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  • Open Access

    ARTICLE

    Bio-Inspired Intelligent Routing in WSN: Integrating Mayfly Optimization and Enhanced Ant Colony Optimization for Energy-Efficient Cluster Formation and Maintenance

    V. G. Saranya*, S. Karthik

    CMES-Computer Modeling in Engineering & Sciences, Vol.141, No.1, pp. 127-150, 2024, DOI:10.32604/cmes.2024.053825

    Abstract Wireless Sensor Networks (WSNs) are a collection of sensor nodes distributed in space and connected through wireless communication. The sensor nodes gather and store data about the real world around them. However, the nodes that are dependent on batteries will ultimately suffer an energy loss with time, which affects the lifetime of the network. This research proposes to achieve its primary goal by reducing energy consumption and increasing the network’s lifetime and stability. The present technique employs the hybrid Mayfly Optimization Algorithm-Enhanced Ant Colony Optimization (MFOA-EACO), where the Mayfly Optimization Algorithm (MFOA) is used to… More >

  • Open Access

    ARTICLE

    EECLP: A Wireless Sensor Networks Energy Efficient Cross-Layer Protocol

    Mohammed Kaddi1,*, Mohammed Omari2, Moamen Alnatoor1

    CMC-Computers, Materials & Continua, Vol.80, No.2, pp. 2611-2631, 2024, DOI:10.32604/cmc.2024.052048

    Abstract Recent advancements in wireless communications have allowed the birth of novel wireless sensor networks (WSN). A sensor network comprises several micro-sensors deployed randomly in an area of interest. A micro-sensor is provided with an energy resource to supply electricity to all of its components. However, the disposed energy resource is limited and battery replacement is generally infeasible. With this restriction, the sensors must conserve energy to prolong their lifetime. Various energy conservation strategies for WSNs have been presented in the literature, from the application to the physical layer. Most of these solutions focus only on… More >

  • Open Access

    ARTICLE

    A Novel Optimization Approach for Energy-Efficient Multiple Workflow Scheduling in Cloud Environment

    Ambika Aggarwal1, Sunil Kumar2,3, Ashok Bhansali4, Deema Mohammed Alsekait5,*, Diaa Salama AbdElminaam6,7,8

    Computer Systems Science and Engineering, Vol.48, No.4, pp. 953-967, 2024, DOI:10.32604/csse.2024.050406

    Abstract Existing multiple workflow scheduling techniques focus on traditional Quality of Service (QoS) parameters such as cost, deadline, and makespan to find optimal solutions by consuming a large amount of electrical energy. Higher energy consumption decreases system efficiency, increases operational cost, and generates more carbon footprint. These major problems can lead to several problems, such as economic strain, environmental degradation, resource depletion, energy dependence, health impacts, etc. In a cloud computing environment, scheduling multiple workflows is critical in developing a strategy for energy optimization, which is an NP-hard problem. This paper proposes a novel, bi-phase Energy-Efficient… More >

  • Open Access

    ARTICLE

    A Layered Energy-Efficient Multi-Node Scheduling Mechanism for Large-Scale WSN

    Xue Zhao, Shaojun Tao, Hongying Tang, Jiang Wang*, Baoqing Li*

    CMC-Computers, Materials & Continua, Vol.79, No.1, pp. 1335-1351, 2024, DOI:10.32604/cmc.2024.047996

    Abstract In recent years, target tracking has been considered one of the most important applications of wireless sensor network (WSN). Optimizing target tracking performance and prolonging network lifetime are two equally critical objectives in this scenario. The existing mechanisms still have weaknesses in balancing the two demands. The proposed heuristic multi-node collaborative scheduling mechanism (HMNCS) comprises cluster head (CH) election, pre-selection, and task set selection mechanisms, where the latter two kinds of selections form a two-layer selection mechanism. The CH election innovatively introduces the movement trend of the target and establishes a scoring mechanism to determine More >

  • Open Access

    ARTICLE

    An OP-TEE Energy-Efficient Task Scheduling Approach Based on Mobile Application Characteristics

    Hai Wang*, Xuan Hao, Shuo Ji*, Jie Zheng, Yuhui Ma, Jianfeng Yang

    Intelligent Automation & Soft Computing, Vol.37, No.2, pp. 1621-1635, 2023, DOI:10.32604/iasc.2023.037898

    Abstract Trusted Execution Environment (TEE) is an important part of the security architecture of modern mobile devices, but its secure interaction process brings extra computing burden to mobile devices. This paper takes open portable trusted execution environment (OP-TEE) as the research object and deploys it to Raspberry Pi 3B, designs and implements a benchmark for OP-TEE, and analyzes its program characteristics. Furthermore, the application execution time, energy consumption and energy-delay product (EDP) are taken as the optimization objectives, and the central processing unit (CPU) frequency scheduling strategy of mobile devices is dynamically adjusted according to the More >

  • Open Access

    ARTICLE

    Virtual Machine Consolidation with Multi-Step Prediction and Affinity-Aware Technique for Energy-Efficient Cloud Data Centers

    Pingping Li*, Jiuxin Cao

    CMC-Computers, Materials & Continua, Vol.76, No.1, pp. 81-105, 2023, DOI:10.32604/cmc.2023.039076

    Abstract Virtual machine (VM) consolidation is an effective way to improve resource utilization and reduce energy consumption in cloud data centers. Most existing studies have considered VM consolidation as a bin-packing problem, but the current schemes commonly ignore the long-term relationship between VMs and hosts. In addition, there is a lack of long-term consideration for resource optimization in the VM consolidation, which results in unnecessary VM migration and increased energy consumption. To address these limitations, a VM consolidation method based on multi-step prediction and affinity-aware technique for energy-efficient cloud data centers (MPaAFVMC) is proposed. The proposed… More >

  • Open Access

    ARTICLE

    Energy-Efficient Approaches for a Machine Tool Building in a University through Field Measurement and Energy Modelling

    Kusnandar1, Win-Jet Luo1,2, Indra Permana1, Fu-Jen Wang2,*, Gantulga Bayarkhuu2

    Energy Engineering, Vol.120, No.6, pp. 1387-1399, 2023, DOI:10.32604/ee.2023.027459

    Abstract The heating, ventilating, and air conditioning (HVAC) system consumes nearly 50% of the building’s energy, especially in Taiwan with a hot and humid climate. Due to the challenges in obtaining energy sources and the negative impacts of excessive energy use on the environment, it is essential to employ an energy-efficient HVAC system. This study conducted the machine tools building in a university. The field measurement was carried out, and the data were used to conduct energy modelling with EnergyPlus (EP) in order to discover some improvements in energy-efficient design. The validation between field measurement and… More >

  • Open Access

    ARTICLE

    Power Optimized Multiple-UAV Error-Free Network in Cognitive Environment

    Shakti Raj Chopra1, Parulpreet Singh1, Ahmed Alhussen2,*, Nitin Mittal3, MohdAnul Haq4

    CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 3189-3201, 2023, DOI:10.32604/cmc.2023.030061

    Abstract Many extensive UAV communication networks have used UAV cooperative control. Wireless networking services can be offered using unmanned aerial vehicles (UAVs) as aerial base stations. Not only is coverage maximization, but also better connectivity, a fundamental design challenge that must be solved. The number of applications for unmanned aerial vehicles (UAVs) operating in unlicensed bands is fast expanding as the Internet of Things (IoT) develops. Those bands, however, have become overcrowded as the number of systems that use them grows. Cognitive Radio (CR) and spectrum allocation approaches have emerged as a potential approach for resolving… More >

  • Open Access

    ARTICLE

    An Energy-Efficient Protocol for Internet of Things Based Wireless Sensor Networks

    Mohammed Mubarak Mustafa1, Ahmed Abelmonem Khalifa2,3, Korhan Cengiz4,5, Nikola Ivković6,*

    CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 2397-2412, 2023, DOI:10.32604/cmc.2023.036275

    Abstract The performance of Wireless Sensor Networks (WSNs) is an important fragment of the Internet of Things (IoT), where the current WSNbuilt IoT network’s sensor hubs are enticing due to their critical resources. By grouping hubs, a clustering convention offers a useful solution for ensuring energy-saving of hubs and Hybrid Media Access Control (HMAC) during the course of the organization. Nevertheless, current grouping standards suffer from issues with the grouping structure that impacts the exhibition of these conventions negatively. In this investigation, we recommend an Improved Energy-Proficient Algorithm (IEPA) for HMAC throughout the lifetime of the… More >

  • Open Access

    ARTICLE

    Energy-Efficient Clustering Using Optimization with Locust Game Theory

    P. Kavitha Rani1, Hee-Kwon Chae2, Yunyoung Nam2,*, Mohamed Abouhawwash3,4

    Intelligent Automation & Soft Computing, Vol.36, No.3, pp. 2591-2605, 2023, DOI:10.32604/iasc.2023.033697

    Abstract Wireless sensor networks (WSNs) are made up of several sensors located in a specific area and powered by a finite amount of energy to gather environmental data. WSNs use sensor nodes (SNs) to collect and transmit data. However, the power supplied by the sensor network is restricted. Thus, SNs must store energy as often as to extend the lifespan of the network. In the proposed study, effective clustering and longer network lifetimes are achieved using multi-swarm optimization (MSO) and game theory based on locust search (LS-II). In this research, MSO is used to improve the… More >

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