Master Thesis Machine to Machine Communication Projects

         Master Thesis Machine to Machine Communication Projects is the first step in turning your invisible dream into the visible dream. We provide our best of best ideas and knowledge for the national/international level postgraduate students and research professorates with our high mission of develop next generation of scientist in machine to machine communication. You can approach us at any time through our 24/7 friendly service.

List of Premium Machine to Machine Communication Projects:

• Towards a Fog to Cloud control topology for Quality of Service aware end-to-end communication
• Architecture of a synchronized low latency network node targeted to research and education
• Modeling and optimization of packet transmission scheduling in Machine to Machine communications
• A Machine Learning Decision-Support System Improves the Internet of Things’ Smart Meter Operations [Master Thesis Machine to Machine Communication Projects]
• A Survey of Enabling Technologies of Low Power and Long Range Machine to Machine Communications
• AFT: Adaptive Fibonacci based Tuning Protocol for Service and Resource discovery in the Internet of Things
• Large scale MIMO performance analysis over cascaded α-μ MIMO channel for M2M communication
• Viability Bounds of M2M Communication using Energy-Harvesting and Passive Wake-up Radio
• Comparison of Collision Free and Contention Based Radio Access Protocols for the Internet of Things
• Massive Machine to Machine Communications in Cellular Network: Distributed Queuing Random Access Meets MIMO
• An Online Strategy of Adaptive Traffic Offloading and Bandwidth Allocation for Green M2M Communications
• Comparison Data Traffic Scheduling Techniques for Classifying QoS over 5G Mobile Networks [Master Thesis Machine to Machine Communication Projects]
• IoT-based Techniques for Online M2M Interactive Itemized Data Registration and Offline Information Traceability in a Digital Manufacturing System
• An Integrated Intelligent System for Internet of Things Device Selection and Placement in Opportunistic Networks Using Fuzzy Logic and Genetic Algorithm
• Interest, energy and physical aware coalition formation and resource allocation in smart Internet of Things applications