Which IoT protocol should you use for your design?
Rudy Ramos, Mouser Electronics
embedded.com (November 03, 2016)
One thing is for certain when it comes to designing an IoT (Internet of Things) device; it won't be standalone. Unlike the way most traditional embedded devices have been developed in the past, such as the old-style digital thermostat I have in my hallway, IoT devices will always feature some form of communication. In the majority of cases, this will be wireless-based, and the key determining factors in the selection of the way it will communicate will be the required range, the amount of data to be transferred, and the available power budget.
Thus, embedded developers will now find themselves needing to delve into the world of communication protocols, standards, and wireless specifications. Understanding wireless design is a specialist subject in itself; thankfully, the availability of a range of pre-certified, type-approved wireless modules greatly simplifies the task.
The first step in determining which protocol to use for your IoT device is to take a step back and review the OSI 7-layer model. Getting the terminology right and using this model as a way of understanding which protocol method fits where can help. Appreciating the role of the different layers (e.g., physical, transport, network) and their correlation to the task at hand (e.g., communications, data exchange, device management) helps to put everything into context.
To read the full article, click here
Related Semiconductor IP
- USB 20Gbps Device Controller
- Fault Tolerant DDR2/DDR3/DDR4 Memory controller
- 25MHz to 4.0GHz Fractional-N RC PLL Synthesizer on TSMC 3nm N3P
- AGILEX 7 R-Tile Gen5 NVMe Host IP
- 100G PAM4 Serdes PHY - 14nm
Related White Papers
- 7 warning signs that you should be concerned about your IP provider
- Which USB is Right for Your Application? (Part 2)
- How effective use of ESL tools can increase your HW/SW system design productivity
- How to use the CORDIC algorithm in your FPGA design
Latest White Papers
- aTENNuate: Optimized Real-time Speech Enhancement with Deep SSMs on RawAudio
- Combating the Memory Walls: Optimization Pathways for Long-Context Agentic LLM Inference
- Hardware Acceleration of Kolmogorov-Arnold Network (KAN) in Large-Scale Systems
- CRADLE: Conversational RTL Design Space Exploration with LLM-based Multi-Agent Systems
- On the Thermal Vulnerability of 3D-Stacked High-Bandwidth Memory Architectures