Improving performance and security in IoT wearables
By Pritesh Mandaliya, Cypress Semiconductor
Many IoT applications – including connected cars, factory automation, smart city, connected health, and wearables – require nonvolatile memory to store data and code. Traditionally, embedded applications have used external Flash memory for this purpose.
However, as modern semiconductor technology faces challenges in scaling and cost as it moves to smaller geometries, it has become increasingly difficult to embed Flash memory within the host SoC. Therefore, future MCU or SoC designs are targeting system-in-package (SiP) or the use of external Flash. This trend does not address the needs of IoT applications like wearables because of their small form factor, strict cost constraints, and low-power related requirements.
To address these issues, Flash memory manufacturers are developing architectures that optimize size and power consumption. At the same time, they are introducing important new capabilities that support greater endurance, reliability, security, and safety.
To read the full article, click here
Related Semiconductor IP
- Ultra-Low-Power LPDDR3/LPDDR2/DDR3L Combo Subsystem
- Parameterizable compact BCH codec
- 1G BASE-T Ethernet Verification IP
- Network-on-Chip (NoC)
- Microsecond Channel (MSC/MSC-Plus) Controller
Related Articles
- How to achieve better IoT security in Wi-Fi modules
- IoT Security: Exploring Risks and Countermeasures Across Industries
- The Growing Imperative Of Hardware Security Assurance In IP And SoC Design
- Achieving Lower Power, Better Performance, And Optimized Wire Length In Advanced SoC Designs
Latest Articles
- Leveraging FPGAs for Homomorphic Matrix-Vector Multiplication in Oblivious Message Retrieval
- Extending and Accelerating Inner Product Masking with Fault Detection via Instruction Set Extension
- ioPUF+: A PUF Based on I/O Pull-Up/Down Resistors for Secret Key Generation in IoT Nodes
- In-Situ Encryption of Single-Transistor Nonvolatile Memories without Density Loss
- David vs. Goliath: Can Small Models Win Big with Agentic AI in Hardware Design?