All Stories

  1. Monitoring 5G Core Networks Vulnerabilities With eBPF
  2. AIChronoLens: AI/ML Explainability for Time Series Forecasting in Mobile Networks
  3. DeExp: Revealing Model Vulnerabilities for Spatio-Temporal Mobile Traffic Forecasting With Explainable AI
  4. Twinning Commercial Network Traces on Experimental Open RAN Platforms
  5. Unveiling the 5G Mid-Band Landscape: From Network Deployment to Performance and Application QoE
  6. Handling Data Handoff of AI-Based Applications in Edge Computing Systems
  7. EXPLORA: AI/ML EXPLainability for the Open RAN
  8. waveSLAM: Empowering Accurate Indoor Mapping Using Off-the-Shelf Millimeter-wave Self-sensing
  9. Characterizing and Modeling Mobile Networks User Traffic at Millisecond Level
  10. A study on 5G performance and fast conditional handover for public transit systems
  11. Spotting Deep Neural Network Vulnerabilities in Mobile Traffic Forecasting with an Explainable AI Lens
  12. In-depth study of RNTI management in mobile networks: Allocation strategies and implications on data trace analysis
  13. Characterizing Location Management Function Performance in 5G Core Networks
  14. Uncovering 5G Performance on Public Transit Systems with an App-based Measurement Study
  15. Experimenting with localization management functions in 5G core networks
  16. Opportunities and Challenges for Virtual Reality Streaming over Millimeter-Wave: An Experimental Analysis
  17. Mobility-Driven and Energy-Efficient Deployment of Edge Data Centers in Urban Environments
  18. Toward native explainable and robust AI in 6G networks: Current state, challenges and road ahead
  19. A mobility-based deployment strategy for edge data centers
  20. Traffic-Driven Sounding Reference Signal Resource Allocation in (Beyond) 5G Networks
  21. OctoMap: Supporting Service Function Chaining via Supervised Learning and Online Contextual Bandit
  22. On blockchain integration into mobile crowdsensing via smart embedded devices: A comprehensive survey
  23. The CORONA business in modern cities
  24. Performance evaluation of hybrid crowdsensing systems with stateful CrowdSenSim 2.0 simulator
  25. Event-Based Vision: Understanding Network Traffic Characteristics
  26. A Machine-Learning-Based Framework for Optimizing the Operation of Future Networks
  27. openLEON: An end-to-end emulation platform from the edge data center to the mobile user
  28. The Impact of Human Mobility on Edge Data Center Deployment in Urban Environments
  29. Crowdsensed Data Learning-Driven Prediction of Local Businesses Attractiveness in Smart Cities
  30. Analysis of TCP Performance in 5G mm-Wave Mobile Networks
  31. Scaling Millimeter-Wave Networks to Dense Deployments and Dynamic Environments
  32. pDCell
  33. A Survey on Mobile Crowdsensing Systems: Challenges, Solutions, and Opportunities
  34. CrowdSenSim 2.0
  35. Profiling Performance of Application Partitioning for Wearable Devices in Mobile Cloud and Fog Computing
  36. Why energy matters? Profiling energy consumption of mobile crowdsensing data collection frameworks
  37. Collaborative Data Delivery for Smart City-Oriented Mobile Crowdsensing Systems
  38. OpenLEON
  39. High-Precision Design of Pedestrian Mobility for Smart City Simulators
  40. Profiling Energy Efficiency of Mobile Crowdsensing Data Collection Frameworks for Smart City Applications
  41. Sociability-Driven Framework for Data Acquisition in Mobile Crowdsensing Over Fog Computing Platforms for Smart Cities
  42. Performance and Energy Efficiency Metrics for Communication Systems of Cloud Computing Data Centers
  43. Enriching Remote Control Applications with Fog Computing
  44. Cost analysis of smart lighting solutions for smart cities
  45. Energy efficient data collection in opportunistic mobile crowdsensing architectures for smart cities
  46. On the Energy-Proportionality of Data Center Networks
  47. CrowdSenSim: a Simulation Platform for Mobile Crowdsensing in Realistic Urban Environments
  48. A Cost-Effective Distributed Framework for Data Collection in Cloud-Based Mobile Crowd Sensing Architectures
  49. Intelligent Gaming for Mobile Crowd-Sensing Participants to Acquire Trustworthy Big Data in the Internet of Things
  50. Assessing Performance of Internet of Things-Based Mobile Crowdsensing Systems for Sensing as a Service Applications in Smart Cities
  51. Game-Theoretic Recruitment of Sensing Service Providers for Trustworthy Cloud-Centric Internet-of-Things (IoT) Applications
  52. Sociability-Driven User Recruitment in Mobile Crowdsensing Internet of Things Platforms
  53. Smart Probabilistic Fingerprinting for Indoor Localization over Fog Computing Platforms
  54. Network coding-based content distribution in cellular access networks
  55. Power comparison of cloud data center architectures
  56. Network-assisted offloading for mobile cloud applications
  57. Performance Metrics for Data Center Communication Systems
  58. Energy-Efficient Computation Offloading for Wearable Devices and Smartphones in Mobile Cloud Computing
  59. NC-CELL: Network coding-based content distribution in cellular networks for cloud applications