Aerial Edge Computing on Orbit: A Task Offloading and Allocation Scheme

Zhang, Yuru; Chen, Chen; Liu, Lei; Lan, Dapeng; Jiang, Hongbo; Wan, Shaohua

doi:10.1109/tnse.2022.3207214

Cited by 71 publications

(18 citation statements)

References 32 publications

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“…Machine learning [ 1 ], big data [ 2 , 3 ], and the Internet of Things (IoT) [ 4 ] have infiltrated every aspect of people's lives. Generative adversarial networks (GANs) [ 5 ] have been viewed as the most interesting ideas of artificial intelligence in the last decade.…”

Section: Introductionmentioning

confidence: 99%

Generated Image Editing Method Based on Global-Local Jacobi Disentanglement for Machine Learning

Zhang

Wang

et al. 2023

Sensors

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Accurate semantic editing of the generated images is extremely important for machine learning and sample enhancement of big data. Aiming at the problem of semantic entanglement in generated image latent space of the StyleGAN2 network, we proposed a generated image editing method based on global-local Jacobi disentanglement. In terms of global disentanglement, we extract the weight matrix of the style layer in the pre-trained StyleGAN2 network; obtain the semantic attribute direction vector by using the weight matrix eigen decomposition method; finally, utilize this direction vector as the initialization vector for the Jacobi orthogonal regularization search algorithm. Our method improves the speed of the Jacobi orthogonal regularization search algorithm with the proportion of effective semantic attribute editing directions. In terms of local disentanglement, we design a local contrast regularized loss function to relax the semantic association local area and non-local area and utilize the Jacobi orthogonal regularization search algorithm to obtain a more accurate semantic attribute editing direction based on the local area prior MASK. The experimental results show that the proposed method achieves SOTA in semantic attribute disentangled metrics and can discover more accurate editing directions compared with the mainstream unsupervised generated image editing methods.

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Section: Introductionmentioning

confidence: 99%

Generated Image Editing Method Based on Global-Local Jacobi Disentanglement for Machine Learning

Zhang

Wang

et al. 2023

Sensors

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“…Some of the current research has been carried out ignoring the multibeam characteristic in satellite constellations. 1 Indeed, the rapid movement of giant constellations of multibeam satellites will pose the problem of frequent switching of links to Earth. Researchers are exploring forward techniques to accommodate these high-speed movement characteristics and to improve satellite resource utilisation while guaranteeing quality of service (QoS) to users.…”

Section: Introductionmentioning

confidence: 99%

Artificial intelligence in multibeam satellite communication systems: architecture and prospects

Li,

Chen,

Huang

et al. 2023

Eighth Asia Pacific Conference on Optics Manufacture and Third International Forum of Young Scientists on Advanced Optical Manu

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“…The widespread IoT devices motivate the convergence of satellite networks and terrestrial networks. Furthermore, since embedding MEC servers in satellites can provide a computing service for IoT devices, even in remote and depopulated areas, SEC has received extensive attention [10][11][12][13][14].…”

Section: Introductionmentioning

confidence: 99%

“…Aerospace 2023, 10, x FOR PEER REVIEW 2 of 27 Furthermore, since embedding MEC servers in satellites can provide a computing service for IoT devices, even in remote and depopulated areas, SEC has received extensive attention [10][11][12][13][14].…”

Section: Introductionmentioning

confidence: 99%

“…Yu et al [13] proposed a deep-imitation-learning-driven offloading and caching algorithm to achieve real-time decision making. Zhang et al [14] presented a greedy-strategy-based task allocation algorithm for LEO satellite networks. Some scholars considered satellite-terrestrial links: Tang et al [7] proposed a LEO satellite network that combined hybrid cloud and edge computing, taking into account satellite coverage time and computation capabilities.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Task Offloading with Data-Dependent Constraints in Satellite Edge Computing Networks: A Multi-Objective Approach

Zhang,

Feng,

Yang

et al. 2023

Aerospace

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Senabling a satellite network with edge computing capabilities, SEC provides users with a full range of computing service. In this paper, we construct a multi-objective optimization model for task offloading with data-dependent constraints in an SEC network and aim to achieve optimal tradeoffs among energy consumption, cost, and makespan. However, dependency constraints between tasks may lead to unexpected computational delays and even task failures in an SEC network. To solve this, we proposed a Petri-net-based constraint amending method with polynomial complexity and generated offloading results satisfying our constraints. For the multiple optimization objectives, a strengthened dominance relation sort was established to balance the convergence and diversity of nondominated solutions. Based on these, we designed a multi-objective wolf pack search (MOWPS) algorithm. A series of adaptive mechanisms was employed for avoiding additional computational overhead, and a Lamarckian-learning-based multi-neighborhood search prevents MOWPS from becoming trapped in the local optimum. Extensive computational experiments demonstrate the outperformance of MOWPS for solving task offloading with data-dependent constraints in an SEC network.

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Aerial Edge Computing on Orbit: A Task Offloading and Allocation Scheme

Cited by 71 publications

References 32 publications

Generated Image Editing Method Based on Global-Local Jacobi Disentanglement for Machine Learning

Generated Image Editing Method Based on Global-Local Jacobi Disentanglement for Machine Learning

Artificial intelligence in multibeam satellite communication systems: architecture and prospects

Task Offloading with Data-Dependent Constraints in Satellite Edge Computing Networks: A Multi-Objective Approach

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