Context awareness
Modern algorithms are increasingly required to operate in diverse, dynamic, and often unpredictable environments. These environments range from real-time data streams, which demand rapid processing and decision-making, to embedded systems with strict limitations on computational resources. Additionally, algorithms must navigate complex ecosystems that include cloud infrastructures, edge computing environments, and the integration of internet of things (IoT) devices. In such varied contexts, algorithms must be resilient, adaptive, and capable of performing under different conditions and constraints. The following are emerging trends that support the development of context-aware algorithms:
- Biologically inspired algorithms: Nature serves as a rich source of inspiration for developing algorithms that can adapt to changing environments. Biologically inspired algorithms, such as genetic algorithms, ant colony optimization, and neural-inspired computing, leverage...
