such constraints, one of the primary difficulties for the WSN is to achieve the lowest possible energy consumption across the network. This article aims to develop an Energy-Efficient cluster-based Lightweight On-Demand Ad hoc Distance Vector Routing… More >

  • Open Access

    ARTICLE

    Energy Aware Seagull Optimization-Based Unequal Clustering Technique in WSN Communication

    D. Anuradha1,*, R. Srinivasan2, T. Ch. Anil Kumar3, J. Faritha Banu4, Aditya Kumar Singh Pundir5, D. Vijendra Babu6

    Intelligent Automation & Soft Computing, Vol.32, No.3, pp. 1325-1341, 2022, DOI:10.32604/iasc.2022.021946 - 09 December 2021

    Abstract Wireless sensor network (WSN) becomes a hot research area owing to an extensive set of applications. In order to accomplish energy efficiency in WSN, most of the earlier works have focused on the clustering process which enables to elect CHs and organize unequal clusters. However, the clustering process results in hot spot problem and can be addressed by the use of unequal clustering techniques, which enables to construct of clusters of unequal sizes to equalize the energy dissipation in the WSN. Unequal clustering can be formulated as an NP-hard issue and can be solved by… More >

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