## 6 Key Challenges and Future Directions
### Limitations of Current WebAssembly Implementations
Even then, the device's resource constraints, such as memory, CPU power, or battery life, can limit the complexity or the number of Wasm modules that can be used. * **Interactions with IoT Protocols*
* IoT applications often communicate using IoT-specific protocols such as MQTT, CoAP, and DDS. Currently, Wasm cannot directly interact with these protocols because it has no direct access to the underlying system or network I/O operations. Therefore, developers need to rely on JavaScript or the host environment to manage these interactions, which may not always be feasible or efficient in an IoT context. The existing interoperability issues pose hurdles for developers, and addressing these challenges is a critical area of focus in the ongoing evolution of Wasm. With further development and enhancements, Wasm's impact on the IoT world could be revolutionary, turning these challenges into opportunities for creating more robust, efficient, and secure IoT applications. * **Memory Management*
* The manual memory management required by Wasm's design can pose challenges for developers used to languages with automatic memory management. This can lead to a steep learning curve and potential memory management issues. In the context of Wasm and IoT, managing memory efficiently presents a distinct set of challenges. The uniqueness of the Wasm memory model and the often resource-constrained nature of IoT devices amplify these challenges. * **Wasm's Linear Memory Model*
* Wasm employs a linear memory model in which all data (both code and state) are stored in a large contiguous block of memory. This model is simple and efficient, making it easy for the Wasm virtual machine to manage memory. However, it means that the application must manually manage memory allocation and
deallocation. This is a complex task and prone to human error, with potentially serious consequences such as memory leaks or buffer overflows. * **Lack of Automatic Garbage Collection*
* Wasm does not yet have support for automatic garbage collection, which is a feature found in many high-level languages that automatically reclaims memory no longer in use. Although there is ongoing work to add garbage collection support to Wasm, the lack of it currently means that developers must manually manage memory, increasing the complexity of developing Wasm applications. This issue is particularly important in the context of IoT, where devices are often constrained in terms of memory resources. An IoT application with inefficient memory usage can easily consume too much memory, potentially causing the device to crash or behave unpredictably. * **Limited Memory Resources on IoT Devices*
* IoT devices range from powerful edge servers to tiny sensors with very limited processing power and memory. For devices at the lower end of this spectrum, the relatively large size of the Wasm runtime and the memory consumed by Wasm applications can be a significant problem. Developers must carefully optimize their applications to reduce memory usage, a task that is made more difficult by the current limitations of Wasm's memory management. * **Difficulty Debugging Memory Issues*
* Wasm's binary nature and the lack of a built-in debugger make debugging memory-related issues challenging. While developers can use tools such as source maps to map the Wasm code back to the original source code, these tools might not always provide enough information to diagnose a memory problem. Additionally, the linear memory model of Wasm is very low-level, making it difficult to understand how memory is being used and where potential problems might lie. * **Limited Access to Web APIs*
* Wasm modules do not have direct access to web APIs and need to go through JavaScript, which can result in performance bottlenecks and increased complexity. Wasm's integration into the web ecosystem presents unique challenges, particularly in the context of access to web APIs.