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- JUAN LUIS
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- HERRERA GONZÁLEZ
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- JUAN LUIS HERRERA GONZÁLEZ
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- A Developer-Focused Genetic Algorithm for IoT Application Placement in the Computing Continuum
- A Machine Learning-Based Framework to Estimate the Lifetime of Network Line Cards
- A Privacy-Aware Architecture to Share Device-to-Device Contextual Information
- A microservice architecture for access control based on long-distance facial recognition
- Context-Aware Service Delegation for Opportunistic Pervasive Computing
- Context-aware privacy-preserving access control for mobile computing
- Continuous QoS-aware adaptation of Cloud-IoT application placements
- Dantalion: Digital Twinning the Computing Continuum
- Deploying Next Generation IoT Applications Through SDN-Enabled Fog Infrastructures
- EFCC: A flexible Emulation Framework to evaluate network, computing and application deployments in the Cloud Continuum
- ELTO: Energy Efficiency-Load balancing Trade-Off Solution to Handle With Conflicting Metrics in Hybrid IP/SDN Scenarios
- Early detection of link failures through the modeling of the hardware deterioration process
- Enabling Automated Service Orchestration in a Computing Continuum with User-Owned Devices
- Enabling Reusable and Comparable xApps in the Machine Learning-Driven Open RAN
- Energy consumption and workload prediction for edge nodes in the Computing Continuum
- Energy-Efficient QoS-Aware Application and Network Configuration for Next-Gen IoT
- Enhancing Smartphone Battery Life: A Deep Learning Model Based on User-Specific Application and Network Behavior
- Evolutionary Computation for Latency Minimization in SDN Microservice Architectures
- Fog Node Placement in IoT Scenarios with Stringent QoS Requirements: Experimental Evaluation
- Human Digital Twins: Enhancing Interactions With Digital Ecosystems
- Identification and Visualization of a Patient’s Medical Record via Mobile Devices without an Internet Connection
- Improving the Energy Efficiency of Software-Defined Networks through the Prediction of Network Configurations
- Joint Optimization of Response Time and Deployment Cost in Next-Gen IoT Applications
- Joint energy efficiency and load balancing optimization in hybrid IP/SDN networks
- Latency-Optimal Network Microservice Architecture Deployment in SDN
- Logistic Regression-based Solution to Predict the Transport Assistant Placement in SDN networks
- Meeting Stringent QoS Requirements in IIoT-based Scenarios
- Minimizing Deployment Cost of Hybrid Applications
- Multi-Layered Continuous Reasoning for Cloud-IoT Application Management
- Multi-Objective Genetic Algorithm for the Joint Optimization of Energy Efficiency and Rule Reduction in Software-Defined Networks
- Multi-Objective Optimal Deployment of SDN-Fog Infrastructures and IoT Applications
- OPPNets and Rural Areas: An Opportunistic Solution for Remote Communications
- On the tradeoff between load balancing and energy-efficiency in hybrid IP/SDN networks
- Optimal Deployment of Fog Nodes, Microservices and SDN Controllers in Time-Sensitive IoT Scenarios
- Optimizing response time in SDN-edge environments for time-strict IoT applications
- Optimizing the Response Time in SDN-Fog Environments for Time-Strict IoT Applications
- Orchestrating Microservice-based SDN Controllers: The MSN Realistic Use Case
- Personal data gentrification
- Predicting Response Time in SDN-Fog Environments for IIoT Applications
- Privacy-aware and context-sensitive access control for opportunistic data sharing
- Providing support to IoT devices deployed in disconnected rural environment
- QoS-Aware Fog Node Placement for Intensive IoT Applications in SDN-Fog Scenarios
- Quality of Service-Adaptive Industrial Internet of Things leveraging Edge Computing and Deep Reinforcement Learning The Deep QoS-Adaptive Learning Environment (DeQALE) Architecture
- The Service Node Placement Problem in Software-Defined Fog Networks
- XSTART: XApp Simulated Evaluation Environment for Developers
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