NSTL国家科技图书文献中心

1. Privacy Preserving Adjacency Query Supporting Homoionym Search over Medical Graph Data in Cloud Computing NSTL国家科技图书文献中心

Hourong Li | Yun Tian ... - 《Cloud Computing - CLOUD 2024》 - International Conference on Cloud Computing | Services Conference Federation - 2025, - 46～55 - 共10页

摘要：Cloud computing is widely used in all walks of | query supporting homoionym search in cloud computing | being outsourced to cloud* servers to reduce overhead* | . The untrustworthiness of cloud* servers puts the* | encrypted and stored on the cloud* server, the operation of*

关键词： Graph data | Adjacency query | Searchable encryption | Cloud computing

2. Mechanism of Data Sharing Using Secured Keyword Search in Cloud Computing NSTL国家科技图书文献中心

Umamaheswararao Mogi... | Aezeden Mohamed ... - 《Recent Advancements in Product Design and Manufacturing Systems》 - International Conference on Innovative Product Design and Intelligent Manufacturing System - 2025, - 483～494 - 共12页

摘要：Cloud computing has revolutionized the ability | information from the cloud, but traditional keyword search | techniques are vulnerable to attacks from cloud* service* | to store and analyze vast quantities of data in a | manner that is both economical and adaptable. Keyword

关键词： Cloud computing | Encryption | Decryption | Cipher text

3. Design of Automated Container Layout and Resource Optimization Algorithm based on Cloud Computing Technology NSTL国家科技图书文献中心

Feng Zhang - 《International Conference on Mechatronics and Intelligent Control (ICMIC 2024),Part One of Two Parts》 - International Conference on Mechatronics and Intelligent Control - 2025, - 1344708.1～1344708.6 - 共6页

摘要： application of cloud* computing, container technology has* | algorithm design based on cloud* computing technology to* | With the rapid development and widespread | become a hot topic for enterprises and research | institutions in recent years. This article proposes an

关键词： Cloud computing technology | Container arrangement | Resource optimization algorithm | Experiment and verification

4. A Vehicular Network Routing Based on the DQN Algorithm in the Cloud Environment NSTL国家科技图书文献中心

Mingzhu Ge | Liya Xu ... - 《Cloud Computing - CLOUD 2024》 - International Conference on Cloud Computing | Services Conference Federation - 2025, - 37～45 - 共9页

摘要： cloud-edge collaboration solution possesses powerful | computing and storage capabilities along with relatively | within the IoVs assisted by cloud-edge collaboration to | allocation of computing, caching, and communication | strategy performs better than the existing cloud-edge

关键词： IoVs | Routing | Cloud computing

5. ADAPT: Attention-Driven Domain Adaptation for Inter-cluster Workload Forecasting in Cloud Data Centers NSTL国家科技图书文献中心

Nosin Ibna Mahbub | Afsana Kabir Sinthia ... - 《Cloud Computing - CLOUD 2024》 - International Conference on Cloud Computing | Services Conference Federation - 2025, - 56～68 - 共13页

摘要：Cloud computing has recently gained popularity | . Cloud-native systems are expected to host more than 95 | % of digital workloads. Cloud* service providers face* | widespread favor for predicting extremely nonlinear cloud | due to its cost-effective and high-quality services

关键词： Cloud computing | Workload prediction | Domain adaption

6. An Inference Acceleration Approach for Boosting DNN Cold Start in Cloud-Edge Computing NSTL国家科技图书文献中心

Hao Tian | Haolong Xiang ... - 《Advanced Data Mining and Applications,Part I》 - International Conference on Advanced Data Mining and Applications - 2025, - 283～299 - 共17页

摘要： end. Cloud-edge computing* unleashes the potential of* | , named INAA, for boosting DNN cold start in cloud-edge | computing. Specifically, the problem is modeled to reduce | optimal computing* and bandwidth resource management are* | Nowadays, deep neural networks (DNNs) are

关键词： Cold start | Deep learning | DNN inference | Cloud-edge computing | Distributed algorithm

7. Cloud workload prediction by the DE-based Non-stationary Transformer model NSTL国家科技图书文献中心

Biying Zhang | Zhimin Qiu ... - 《Fourth International Conference on Network Communication and Information Security (ICNCIS 2024)》 - International Conference on Network Communication and Information Security - 2025, - 135160M.1～135160M.6 - 共6页

摘要：Despite the revolution and convenience cloud | computing has brought about, its huge energy usage is | . Accurate cloud* workload prediction enables cloud systems* | cloud workload data, and the lack of predictive | generalization for cloud* workload with different patterns, a*

关键词： Cloud computing | Workload prediction | Non-stationary transformer | Differential evolution

8. Leveraging LLM in Genetic Programming Hyper-heuristics for Dynamic Microservice Deployment NSTL国家科技图书文献中心

Zhengxin Fang | Hui Ma ... - 《AI 2024: Advances in Artificial Intelligence,Part I》 - Australasian Joint Conference on Artificial Intelligence - 2025, - 86～97 - 共12页

摘要：Microservice deployment in cloud* computing is* | a challenging combinatorial optimization problem | due to the complex dependencies among microservices | and the intricate trade-offs among different QoS | requirements, e.g., minimizing Energy Consumption (EC) vs

关键词： LLM | Genetic programming | Hyper-heuristics | Dynamic microservice deployment | Cloud computing

9. FaaS@Edge: Bringing Function-as-a-Service to Voluntary Computing at the Edge NSTL国家科技图书文献中心

Catarina Goncalves | Jose Simao ... - 《Economics of Grids,Clouds,Systems,and Services》 - International Conference on Economics of Grids,Clouds,Systems,and Services - 2025, - 28～42 - 共15页

摘要： cloud computing model ideal for processing vast | computing environments, facilitating low latency and | Function-as-a-Service (FaaS) is an emerging | amounts of data generated by the Internet of Things | . However, existing FaaS approaches struggle to leverage

关键词： Function-as-a-Service | Edge computing | Cloud computing | Volunteer computing | Peer-to-Peer data networks

10. FusionFlow: Neural Fusion and Compression for Communication-Efficient Edge-Cloud Collaborative Computing NSTL国家科技图书文献中心

Ningkang Zhang | Guangyu Wu ... - 《Wireless Artificial Intelligent Computing Systems and Applications,Part II》 - International Conference on Wireless Artificial Intelligent Computing Systems and Applications - 2025, - 516～527 - 共12页

摘要：) partitioning, an edge-cloud* collaborative computing technique* | Things (IoT) and edge computing, there's a surge in | labeling in the cloud, the servers need to receive both | With the recent advancement of the Internet of | demand for effective intelligent data analytics

摘要：Cloud computing is widely used in all walks of | query supporting homoionym search in cloud computing | being outsourced to cloud* servers to reduce overhead* | . The untrustworthiness of cloud* servers puts the* | encrypted and stored on the cloud* server, the operation of*

关键词： Graph data | Adjacency query | Searchable encryption | Cloud computing

摘要：Cloud computing has revolutionized the ability | information from the cloud, but traditional keyword search | techniques are vulnerable to attacks from cloud* service* | to store and analyze vast quantities of data in a | manner that is both economical and adaptable. Keyword

关键词： Cloud computing | Encryption | Decryption | Cipher text

摘要： application of cloud* computing, container technology has* | algorithm design based on cloud* computing technology to* | With the rapid development and widespread | become a hot topic for enterprises and research | institutions in recent years. This article proposes an

关键词： Cloud computing technology | Container arrangement | Resource optimization algorithm | Experiment and verification

摘要： cloud-edge collaboration solution possesses powerful | computing and storage capabilities along with relatively | within the IoVs assisted by cloud-edge collaboration to | allocation of computing, caching, and communication | strategy performs better than the existing cloud-edge

关键词： IoVs | Routing | Cloud computing

摘要：Cloud computing has recently gained popularity | . Cloud-native systems are expected to host more than 95 | % of digital workloads. Cloud* service providers face* | widespread favor for predicting extremely nonlinear cloud | due to its cost-effective and high-quality services

关键词： Cloud computing | Workload prediction | Domain adaption

摘要： end. Cloud-edge computing* unleashes the potential of* | , named INAA, for boosting DNN cold start in cloud-edge | computing. Specifically, the problem is modeled to reduce | optimal computing* and bandwidth resource management are* | Nowadays, deep neural networks (DNNs) are

关键词： Cold start | Deep learning | DNN inference | Cloud-edge computing | Distributed algorithm

摘要：Despite the revolution and convenience cloud | computing has brought about, its huge energy usage is | . Accurate cloud* workload prediction enables cloud systems* | cloud workload data, and the lack of predictive | generalization for cloud* workload with different patterns, a*

关键词： Cloud computing | Workload prediction | Non-stationary transformer | Differential evolution

摘要：Microservice deployment in cloud* computing is* | a challenging combinatorial optimization problem | due to the complex dependencies among microservices | and the intricate trade-offs among different QoS | requirements, e.g., minimizing Energy Consumption (EC) vs

关键词： LLM | Genetic programming | Hyper-heuristics | Dynamic microservice deployment | Cloud computing

摘要： cloud computing model ideal for processing vast | computing environments, facilitating low latency and | Function-as-a-Service (FaaS) is an emerging | amounts of data generated by the Internet of Things | . However, existing FaaS approaches struggle to leverage

关键词： Function-as-a-Service | Edge computing | Cloud computing | Volunteer computing | Peer-to-Peer data networks

摘要：) partitioning, an edge-cloud* collaborative computing technique* | Things (IoT) and edge computing, there's a surge in | labeling in the cloud, the servers need to receive both | With the recent advancement of the Internet of | demand for effective intelligent data analytics

关键词： Communication efficiency | Edge intelligence | Model partitioning

4008-161-200 800-990-8900

国家科技图书文献中心

摘要：Cloud computing is widely used in all walks of | query supporting homoionym search in cloud computing | being outsourced to cloud servers to reduce overhead | . The untrustworthiness of cloud servers puts the | encrypted and stored on the cloud server, the operation of

关键词： Graph data | Adjacency query | Searchable encryption | Cloud computing

摘要：Cloud computing has revolutionized the ability | information from the cloud, but traditional keyword search | techniques are vulnerable to attacks from cloud service | to store and analyze vast quantities of data in a | manner that is both economical and adaptable. Keyword

关键词： Cloud computing | Encryption | Decryption | Cipher text

摘要： application of cloud computing, container technology has | algorithm design based on cloud computing technology to | With the rapid development and widespread | become a hot topic for enterprises and research | institutions in recent years. This article proposes an

关键词： Cloud computing technology | Container arrangement | Resource optimization algorithm | Experiment and verification

摘要： cloud-edge collaboration solution possesses powerful | computing and storage capabilities along with relatively | within the IoVs assisted by cloud-edge collaboration to | allocation of computing, caching, and communication | strategy performs better than the existing cloud-edge

关键词： IoVs | Routing | Cloud computing

摘要：Cloud computing has recently gained popularity | . Cloud-native systems are expected to host more than 95 | % of digital workloads. Cloud service providers face | widespread favor for predicting extremely nonlinear cloud | due to its cost-effective and high-quality services

关键词： Cloud computing | Workload prediction | Domain adaption

摘要： end. Cloud-edge computing unleashes the potential of | , named INAA, for boosting DNN cold start in cloud-edge | computing. Specifically, the problem is modeled to reduce | optimal computing and bandwidth resource management are | Nowadays, deep neural networks (DNNs) are

关键词： Cold start | Deep learning | DNN inference | Cloud-edge computing | Distributed algorithm

摘要：Despite the revolution and convenience cloud | computing has brought about, its huge energy usage is | . Accurate cloud workload prediction enables cloud systems | cloud workload data, and the lack of predictive | generalization for cloud workload with different patterns, a

关键词： Cloud computing | Workload prediction | Non-stationary transformer | Differential evolution

摘要：Microservice deployment in cloud computing is | a challenging combinatorial optimization problem | due to the complex dependencies among microservices | and the intricate trade-offs among different QoS | requirements, e.g., minimizing Energy Consumption (EC) vs

关键词： LLM | Genetic programming | Hyper-heuristics | Dynamic microservice deployment | Cloud computing

摘要： cloud computing model ideal for processing vast | computing environments, facilitating low latency and | Function-as-a-Service (FaaS) is an emerging | amounts of data generated by the Internet of Things | . However, existing FaaS approaches struggle to leverage

关键词： Function-as-a-Service | Edge computing | Cloud computing | Volunteer computing | Peer-to-Peer data networks

摘要：) partitioning, an edge-cloud collaborative computing technique | Things (IoT) and edge computing, there's a surge in | labeling in the cloud, the servers need to receive both | With the recent advancement of the Internet of | demand for effective intelligent data analytics

关键词： Communication efficiency | Edge intelligence | Model partitioning

4008-161-200 800-990-8900

国家科技图书文献中心

摘要：Cloud computing is widely used in all walks of | query supporting homoionym search in cloud computing | being outsourced to cloud* servers to reduce overhead* | . The untrustworthiness of cloud* servers puts the* | encrypted and stored on the cloud* server, the operation of*

摘要：Cloud computing has revolutionized the ability | information from the cloud, but traditional keyword search | techniques are vulnerable to attacks from cloud* service* | to store and analyze vast quantities of data in a | manner that is both economical and adaptable. Keyword

摘要： application of cloud* computing, container technology has* | algorithm design based on cloud* computing technology to* | With the rapid development and widespread | become a hot topic for enterprises and research | institutions in recent years. This article proposes an

摘要：Cloud computing has recently gained popularity | . Cloud-native systems are expected to host more than 95 | % of digital workloads. Cloud* service providers face* | widespread favor for predicting extremely nonlinear cloud | due to its cost-effective and high-quality services

摘要： end. Cloud-edge computing* unleashes the potential of* | , named INAA, for boosting DNN cold start in cloud-edge | computing. Specifically, the problem is modeled to reduce | optimal computing* and bandwidth resource management are* | Nowadays, deep neural networks (DNNs) are

摘要：Despite the revolution and convenience cloud | computing has brought about, its huge energy usage is | . Accurate cloud* workload prediction enables cloud systems* | cloud workload data, and the lack of predictive | generalization for cloud* workload with different patterns, a*

摘要：Microservice deployment in cloud* computing is* | a challenging combinatorial optimization problem | due to the complex dependencies among microservices | and the intricate trade-offs among different QoS | requirements, e.g., minimizing Energy Consumption (EC) vs

摘要：) partitioning, an edge-cloud* collaborative computing technique* | Things (IoT) and edge computing, there's a surge in | labeling in the cloud, the servers need to receive both | With the recent advancement of the Internet of | demand for effective intelligent data analytics