Introduction.- Part I. DISTRIBUTED CLOUD AND EDGE COMPUTING SYSTEMS.- Preliminaries.- Part II. SINGLE-TASK AND MULTI-TASK PREDICTION.- Multiapplication Workload Prediction with Wavelet Decomposition.- Network Traffic Prediction with Temporal Convolutional Networks and LSTM.- Multivariate Resource Usage Prediction with Frequency-Enhanced and Attention-Assisted Transformer.- LSTM-Based Prediction for Large-Scale Resources and Workloads.- Workload and Resource Prediction with Multi-Head Attention and LSTM.- Spatio-temporal Prediction with Bi-directional and Grid LSTM for Workloads and Resources in Clouds.- Part III. TASK SCHEDULING STRATEGIES.- Energy-Efficient Offloading for Static and Dynamic Applications.- Cost-Minimized Offloading and User Association.- Energy-Optimized Partial Computation Offloading.- Cost-Minimized Microservice Migration with Autoencoder-Assisted Evolution.- Cost-Efficient Offloading with Layered Unmanned Aerial Vehicles.- Energy-Minimized Partial Offloading in Satellite-Terrestrial Edge Networks.- Part IV. CLOUD AND EDGE SYSTEMS FOR LARGE AI MODELS.- Multimodal Large Models and Their Applications.- Large Prediction Models and Their Applications.- Inference Offloading and Resource Allocation with Large Models.- Part V. INNOVATIVE PRACTICES IN CLOUD-EDGE SYSTEMS.- Applications of Cloud-Edge Systems in CDNs.- Applications of Cloud-Edge Systems in Industrial Internet.- Applications of Cloud-Edge Systems in Energy Internet.- Applications of Cloud-Edge Systems in Smart Buildings.- Applications of Cloud-Edge Systems in Smart Transportation.- Part VI. INNOVATIVE PRACTICES IN CLOUD-EDGE SYSTEMS: INDUSTRIAL APPLICATIONS.- Applications of Cloud-Edge Systems in Security Monitoring.- Applications of Cloud-Edge Systems in Agricultural Production.- Applications of Cloud-Edge Systems in Ecological Environment.- Applications of Cloud-Edge Systems in Healthcare.- Applications of Cloud-Edge Systems in Smart Education.- Part VII. CONCLUSIONS AND OPEN PROBLEMS.- Conclusion.
Scheduling Tasks in Distributed Cloud and Edge Computing Systems with Evolutionary Optimizers
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