Ad Hoc Networks [E-Book] : 12th EAI International Conference, ADHOCNETS 2020, Paris, France, November 17, 2020, Proceedings / edited by Luca Foschini, Mohamed El Kamili.
This book constitutes the refereed proceedings of the 12th International Conference on Ad Hoc Networks, ADHOCNETS 2020, held in Paris in November 2020. The conference was held virtually due to COVID-19 pandemic. The 19 full papers were selected from 36 submissions covers a variety of network paradig...
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Full text |
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Personal Name(s): | El Kamili, Mohamed, editor |
Foschini, Luca, editor | |
Edition: |
1st edition 2021. |
Imprint: |
Cham :
Springer,
2021
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Physical Description: |
XII, 225 pages 114 illustrations, 95 illustrations in color (online resource) |
Note: |
englisch |
ISBN: |
9783030673697 |
DOI: |
10.1007/978-3-030-67369-7 |
Series Title: |
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Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering ;
345 |
Subject (LOC): |
- Ad Hoc Networks
- An IoT-based Non-Invasive Diabetics Monitoring System for Crucial Conditions
- Model-based and Machine Learning Approaches for Designing Caching and Routing Algorithms
- New results on Q-routing protocol for wireless networks
- Vehicle Software Update Over ICN Architectures
- Joint Mobility-Aware UAV Placement and Routing in Multi-hop UAV Relaying Systems
- Analysis and performance of topology inference in mobile ad hoc networks
- A Stochastic Traffic Model For Congestion Detection in Multi-lane Highways
- Flexibility of Decentralized Energy Restoration in WSNs
- Carrot and Stick: Incentivizing Cooperation Between Nodes in Multihop Wireless Ad Hoc Networks
- Cost-Effective Controller Placement Problem for Software Defined Multihop Wireless Networks
- Efficient Backbone Routing in Hierarchical MANETs
- Transmission Power-Control Certificate Omission in Vehicular Ad hoc Networks
- CVNET'2020: The 1st International Workshop on Cooperative Vehicular NETworking
- Analyzing driving behavior: Towards dynamic driver profiling
- Energy Efficient Adaptive GPS Sampling Using Accelerometer Data Deep Anomaly Detector Based on Spatio-Temporal Clustering for Connected Autonomous Vehicles
- Cacao, a CAN-Bus simulation platform for secured vehicular communication.