Fog computing brings computational services near the network edge to meet the latency constraints of cyber-physical System(CPS)*** devices enable limited computational capacity and energy availability that hamper end ...
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Fog computing brings computational services near the network edge to meet the latency constraints of cyber-physical System(CPS)*** devices enable limited computational capacity and energy availability that hamper end user *** designed a novel performance measurement index to gauge a device’s resource *** examination addresses the offloading mechanism issues,where the end user(EU)offloads a part of its workload to a nearby edge server(ES).Sometimes,the ES further offloads the workload to another ES or cloud server to achieve reliable performance because of limited resources(such as storage and computation).The manuscript aims to reduce the service offloading rate by selecting a potential device or server to accomplish a low average latency and service completion time to meet the deadline constraints of sub-divided *** this regard,an adaptive online status predictive model design is significant for prognosticating the asset requirement of arrived services to make float ***,the development of a reinforcement learning-based flexible x-scheduling(RFXS)approach resolves the service offloading issues,where x=service/resource for producing the low latency and high performance of the *** approach to the theoretical bound and computational complexity is derived by formulating the system efficiency.A quadratic restraint mechanism is employed to formulate the service optimization issue according to a set ofmeasurements,as well as the behavioural association rate and adulation *** system managed an average 0.89%of the service offloading rate,with 39 ms of delay over complex scenarios(using three servers with a 50%service arrival rate).The simulation outcomes confirm that the proposed scheme attained a low offloading uncertainty,and is suitable for simulating heterogeneous CPS frameworks.
Cloud computing has brought about a significant transformation in the field of Information Technology (IT) by providing the capability to access a shared pool of resources over the internet in a scalable and on-demand...
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Deep neural networks have shown promising results in the classification of skin lesion images, particularly when they focus on the most significant regions of an image. However, the identification of melanoma continue...
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The capacity to generalize to future unseen data stands as one of the utmost crucial attributes of deep neural networks. Sharpness-Aware Minimization (SAM) aims to enhance the generalizability by minimizing worst-case...
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In order to maintain sustainable agriculture, it is vital to monitor plant health. Since all species of plants are prone to characteristic diseases, it necessitates regular surveillance to search for any symptoms, whi...
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Home automation is growing rapidly in the Fourth Industrial Revolution (4IR), providing users with unwavering convenience and enhanced security. This paper presents a comprehensive Internet of Things (IoT) smart home ...
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Many recent FPGA-based Processor-in-Memory (PIM) architectures have appeared with promises of impressive levels of parallelism but with performance that falls short of expectations due to reduced maximum clock frequen...
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With the development of artificial intelligence,neural network provides unique opportunities for holography,such as high fidelity and dynamic *** to obtain real 3D scene and generate high fidelity hologram in real tim...
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With the development of artificial intelligence,neural network provides unique opportunities for holography,such as high fidelity and dynamic *** to obtain real 3D scene and generate high fidelity hologram in real time is an urgent ***,we propose a liquid lens based holographic camera for real 3D scene hologram acquisition using an end-to-end physical model-driven network(EEPMD-Net).As the core component of the liquid camera,the first 10 mm large aperture electrowetting-based liquid lens is proposed by using specially fabricated *** design of the liquid camera ensures that the multi-layers of the real 3D scene can be obtained quickly and with great imaging *** EEPMD-Net takes the information of real 3D scene as the input,and uses two new structures of encoder and decoder networks to realize low-noise phase *** comparing the intensity information between the reconstructed image after depth fusion and the target scene,the composite loss function is constructed for phase optimization,and the high-fidelity training of hologram with true depth of the 3D scene is realized for the first *** holographic camera achieves the high-fidelity and fast generation of the hologram of the real 3D scene,and the reconstructed experiment proves that the holographic image has the advantage of low *** proposed holographic camera is unique and can be used in 3D display,measurement,encryption and other fields.
Coherent multiple-input–multiple-output (MIMO) radar could significantly improve the weak moving target detection ability by accumulating multichannel and multiframe echo signal. However, due to the target motion and...
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In wind-turbine power generation systems, generators are typically located in the nacelles, and medium-voltage power converters are mostly placed at the bottom of the tower for maintenance convenience, resulting in lo...
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